Study on Physicians Request for Computed Tomography Examinations for Patients With Head Injury in Hospital’s Emergency Departments In East Java, Indonesia
Background and objectives: There is a lot controversy about the use of Computed tomography (CT) for patients with minor head injury. We aimed to determine the practice of guiding rules for the safety of radiation and increasing awareness of physicians about risks of ionizing radiation and find out the reasons of emergency doctors for sending head injury patients to CT scan exams. Materials and Methods: A descriptive questionnaire in the Emergency Department (ED) based study was performed to assess physicians' knowledge of radiation doses received from radiological treatments and knowledge about Clinic Decision Support rules (CDS). The questionnaire consisted of 26 questions distributed to physicians working in the emergency department in six hospitals in East Java. Finally, the data collected have been analyzed by some tests using SPSS version 15 and Smart PLS. Results: In this study 44 participants had taken part. The percentage of general knowledge and awareness that shows the response of people who work in the emergency departments was total 44 respondents, by percent 6.8% of the respondents had passably knowledge, awareness and 84.1% they were having a good knowledge and awareness and 9.1% the respondents had very good knowledge and awareness. That means almost of respondents have good knowledge and awareness. To find out if an indicator is forming a construct (latent variables) testing the convergent validity of the measurement model with a reflexive indicator assessed based on the correlation between the item score to construct scores were calculated with the help of software Smart PLS. Size reflexive considered valid if the individual has a correlation (loading) to construct (latent variables) to be measured ≥ 0.5 or the value of t-statistics should ≥1.96 (test two tailed) at a significance level of α = 0.05. If one of the indicators has a leading value <0.5,><1.96, then the indicator should be discarded (dropped) because it indicates that the indicators are not good enough to measure the construct in right. The positive influence between general knowledge and awareness against to knowledge about radiation doses can be interpreted that the better general knowledge and awareness, then it will be followed by an increase in their knowledge about radiation doses. And vice versa, the worse general knowledge and awareness, then this will decrease their knowledge about radiation doses too. Conclusion: The present study has illustrated that the level of awareness and knowledge physicians who deal with ionizing radiation in CT scan units are adequate overall. There is a good influence between the diligence in applying the principles of guidance and rules stipulated by the nuclear energy in Indonesia by physicians to adjust the use of CT in the emergency department, the majority of participants who have a good awareness & knowledge, there are some of them do not have enough knowledge.
The Complementary Roles of Computer-Aided Diagnosis and Quantitative Image A...Carestream
This presentation from RSNA explains how their similarities and differences have an impact on assessment, quality assurance and training in radiography. Read the blog at http://www.carestream.com/blog/2016/06/07/differences-between-computer-aided-diagnosis-and-quantitative-image-analysis/
Case Based Medical Diagnosis of Occupational Chronic Lung Diseases From Their...CSCJournals
The clinical decision support system using the case based reasoning (CBR) methodology of Artificial Intelligence (AI) presents a foundation for a new technology of building intelligent computer aided diagnoses systems. This Technology directly addresses the problems found in the traditional Artificial Intelligence (AI) techniques, e.g. the problems of knowledge acquisition, remembering, robust and maintenance. In this paper, we have used the Case Based Reasoning methodology to develop a clinical decision support system prototype for supporting diagnosis of occupational lung diseases. 127 cases were collected for 14 occupational chronic lung diseases, which contains 26 symptoms. After removing the duplicated cases from the database, the system has trained set of 47 cases for Indian Lung patients. Statistical analysis has been done to determine the importance values of the case features. The retrieval strategy using nearest-neighbor approaches is investigated. The results indicate that the nearest neighbor approach has shown the encouraging outcome, used as retrieval strategy. A Consultant Pathologist’s interpretation was used to evaluate the system. Results for Sensitivity, Specificity, Positive Prediction Value and the Negative Prediction Value are 95.3%, 92.7%, 98.6% and 81.2% respectively. Thus, the result showed that the system is capable of assisting an inexperience pathologist in making accurate, consistent and timely diagnoses, also in the study of diagnostic protocol, education, self-assessment, and quality control. In this paper, clinical decision support system prototype is developed for supporting diagnosis of occupational lung diseases from their symptoms and signs through employing Microsoft Visual Basic .NET 2005 along with Microsoft SQL server 2005 environment with the advantage of Object Oriented Programming technology
Presentation that gives an overview of the impact of IT on radiology, including the growing role of biomarkers and artificial intelligence and deep learning on the (future) radiology profession. The shift to precision medicine and personalized care are explained, the reasons for a re-definition of radiology are addressed.
PERFORMANCE OF DATA MINING TECHNIQUES TO PREDICT IN HEALTHCARE CASE STUDY: CH...ijdms
With the promises of predictive analytics in big data, and the use of machine learning algorithms,
predicting future is no longer a difficult task, especially for health sector, that has witnessed a great
evolution following the development of new computer technologies that gave birth to multiple fields of
research. Many efforts are done to cope with medical data explosion on one hand, and to obtain useful
knowledge from it, predict diseases and anticipate the cure on the other hand. This prompted researchers
to apply all the technical innovations like big data analytics, predictive analytics, machine learning and
learning algorithms in order to extract useful knowledge and help in making decisions. In this paper, we
will present an overview on the evolution of big data in healthcare system, and we will apply three learning
algorithms on a set of medical data. The objective of this research work is to predict kidney disease by
using multiple machine learning algorithms that are Support Vector Machine (SVM), Decision Tree (C4.5),
and Bayesian Network (BN), and chose the most efficient one.
