Elinext developed a tool for automated image analysis to detect lungs pneumonia.
Source: https://www.elinext.com/case-study/web/pneumonia-diagnosis-tool/
Computer Vision Applications - White Paper Addepto
Computer vision (CV) is an artificial intelligence-based technology that allows computers to observe the world. Find out in our white paper what tools are used to create computer vision solutions. The number of computer vision applications grow every year. Check out real-life examples in retail and marketing industry.
DETECTING EMOTION FROM FACIAL EXPRESSION HAS BECOME AN URGENT NEED BECAUSE OF
ITS IMMENSE APPLICATIONS IN ARTIFICIAL INTELLIGENCE SUCH AS HUMAN-COMPUTER
COLLABORATION, DATA DRIVEN ANIMATION, HUMAN-ROBOT COMMUNICATION ETC. SINCE IT
IS A DEMANDING AND INTERESTING PROBLEM IN COMPUTER VISION, SEVERAL WORKS HAD
BEEN CONDUCTED REGARDING THIS TOPIC. THE OBJECTIVE OF THIS PROJECT IS TO DEVELOP A
FACIAL EXPRESSION RECOGNITION SYSTEM BASED ON CONVOLUTIONAL NEURAL NETWORK
WITH DATA AUGMENTATION. THIS APPROACH ENABLES TO CLASSIFY SEVEN BASIC EMOTIONS
CONSIST OF ANGRY, DISGUST, FEAR, HAPPY, NEUTRAL, SAD AND SURPRISE FROM IMAGE DATA.
CONVOLUTIONAL NEURAL NETWORK WITH DATA AUGMENTATION LEADS TO HIGHER
VALIDATION ACCURACY THAN THE OTHER EXISTING MODELS (WHICH IS 96.24%) AS WELL AS
HELPS TO OVERCOME THEIR LIMITATIONS.
Computer Vision Applications - White Paper Addepto
Computer vision (CV) is an artificial intelligence-based technology that allows computers to observe the world. Find out in our white paper what tools are used to create computer vision solutions. The number of computer vision applications grow every year. Check out real-life examples in retail and marketing industry.
DETECTING EMOTION FROM FACIAL EXPRESSION HAS BECOME AN URGENT NEED BECAUSE OF
ITS IMMENSE APPLICATIONS IN ARTIFICIAL INTELLIGENCE SUCH AS HUMAN-COMPUTER
COLLABORATION, DATA DRIVEN ANIMATION, HUMAN-ROBOT COMMUNICATION ETC. SINCE IT
IS A DEMANDING AND INTERESTING PROBLEM IN COMPUTER VISION, SEVERAL WORKS HAD
BEEN CONDUCTED REGARDING THIS TOPIC. THE OBJECTIVE OF THIS PROJECT IS TO DEVELOP A
FACIAL EXPRESSION RECOGNITION SYSTEM BASED ON CONVOLUTIONAL NEURAL NETWORK
WITH DATA AUGMENTATION. THIS APPROACH ENABLES TO CLASSIFY SEVEN BASIC EMOTIONS
CONSIST OF ANGRY, DISGUST, FEAR, HAPPY, NEUTRAL, SAD AND SURPRISE FROM IMAGE DATA.
CONVOLUTIONAL NEURAL NETWORK WITH DATA AUGMENTATION LEADS TO HIGHER
VALIDATION ACCURACY THAN THE OTHER EXISTING MODELS (WHICH IS 96.24%) AS WELL AS
HELPS TO OVERCOME THEIR LIMITATIONS.
ML Times: Mainframe Machine Learning Initiative- June newsletter (2018)Leslie McFarlin
I contributed the featured article in the June 2018 newsletter: Structure and Complexity- Algorithms, Data, and User Experience. In it, I untangle the link between data and algorithms, and how that might limit what design options we have.
The project title “SAP Development Object Testing” is a study of the software testing in the company. The project report is about software testing that is an important part of any system development process. In the initial chapter review we see that for proper functioning of the organization. It defines the organization structure of the company.
When dealing with over 300 hundred thousand of malware samples every day, we had to deploy the state-of-the-art techniques to combat cyberthreats. And among them - machine learning algorithms.
In this whitepaper, we start from describing the basic approaches and proceed to explaining the key applications of machine learning algorithms to automated malware detection. Learn more about how Kaspersky Lab protects businesses like yours => https://kas.pr/8dxv
Machine Learning in Static Analysis of Program Source CodeAndrey Karpov
Machine learning has firmly entrenched in a variety of human fields, from speech recognition to medical diagnosing. The popularity of this approach is so great that people try to use it wherever they can. Some attempts to replace classical approaches with neural networks turn up unsuccessful. This time we'll consider machine learning in terms of creating effective static code analyzers for finding bugs and potential vulnerabilities.
Top Artificial Intelligence Tools & Frameworks in 2023.pdfYamuna5
Artificial intelligence has facilitated the processing and use of data in the business world. With the growth of AI and ML, data scientists and developers now have more AI tools and frameworks to work with. We believe it's important for machine learning platforms to be easy to use for business people who need results, but also powerful enough for technical teams who want to push the boundaries of data analysis with customizable extensions. The key to success is choosing the right AI framework or machine learning library.