COMPARISON AND EVALUATION DATA MINING TECHNIQUES IN THE DIAGNOSIS OF HEART DI...ijcsa
Heart disease is one of the biggest health problems in the world because of high mortality and morbidity
caused by the disease. The use of data mining on medical data brought valuable and effective life
achievements and can enhance medical knowledge to make necessary decisions. Data mining plays an
important role in the field of medical science to solve health problems and diagnose ailments in critical
conditions and in normal conditions. For this reason, in this paper, data mining techniques are used to
diagnose heart disease from a dataset that includes 200 samples from different patients. Techniques used to
diagnose heart disease include Bagging, AdaBoostM1, Random Forest, Naive Bayes, RBF Network, IBK,
and NNge that all the techniques used to diagnose heart disease use Weka tool. Then these techniques are
compared to determine which is more accurate in the diagnosis of heart disease that according to the
results, it was found that the RBF Network with the accuracy of 88.2% is the most accurate classification in
the diagnosis of heart disease.
MedicalResearch.com: Medical Research Exclusive Interviews December 14 2014Marie Benz MD FAAD
MedicalResearch.com features exclusive interviews with medical researchers from major and specialty medical research and health care journals and meetings.
Poster: Audit of Appropriateness for Brain Scan Use for Paediatric Headache a...Lyndon Woytuck
The purpose is to evaluate practice variation at the emergency department in comparison with best practice for brain imaging in children presenting with headache. The results of the study might be used to inform a clinical prediction rule in order to better stratify risk according to the American College of Radiology Appropriateness Criteria.
I created a poster for presentation and am currently working on a paper for publication in a scholarly journal.
The Complementary Roles of Computer-Aided Diagnosis and Quantitative Image A...Carestream
This presentation from RSNA explains how their similarities and differences have an impact on assessment, quality assurance and training in radiography. Read the blog at http://www.carestream.com/blog/2016/06/07/differences-between-computer-aided-diagnosis-and-quantitative-image-analysis/
Case Based Medical Diagnosis of Occupational Chronic Lung Diseases From Their...CSCJournals
The clinical decision support system using the case based reasoning (CBR) methodology of Artificial Intelligence (AI) presents a foundation for a new technology of building intelligent computer aided diagnoses systems. This Technology directly addresses the problems found in the traditional Artificial Intelligence (AI) techniques, e.g. the problems of knowledge acquisition, remembering, robust and maintenance. In this paper, we have used the Case Based Reasoning methodology to develop a clinical decision support system prototype for supporting diagnosis of occupational lung diseases. 127 cases were collected for 14 occupational chronic lung diseases, which contains 26 symptoms. After removing the duplicated cases from the database, the system has trained set of 47 cases for Indian Lung patients. Statistical analysis has been done to determine the importance values of the case features. The retrieval strategy using nearest-neighbor approaches is investigated. The results indicate that the nearest neighbor approach has shown the encouraging outcome, used as retrieval strategy. A Consultant Pathologist’s interpretation was used to evaluate the system. Results for Sensitivity, Specificity, Positive Prediction Value and the Negative Prediction Value are 95.3%, 92.7%, 98.6% and 81.2% respectively. Thus, the result showed that the system is capable of assisting an inexperience pathologist in making accurate, consistent and timely diagnoses, also in the study of diagnostic protocol, education, self-assessment, and quality control. In this paper, clinical decision support system prototype is developed for supporting diagnosis of occupational lung diseases from their symptoms and signs through employing Microsoft Visual Basic .NET 2005 along with Microsoft SQL server 2005 environment with the advantage of Object Oriented Programming technology
Presentation that gives an overview of the impact of IT on radiology, including the growing role of biomarkers and artificial intelligence and deep learning on the (future) radiology profession. The shift to precision medicine and personalized care are explained, the reasons for a re-definition of radiology are addressed.
PERFORMANCE OF DATA MINING TECHNIQUES TO PREDICT IN HEALTHCARE CASE STUDY: CH...ijdms
With the promises of predictive analytics in big data, and the use of machine learning algorithms,
predicting future is no longer a difficult task, especially for health sector, that has witnessed a great
evolution following the development of new computer technologies that gave birth to multiple fields of
research. Many efforts are done to cope with medical data explosion on one hand, and to obtain useful
knowledge from it, predict diseases and anticipate the cure on the other hand. This prompted researchers
to apply all the technical innovations like big data analytics, predictive analytics, machine learning and
learning algorithms in order to extract useful knowledge and help in making decisions. In this paper, we
will present an overview on the evolution of big data in healthcare system, and we will apply three learning
algorithms on a set of medical data. The objective of this research work is to predict kidney disease by
using multiple machine learning algorithms that are Support Vector Machine (SVM), Decision Tree (C4.5),
and Bayesian Network (BN), and chose the most efficient one.
COMPARISON AND EVALUATION DATA MINING TECHNIQUES IN THE DIAGNOSIS OF HEART DI...ijcsa
Heart disease is one of the biggest health problems in the world because of high mortality and morbidity
caused by the disease. The use of data mining on medical data brought valuable and effective life
achievements and can enhance medical knowledge to make necessary decisions. Data mining plays an
important role in the field of medical science to solve health problems and diagnose ailments in critical
conditions and in normal conditions. For this reason, in this paper, data mining techniques are used to
diagnose heart disease from a dataset that includes 200 samples from different patients. Techniques used to
diagnose heart disease include Bagging, AdaBoostM1, Random Forest, Naive Bayes, RBF Network, IBK,
and NNge that all the techniques used to diagnose heart disease use Weka tool. Then these techniques are
compared to determine which is more accurate in the diagnosis of heart disease that according to the
results, it was found that the RBF Network with the accuracy of 88.2% is the most accurate classification in
the diagnosis of heart disease.
MedicalResearch.com: Medical Research Exclusive Interviews December 14 2014Marie Benz MD FAAD
MedicalResearch.com features exclusive interviews with medical researchers from major and specialty medical research and health care journals and meetings.
Poster: Audit of Appropriateness for Brain Scan Use for Paediatric Headache a...Lyndon Woytuck
The purpose is to evaluate practice variation at the emergency department in comparison with best practice for brain imaging in children presenting with headache. The results of the study might be used to inform a clinical prediction rule in order to better stratify risk according to the American College of Radiology Appropriateness Criteria.
I created a poster for presentation and am currently working on a paper for publication in a scholarly journal.
Clinicians, Leveraging AI expertise, Understanding the
Regulatory Framework
• Clinical interpretability guiding the adoption of AI-first
differential diagnoses
• Disparity in data literacy affecting the communication of
AI among healthcare scientists
• Regulatory challenges impeding the penetration of AI
into clinical practice - from research to policymakers
Frank J. Rybicki MD, PhD, Professor and Chair, Department
of Radiology, UNIVERSITY OF OTTAWA FACULTY OF
MEDICINE
Medical Informatics: Computational Analytics in HealthcareNUS-ISS
Presented by Dr Liu Nan, Senior Research Scientist and Principal Investigator, Singapore General Hospital at ISS Seminar: How Analytics is Transforming Healthcare on 31 Oct 2014.
Diagnosis of rheumatoid arthritis using an ensemble learning approachcsandit
Rheumatoid arthritis is one of the diseases that it
s cause is unknown yet; exploring the field of
medical data mining can be helpful in early diagnos
is and treatment of the disease. In this
study, a predictive model is suggested that diagnos
es rheumatoid arthritis. The rheumatoid
arthritis dataset was collected from 2,564 patients
referred to rheumatology clinic. For each
patient a record consists of several clinical and d
emographic features is saved. After data
analysis and pre-processing operations, three diffe
rent methods are combined to choose proper
features among all the features. Various data class
ification algorithms were applied on these
features. Among these algorithms Adaboost had the h
ighest precision. In this paper, we
proposed a new classification algorithm entitled CS
-Boost that employs Cuckoo search
algorithm for optimizing the performance of Adaboos
t algorithm. Experimental results show
that the CS-Boost algorithm enhance the accuracy of
Adaboost in predicting of Rheumatoid
Arthritis.
June 2018 version
How deep learning reshapes medicine
- Brief deep learning
- Recent applications
- Specific researches
- Perspectives and future directions
IMPACT OF HEALTH INFORMATICS TECHNOLOGY ON THE IMPLEMENTATION OF A MODIFIED E...hiij
The Modified Early Warning System (MEWS) is based on a patient score that helps the medical team monitor patients to identify a patient that may be experiencing a sudden decline in care. This study consists of a detailed review of clinical data and patient outcomes to assess impact of technology and patient care.There are a total of thirteen hospitals included in this review. These facilities have implemented vitals capture and the MEWS scoring system.
Austin Ophthalmology is an open access, peer reviewed, scholarly journal dedicated to publish articles covering all areas of Ophthalmology.
The journal aims to promote latest information and provide a forum for doctors, researchers, physicians, and healthcare professionals to find most recent advances in the areas of Ophthalmology. Austin Ophthalmology accepts research articles, reviews, mini reviews, case reports and rapid communication covering all aspects of Ophthalmology.
Austin Ophthalmology strongly supports the scientific up gradation and fortification in related scientific research community by enhancing access to peer reviewed scientific literary works. Austin Publishing Group also brings universally peer reviewed journals under one roof thereby promoting knowledge sharing.
ASTUTE: Acute Stroke Telemedicine: Utility Training and Evaluation
Implementing Telemedicine in Acute Stroke and the development of a Standardised Telemedicine Tookit
Lancashire Teaching Hsopitals NHS Foundation Trust
Poster from the 'Delivering NHS services, seven days a week' event held in Birmingham on 16 November 2013
More information about this event can be found at
http://www.nhsiq.nhs.uk/news-events/events/nhs-services-seven-days-a-week.aspx
USING DATA MINING TECHNIQUES FOR DIAGNOSIS AND PROGNOSIS OF CANCER DISEASEIJCSEIT Journal
Breast cancer is one of the leading cancers for women in developed countries including India. It is the
second most common cause of cancer death in women. The high incidence of breast cancer in women has
increased significantly in the last years. In this paper we have discussed various data mining approaches
that have been utilized for breast cancer diagnosis and prognosis. Breast Cancer Diagnosis is
distinguishing of benign from malignant breast lumps and Breast Cancer Prognosis predicts when Breast
Cancer is to recur in patients that have had their cancers excised. This study paper summarizes various
review and technical articles on breast cancer diagnosis and prognosis also we focus on current research
being carried out using the data mining techniques to enhance the breast cancer diagnosis and prognosis.
Assessment of Health Care Workers Knowledge, Attitude and Practices of Radiat...ijtsrd
Radiological doses are low and the chances of long time effect is minimal, but it should be kept as low as reasonably achievable. Therefore health workers especially Doctors requesting for imaging must be well trained in deciding when medical imaging should be carried out and should also have accurate knowledge of the associated risk involved. This can only be achieved if a proper knowledge and safety practice is adhered to. A cross sectional study to investigate the level of health workers knowledge, about radiation safety and their attitude towards radiation safety was carried out. A self administered questionnaire for radiation safety was sent to a purposive sample of 174 Health workers at a Specialist Hospital, in Jos, Plateau State, Nigeria. 169 questionnaires were filled and return by participant responsive rate 97.1 . The sample include 8 Radiologist, 72 Nurses, 3 Oncologist, 49 Clinicians, 26 Technicians and 11 Surgeons. Majority of the participants have never attain any radiation safety related training 76 . Radiologist and oncologist who were more frequently expose to ionizing radiation, their knowledge was not far better than the other health workers. The general knowledge score ranges from 5.9 to 60.9 , with a low score among nurses and surgeons. The most alarming was the applicability and convenience of radiation protection policies and procedure. Adherence to safety precaution practices was mostly violated by participants, especially nurses and surgeons, but they attributed it to the poor application of protective measures during performing the procedures. The investigation concluded that Health workers in a Specialist Hospital, Jos Plateau State, Nigeria have fair knowledge, negative attitude and poor safety practices towards radiation safety policies and precautions. Chenko G. Y. Nimchang | Ndam Moses Ponsel | Manset W. E. | Songden S. D "Assessment of Health Care Workers Knowledge, Attitude and Practices of Radiation Safety at a Specialist Hospital, Jos, Plateau State, Nigeria" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-6 , October 2022, URL: https://www.ijtsrd.com/papers/ijtsrd46452.pdf Paper URL: https://www.ijtsrd.com/medicine/nursing/46452/assessment-of-health-care-workers-knowledge-attitude-and-practices-of-radiation-safety-at-a-specialist-hospital-jos-plateau-state-nigeria/chenko-g-y-nimchang
EFFECTS OF X-RAY RADIATION EXPOSURE TOWARD LYMPHOCYTES OF RADIOGRAPHERS IN AB...irjes
X-ray radiation sources in ABCD Hospitalisused as one of the healthfacilities and the role of management, itis not maximized as well in providing protection against the radiographer. The use of personal protective equipmentisstilla rare thingdone right by the radiologist. This studyaimed to analyze the influence of X-ray radiation to the lymphocytes of radiographer in the ABCD Hospital. This studyis a quantitative studyconductedin 4 Hospitals in Mataram, West NusaTenggara (NTB) in June and October 2014. The populations in thisstudywere all radiographerswhoworking in ABCD Hospital as many as 30 people. The sampling technique usedis simple randomsamplingwhere a sample size of 28 people. Data wasanalyzed by usingregressionanalysis. Theseresultsindicatethat the radiologistcharacteristics affect the lymphocytes wereage (p = 0.028), radiation protection training (p = 0.046), use of APD (p = 0.026) and radiation dose (p = 0.046). Radiation protection efforts at A hospital are still not good and B, C and D hospitals are good.
Clinicians, Leveraging AI expertise, Understanding the
Regulatory Framework
• Clinical interpretability guiding the adoption of AI-first
differential diagnoses
• Disparity in data literacy affecting the communication of
AI among healthcare scientists
• Regulatory challenges impeding the penetration of AI
into clinical practice - from research to policymakers
Frank J. Rybicki MD, PhD, Professor and Chair, Department
of Radiology, UNIVERSITY OF OTTAWA FACULTY OF
MEDICINE
Medical Informatics: Computational Analytics in HealthcareNUS-ISS
Presented by Dr Liu Nan, Senior Research Scientist and Principal Investigator, Singapore General Hospital at ISS Seminar: How Analytics is Transforming Healthcare on 31 Oct 2014.
Diagnosis of rheumatoid arthritis using an ensemble learning approachcsandit
Rheumatoid arthritis is one of the diseases that it
s cause is unknown yet; exploring the field of
medical data mining can be helpful in early diagnos
is and treatment of the disease. In this
study, a predictive model is suggested that diagnos
es rheumatoid arthritis. The rheumatoid
arthritis dataset was collected from 2,564 patients
referred to rheumatology clinic. For each
patient a record consists of several clinical and d
emographic features is saved. After data
analysis and pre-processing operations, three diffe
rent methods are combined to choose proper
features among all the features. Various data class
ification algorithms were applied on these
features. Among these algorithms Adaboost had the h
ighest precision. In this paper, we
proposed a new classification algorithm entitled CS
-Boost that employs Cuckoo search
algorithm for optimizing the performance of Adaboos
t algorithm. Experimental results show
that the CS-Boost algorithm enhance the accuracy of
Adaboost in predicting of Rheumatoid
Arthritis.
June 2018 version
How deep learning reshapes medicine
- Brief deep learning
- Recent applications
- Specific researches
- Perspectives and future directions
IMPACT OF HEALTH INFORMATICS TECHNOLOGY ON THE IMPLEMENTATION OF A MODIFIED E...hiij
The Modified Early Warning System (MEWS) is based on a patient score that helps the medical team monitor patients to identify a patient that may be experiencing a sudden decline in care. This study consists of a detailed review of clinical data and patient outcomes to assess impact of technology and patient care.There are a total of thirteen hospitals included in this review. These facilities have implemented vitals capture and the MEWS scoring system.
Austin Ophthalmology is an open access, peer reviewed, scholarly journal dedicated to publish articles covering all areas of Ophthalmology.
The journal aims to promote latest information and provide a forum for doctors, researchers, physicians, and healthcare professionals to find most recent advances in the areas of Ophthalmology. Austin Ophthalmology accepts research articles, reviews, mini reviews, case reports and rapid communication covering all aspects of Ophthalmology.
Austin Ophthalmology strongly supports the scientific up gradation and fortification in related scientific research community by enhancing access to peer reviewed scientific literary works. Austin Publishing Group also brings universally peer reviewed journals under one roof thereby promoting knowledge sharing.
ASTUTE: Acute Stroke Telemedicine: Utility Training and Evaluation
Implementing Telemedicine in Acute Stroke and the development of a Standardised Telemedicine Tookit
Lancashire Teaching Hsopitals NHS Foundation Trust
Poster from the 'Delivering NHS services, seven days a week' event held in Birmingham on 16 November 2013
More information about this event can be found at
http://www.nhsiq.nhs.uk/news-events/events/nhs-services-seven-days-a-week.aspx
USING DATA MINING TECHNIQUES FOR DIAGNOSIS AND PROGNOSIS OF CANCER DISEASEIJCSEIT Journal
Breast cancer is one of the leading cancers for women in developed countries including India. It is the
second most common cause of cancer death in women. The high incidence of breast cancer in women has
increased significantly in the last years. In this paper we have discussed various data mining approaches
that have been utilized for breast cancer diagnosis and prognosis. Breast Cancer Diagnosis is
distinguishing of benign from malignant breast lumps and Breast Cancer Prognosis predicts when Breast
Cancer is to recur in patients that have had their cancers excised. This study paper summarizes various
review and technical articles on breast cancer diagnosis and prognosis also we focus on current research
being carried out using the data mining techniques to enhance the breast cancer diagnosis and prognosis.
USING DATA MINING TECHNIQUES FOR DIAGNOSIS AND PROGNOSIS OF CANCER DISEASE
Similar to Study on Physicians Request for Computed Tomography Examinations for Patients With Head Injury in Hospital’s Emergency Departments In East Java, Indonesia
Assessment of Health Care Workers Knowledge, Attitude and Practices of Radiat...ijtsrd
Radiological doses are low and the chances of long time effect is minimal, but it should be kept as low as reasonably achievable. Therefore health workers especially Doctors requesting for imaging must be well trained in deciding when medical imaging should be carried out and should also have accurate knowledge of the associated risk involved. This can only be achieved if a proper knowledge and safety practice is adhered to. A cross sectional study to investigate the level of health workers knowledge, about radiation safety and their attitude towards radiation safety was carried out. A self administered questionnaire for radiation safety was sent to a purposive sample of 174 Health workers at a Specialist Hospital, in Jos, Plateau State, Nigeria. 169 questionnaires were filled and return by participant responsive rate 97.1 . The sample include 8 Radiologist, 72 Nurses, 3 Oncologist, 49 Clinicians, 26 Technicians and 11 Surgeons. Majority of the participants have never attain any radiation safety related training 76 . Radiologist and oncologist who were more frequently expose to ionizing radiation, their knowledge was not far better than the other health workers. The general knowledge score ranges from 5.9 to 60.9 , with a low score among nurses and surgeons. The most alarming was the applicability and convenience of radiation protection policies and procedure. Adherence to safety precaution practices was mostly violated by participants, especially nurses and surgeons, but they attributed it to the poor application of protective measures during performing the procedures. The investigation concluded that Health workers in a Specialist Hospital, Jos Plateau State, Nigeria have fair knowledge, negative attitude and poor safety practices towards radiation safety policies and precautions. Chenko G. Y. Nimchang | Ndam Moses Ponsel | Manset W. E. | Songden S. D "Assessment of Health Care Workers Knowledge, Attitude and Practices of Radiation Safety at a Specialist Hospital, Jos, Plateau State, Nigeria" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-6 | Issue-6 , October 2022, URL: https://www.ijtsrd.com/papers/ijtsrd46452.pdf Paper URL: https://www.ijtsrd.com/medicine/nursing/46452/assessment-of-health-care-workers-knowledge-attitude-and-practices-of-radiation-safety-at-a-specialist-hospital-jos-plateau-state-nigeria/chenko-g-y-nimchang
EFFECTS OF X-RAY RADIATION EXPOSURE TOWARD LYMPHOCYTES OF RADIOGRAPHERS IN AB...irjes
X-ray radiation sources in ABCD Hospitalisused as one of the healthfacilities and the role of management, itis not maximized as well in providing protection against the radiographer. The use of personal protective equipmentisstilla rare thingdone right by the radiologist. This studyaimed to analyze the influence of X-ray radiation to the lymphocytes of radiographer in the ABCD Hospital. This studyis a quantitative studyconductedin 4 Hospitals in Mataram, West NusaTenggara (NTB) in June and October 2014. The populations in thisstudywere all radiographerswhoworking in ABCD Hospital as many as 30 people. The sampling technique usedis simple randomsamplingwhere a sample size of 28 people. Data wasanalyzed by usingregressionanalysis. Theseresultsindicatethat the radiologistcharacteristics affect the lymphocytes wereage (p = 0.028), radiation protection training (p = 0.046), use of APD (p = 0.026) and radiation dose (p = 0.046). Radiation protection efforts at A hospital are still not good and B, C and D hospitals are good.
An approach for radiation dose reduction in computerized tomographyIJECEIAES
Minimization of radiation dose plays an important role in human wellbeing. Excess of radiation dose leads to cancer. Radiation greatly affects young children less than 10 years of age as their life span is longer. Radiation can be reduced by hardware and/or by software techniques. Hardware methods deal with variation of parameters such as tube voltage, tube current, exposure time, focal distance and filter type. Software techniques include image processing methods. The originally acquired X-ray images may be contaminated with noise due to the fact of instability in the case of sensors, electrical power or X-ray source, that is responsible for the degradation of the image attributes. An enhanced image denoising algorithm has been proposed which decreases Gaussian noise combined with salt and pepper noise that retains most information particulars.
A KNOWLEDGE BASED AUTOMATIC RADIATION TREATMENT PLAN ALERT SYSTEMijaia
In radiation therapy, preventing treatment plan errors is of paramount importance. In this paper, an alert system is proposed and developed for checking if the pending cancer treatment plan is consistent with the intended use. A key step in the development of the paper is characterization of various treatment plan fingerprints by three-dimension vectors taken from possibly thousands of variables in each treatment plan. Then three machine learning based algorithms are developed and tested in the paper. The first algorithm is a knowledge-based support vector machine method. If an incorrect treatment plan were offered, the algorithm would tell that the pending treatment plan is inconsistent with the intended use and provide a red flag. The algorithm is tested on the actual patient data sets with 100% successful rate and 0% failure rate. In addition, two algorithms based on the well-known k-nearest neighbour and Bayesian approach respectively are developed. Similar to the support vector machine algorithm, these two algorithms are also tested with 100% success rate and 0% failure rate. The key seems to pick up the right features.
Evaluation of SVM performance in the detection of lung cancer in marked CT s...nooriasukmaningtyas
This paper concerns the development/analysis of the IQ-OTH/NCCD lung cancer dataset. This CT-scan dataset includes more than 1100 images of diagnosed healthy and tumorous chest scans collected in two Iraqi hospitals. A computer system is proposed for detecting lung cancer in the dataset by using image-processing/computer-vision techniques. This includes three preprocessing stages: image enhancement, image segmentation, and feature extraction techniques. Then, support vector machine (SVM) is used at the final stage as a classification technique for identifying the cases on the slides as one of three classes: normal, benign, or malignant. Different SVM kernels and feature extraction techniques are evaluated. The best accuracy achieved by applying this procedure on the new dataset was 89.8876%.
The students at Wilmington High School have Career Day to generate interest in all the many careers they may choose to pursue. Here is the Power Point presentation I developed to help explain the job of being a Radiation Therapist.
Investigations have been done concerning computed tomography (CT) dose output of some selected hospitals in the Federal capital Territory, Abuja, Nigeria by calculating the Effective doses of CT head in some selected hospitals and compare its average with the Mean Reference Dose of CT Head. Data was collected at five hospitals in the Federal Capital Territory, Abuja, Nigeria. The Effective Dose of each of the patients undergoing CT Head examination was calculated using the coefficient factor and the DLP values. Patients’ CT dose data from the ages of 18 to 60years from each of the 5 centres for each study types from January, 2013 to December, 2014 were extracted. A total of 181 patients’ CT dose data was extracted. The effective dose range for CT Head examination in Abuja, Federal Capital Territory is 1.8 to 6.8mSv.
Teleradiology is a branch of telemedicine in which telecommunication systems are used to transmit radiological images from one location to another. Interpretation of all noninvasive imaging studies, such as digitized x-rays, CT, MRI, ultrasound, and nuclear medicine studies, can be carried out in such a manner.
The first steps in teleradiology date back to 1929 when a medical image was transmitted via telegraph to a distant location
Advances in automatic tuberculosis detection in chest x ray imagessipij
Tuberculosis (TB) is very dangerous and rapidly spread disease in the world. In the investigating cases for
suspected tuberculosis (TB), chest radiography is not only the key techniques of diagnosis based on the
medical imaging but also the diagnostic radiology. So, Computer aided diagnosis (CAD) has been popular
and many researchers are interested in this research areas and different approaches have been proposed
for the TB detection and lung decease classification. In this paper, the medical background history of TB
decease in chest X-rays and a survey of the various approaches in TB detection and classification are
presented. The literature in the related methods is surveyed papers in this research area until now 2014.
Current literature on dental radiology was reviewed in order to seek justification for radiological protection of patients in dental radiography, to explore the different factors affecting patient dose and to derive practical guidance on how to achieve radiological protection of patients in dentistry. Individual doses incurred in dental radiology are in general relatively low, however it is generally accepted that there is no safe level of radiation dose and that no matter how low the doses received are, there is a mathematical probability of an effect. Hence appropriate patient protection measures must be instituted to keep the exposures as low as reasonably achievable (ALARA). The literature review demonstrated that there is considerable scope for significant dose reductions in dental radiology using the techniques of optimization of protection.
Most dental professionals are not convinced of the need for regulatory control of dental radiography practice. They believe doses are too low to warrant regulatory control and consequently patient protective measures. This study shows that individual doses in dental radiology are relatively low. However, there is no safe level of radiation dose and that no
matter how low the doses received are, there is a
mathematical probability of an effect. Consequently, appropriate patient protection measures must be instituted to keep exposures as low as reasonably achievable (ALARA).
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Study on Physicians Request for Computed Tomography Examinations for Patients With Head Injury in Hospital’s Emergency Departments In East Java, Indonesia
1. International Refereed Journal of Engineering and Science (IRJES)
ISSN (Online) 2319-183X, (Print) 2319-1821
Volume 6, Issue 3 (March 2017), PP.80-85
www.irjes.com 80 | Page
Study on Physicians Request for Computed Tomography Examinations for
Patients With Head Injury in Hospital’s Emergency Departments In East
Java, Indonesia
Aiman Mohamed Sadeg1
, Johan AE Noor2
,Yuyun Yueniwati3
1
(Dept. Of Physics, Faculty Of Sciences, Brawijaya University, Malang 65145, East Java, Indonesia)
2
(Dept. Of Emergency, Six General Hospitals, East Java, Indonesia)
ABSTRACT:-
Background and objectives: There is a lot controversy about the use of Computed tomography (CT) for
patients with minor head injury. We aimed to determine the practice of guiding rules for the safety of radiation
and increasing awareness of physicians about risks of ionizing radiation and find out the reasons of emergency
doctors for sending head injury patients to CT scan exams.
Materials and Methods: A descriptive questionnaire in the Emergency Department (ED) based study was
performed to assess physicians' knowledge of radiation doses received from radiological treatments and
knowledge about Clinic Decision Support rules (CDS). The questionnaire consisted of 26 questions distributed
to physicians working in the emergency department in six hospitals in East Java. Finally, the data collected have
been analyzed by some tests using SPSS version 15 and Smart PLS.
Results: In this study 44 participants had taken part. The percentage of general knowledge and awareness that
shows the response of people who work in the emergency departments was total 44 respondents, by percent
6.8% of the respondents had passably knowledge, awareness and 84.1% they were having a good knowledge
and awareness and 9.1% the respondents had very good knowledge and awareness. That means almost of
respondents have good knowledge and awareness. To find out if an indicator is forming a construct (latent
variables) testing the convergent validity of the measurement model with a reflexive indicator assessed based on
the correlation between the item score to construct scores were calculated with the help of software Smart PLS.
Size reflexive considered valid if the individual has a correlation (loading) to construct (latent variables) to be
measured ≥ 0.5 or the value of t-statistics should ≥1.96 (test two tailed) at a significance level of α = 0.05. If one
of the indicators has a leading value <0.5, or the value of the t-statistic <1.96, then the indicator should be
discarded (dropped) because it indicates that the indicators are not good enough to measure the construct in
right. The positive influence between general knowledge and awareness against to knowledge about radiation
doses can be interpreted that the better general knowledge and awareness, then it will be followed by an increase
in their knowledge about radiation doses. And vice versa, the worse general knowledge and awareness, then this
will decrease their knowledge about radiation doses too.
Conclusion: The present study has illustrated that the level of awareness and knowledge physicians who deal
with ionizing radiation in CT scan units are adequate overall. There is a good influence between the diligence in
applying the principles of guidance and rules stipulated by the nuclear energy in Indonesia by physicians to
adjust the use of CT in the emergency department, the majority of participants who have a good awareness &
knowledge, there are some of them do not have enough knowledge.
Keywords: - Awareness & knowledge, Radiation doses, Radiation side effects, CT scan procedures,
Physicians in the emergency departments.
I. INTRODUCTION
Radiological examinations are an essential tool for the evaluation of many disorders in daily practice.
Most of them, especially computed tomography (CT), use ionizing radiation, which has adverse biological
effects [1]. Radiation is energy in the form of waves of particles. There are two forms of radiation non-ionizing
and ionizing radiation. It is well known that ionizing radiation has biological damaging effects, either affecting
the cell directly or indirectly via the production of free radicals. Both lead to DNA damage, including single or
double-strand breaks, and or DNA, protein cross-links [2]. Figure (1) explain to Biological effect of ionizing
radiation in the page.
2. Study On Physicians Request For Computed Tomography Examinations For ….
www.irjes.com 81 | Page
Figure 1 Biological effect of ionizing radiation [3]
Wilhelm Roentgen first discovered ionizing radiation in the form of x-rays in 1895, while performing
experiments with cathode rays. In the 1970s, CT was introduced as an innovative x-ray imaging tool. This
technology was invented by electrical engineer Godfrey N. Hounsfield of Central Research Laboratories
(London) in 1972, along with physicist Allan M. Also in 1972, the first CT head scanner was developed, and the
first commercial unit of this prototype was installed in the USA, in 1973. Between 1974 and 1976, CT scanners
began to be installed and used in medical institutions [4].
Computed tomography (CT) use in the evaluation of emergency department (ED) patients increased
significantly during the last decade [5]. This trend has contributed to increasing health care costs and growing
patient exposure to ionizing radiation [6]. However, it is unclear whether the increase in CT radiation is due to
an increase of inappropriate use of CT scans. It has been suggested that commitment to evidence based Clinical
Decision Support (CDS) can lead to more judicious use of CT scans in EDs [7].
The Canadian and New Orleans head CT rules are two of the most widely validated CDS for mTBI.
The derivation and verification cohorts for these two CDS were composed of patients with blunt head trauma
who either had loss of consciousness (LOC), amnesia or disorientation. The deficiency in the knowledge of a
medical doctor might alter the expected benefits compared to the risk involved, and can affect medical
decisions[8].
As a result of the increased visibility of cases of cancer and other side effects as a result of large doses
that are exposed during CT imaging, the Physicians need to have a clear understanding of the radiation risks
associated with specific imaging examinations [9]. The physicians act as gatekeepers, referring their patients for
imaging procedures and having open access to all imaging examinations including CT. Finally, the reason for
choosing this problem is how we can minimize[10] the increasing exposure and unjustified to ionizing radiation
in the CT examination, when it is ordered using computed tomography in emergency department with minor
brain injury and the best ways followed by the physician for estimating dose to the patient per year before the
CT examination in the emergency department.
The main problems underline in this research can be made such the following questions: How to
evaluation on request computed tomography the head for patients with minor head injury in the emergency
department in six hospitals in East Java?
Moreover, the Benefits of the Research were,
Reduce the risks of radiation resulting CT scans.
Improve awareness and knowledge of physician in the emergency department.
Curbing exceeds clinic design support.
Finally Research Limitations
The study was carried out in the Emergency Department that employ CT scan.
The survey was targeting the physicians of Emergency Department who works in the emergency
department.
The study has covered six general hospitals in East Java.
3. Study On Physicians Request For Computed Tomography Examinations For ….
www.irjes.com 82 | Page
II. MATERIALS AND METHODS
This study would try to evaluation on request for computed tomography for patients with minor head
injury in the emergency department and determines the practice of guiding rules for the safety of radiation and
increasing awareness of physicians about risks of ionizing radiation. In particular Ionizing radiation has long-
term risks, including cancer. That the research focused on Improve awareness and knowledge of physicians in
the emergency department. The study has been done in the Emergency Departments in the six hospitals in East
Java in Indonesia that can mention as; Then, the data (RKZ Panti Waluya hospital, RSUD Ngudi Waluyo
Wlingi hospital, RSUD dr Soedono Madiun hospital, RS Abdoer Rahim Situbondo hospital, Persada hospital,
RSUD Lawang hospital). Then, the data have collected in almost three months from September to November
2016 and the data were analyzed by using software called Statistical Package for the Social Sciences “SPSS”
and Partial Least Squares (PLS) method. By studying the relationship between awareness and knowledge,
including the other variables (through knowledge about radiation doses and knowledge about side effects) to get
a CT scan procedure proper treatment so note the relationship between awareness and knowledge between
knowledge about radiation doses and side effects that affect the adjust the using computed tomography. Figure
(2) will show the relationship among awareness & knowledge, knowledge about radiation doses, knowledge
about side effects and to get a CT scan procedure proper treatment.
Figure 2 Conceptual Framework
The numbers of questions that has been written down for each variable were as follows: 13 questions
about general awareness & knowledge, 4 questions about CT scan procedures, proper treatment, 6 questions
about knowledge about side effects and 3 questions about radiation doses knowledge
Operational Definitions
Physicians in the emergency departments: they are the people who work in the emergency department in
the hospital. However, the study is going to focus on this sample.
Radiation doses: it rather means absorbed dose which is a physical dose quantity representing the mean
energy imparted to matter per unit mass by ionizing radiation. In the SI system of units, the unit of measure
is joules per kilogram that named Gray (Gy) as has already mentioned.
Radiation side effects: as a result of getting high doses of X-ray that let to get bad effects of the exposure.
Moreover, these effects may lead to cause disease and cancer cells.
CT scan procedures: A computed tomography (CT) scan uses X-rays to make detailed pictures of structures
inside of the body. During the test, you will lie on a table that is attached to the CT scanner, which is a large
doughnut-shaped machine. The CT scanner sends X-rays through the body area being studied.
III. RESULTS & DISCUSSION
The first survey has carried out in East Java, Indonesia with the aim of how to evaluation on request
Computed Tomography (CT) scans of the head in patients with minor head injury in the Emergency Department
and determines the practice of guiding rules for the safety of radiation and increasing awareness of physicians
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about risks of ionizing radiation. In total, out of the 50 questionnaires had been distributed, 44 questionnaires
were returned with completed answers. In the survey results, it shows the respondents, including gender, age,
degree, the duration of experience and the person‟s career. For example:
1. Identity of Respondents by Gender
Table 1 The Gender participants from the analysis
Frequency Percent
Male
Female
Total
21
23
44
47.7%
52.3%
100%
Table 1 The Gender participants from the analysis that shows the response of people who work in the
emergency departments was total 44 respondents, by percent 47.7% of the respondents were male and 53.5%
were female. The reason that makes the percentage of women is higher because in Indonesia they have a higher
population rate than men as shows figure (3) the percentage of gender.
Figure 3 The percentage of gender
IV. INTERPRETATION OF THE RESULT
4.1Analysis using PLS
4.1.1Convergent Validity
Size reflexive considered valid if the individual has a correlation (loading) to construct (latent
variables) to be measured ≥ 0.5 or the value of t-statistics should ≥1.96 (test two tailed) at a significance level of
α= 0.05. If one of the indicators has a leading value <0.5, or the value of the t-statistic <1.96, then the indicator
should be discarded (dropped) because it indicates that the indicators are not good enough to measure the
construct in right
4.1.2Construct Dependent Evaluation
Evaluation of the model using the R-square (R2
) to construct the dependent, R-square value reflects the
overall predictive power of the model with a limit of R-square values greater than 0.10 or greater than 10
percent (or goodness-fit of the model) [10]. Figure (4) to explain Structural Equation With Partial Least Square
Approach Using Software Smart PLS (Measurement Model Specification)
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Figure 4 Structural Equation With Partial Least Square Approach Using Software Smart PLS
(Measurement Model Specification)
V. CONCLUSION
Based on the current results of a survey on the awareness and knowledge of physicians about the
benefit and risk of ionizing radiation in computer tomography (CT) units in the emergency department. The
findings demonstrated that as follow:
1. The level of awareness and knowledge physicians who deal with ionizing radiation in CT scan units are
adequate overall.
2. There is a good influence between the diligence in applying the principles of guidance and rules stipulated
by the nuclear energy (BAPETEN) in Indonesia by physicians to adjust the use of CT in the emergency
department.
3. Finally, from the research results it can be concluded that, besides to the majority of participants who have
a good awareness & knowledge, there are some of them do not have enough knowledge.
On the other hand, in versus there a number of previous studies and reports are in disagreement with present
study [11], [12], [13]. Recommendations Based on the findings of the study, it can provide the recommendations
as follow:
1. The hospitals should provide some courses or workshops occasionally to enhance or keep the level of
awareness of physicians about ionizing radiation.
2. Through this research I recommend that there be keen more on the application of clinical decision support
rules by the physicians in the emergency department.
3. Hopefully it can be the existence of specialist medical physics in hospitals is important to avoid the
unjustified use of radiation.
4. According to the responses, CT scan must be available in an Emergency Department in each hospital.
ACKNOWLEDGEMENTS
The authors declare that there is no conflict of interests regarding the publication of this paper.
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