The adoption of digital technologies to aid in the introduction of innovative business models or alter the operations of current businesses is known as digital transformation. In the past, developing a technology-driven plan and putting it into practise might take years to complete. KTLO (keeping the Lights On), or the upkeep of current infrastructure and systems, was frequently where corporations would spend 80% of their budget and resources. However, the effects of COVID-19 on firms nearly doubled the rate of adoption of the most recent trends in digital transformation.
Bringing Machine Learning to Mobile Apps with TensorFlowMarianne Harness
Use TensorFlow an open-source platform for machine learning and provide a seamless customer experience through intelligent mobile apps to your customer.
implementing_ai_for_improved_performance_testing_the_key_to_success.pptxsarah david
Experience a revolution in software testing with our AI-driven Performance Testing solutions at Cuneiform Consulting. In a world dominated by technological advancements, implementing AI is the key to unlocking unparalleled software performance. Boost your applications with speed, scalability, and responsiveness, ensuring a seamless user experience. Cuneiform Consulting leads the way in reshaping quality assurance, adhering to the predictions of the World Quality Report for AI's significant role in the next decade. Join us to stay ahead, save costs with constant AI-powered testing, and explore the boundless possibilities of AI/ML development services. Contact us now for a future-proof digital transformation!
Human Emotion Recognition using Machine Learningijtsrd
It is quite interesting to recognize the human emotions in the field of machine learning. Using a person's facial expression one can know his emotions or what the person wants to express. But at the same time it's not easy to recognize one's emotion easily its quite challenging at times. Facial expression consist of various human emotions such as sad, happy , excited, angry, frustrated and surprise. Few years back Natural language processing was used to detect the sentiment from the text and then it took a step forward towards emotion detection. Sentiments can be positive, negative or neutral where as emotions are more refined categories. There are many techniques used to recognize emotions. This paper provides a review of research work carried out and published in the field of human emotion recognition and various techniques used for human emotions recognition. Prof. Mrs. Dhanamma Jagli | Ms. Pooja Shetty "Human Emotion Recognition using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25217.pdfPaper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/25217/human-emotion-recognition-using-machine-learning/prof-mrs-dhanamma-jagli
XYZ Fast Prototyping MGMT 3405 1 Definition – Fa.docxjeffevans62972
XYZ Fast Prototyping MGMT 3405
1
Definition – Fast Prototyping
Fast or rapid prototyping is a methodical exploration of innovative concept(s) by quick assembly
of pieces either tangible or intangible to validate assumptions which are important to
implement the concept. The outline of this concept is described in article “Intuit Inc. Project
AgriNova” published in HBR by Thomas Eisenmann and Tanya Bijlani. Quickly identifying &
rapidly developing solutions for part of the system which could be potential road blocks is key
to ensure success of the product. This does not need complete development of all (or some)
parts
Problem Statement
Our organization is specialized Business Analytics and Data Management expertise. Among
other things, one of the requests often made by our customer is to give guidance on suitability
of tool (or set of tools) for a particular task. Even though this knowledge is available within our
organization, it is dispersed as the consultants are working with different customer.
We set out to address the issue of
- timely availability of comparison metrics across tools
- continuous update to the metrics being used to compared
After discussing with our executives we decided to build a web based application internally so
that we can feed in the comparison data on continuous basis without spending too much time
on reconciliation efforts.
There were few challenges to be resolved while addressing the issues given in problem
statement. We conducted a brainstorming session within our organization. The outcome of this
session was a list of important components outline of which is as follows:
- User Interface: The UI should be easy to use and intuitive enough to hide the complexity
underneath. Unless the tool is easy to use people will be reluctant to use it.
- Data Update: The data should be fed in on continuous basis to ensure updates for the
tools to be compared are captured on regular basis. If the data is stale it will raise the
credibility issue of the presented comparison. We cannot compare data of outdated
version of the tools.
- Contextual Text Mapping: The biggest issue is contextual mapping of text which
describes a particular feature of tool, product or application.
Of course this list is not comprehensive, but we need to address these points to ensure viability
of the entire efforts.
I think using “Fast Prototyping” to validate the feasibility of the components is best course of
action before attempting to build this product.
Leap of Faith
Can we build & expand? As the data volume increase the methods employed, especially the
algorithm employed will perform satisfactorily? We decided to find this out.
Can we win? We did not spend great amount of time with user experience. We took a leap of
faith by assuming that the team who participated in building UX is representative of future
users. I think we should be able to tweak UI based on usage analytics and.
UNCOVERING FAKE NEWS BY MEANS OF SOCIAL NETWORK ANALYSISpijans
The short access to facts on social media networks in addition to its exponential upward push also made it tough to distinguish among faux information or actual facts. The quick dissemination thru manner of sharing has more high quality its falsification exponentially. It is also essential for the credibility of social media networks to avoid the spread of fake facts. So its miles rising research task to robotically check for misstatement of information thru its source, content material, or author and save you the unauthenticated assets from spreading rumours. This paper demonstrates an synthetic intelligence primarily based completely approach for the identification of the fake statements made by way of the use of social network entities. Versions of Deep neural networks are being applied to evalues datasets and have a look at for fake information presence. The implementation setup produced most volume 99% category accuracy, even as dataset is tested for binary (real or fake) labelling with multiple epochs.
UNCOVERING FAKE NEWS BY MEANS OF SOCIAL NETWORK ANALYSISpijans
The short access to facts on social media networks in addition to its exponential upward push also made it
tough to distinguish among faux information or actual facts. The quick dissemination thru manner of sharing has more high quality its falsification exponentially. It is also essential for the credibility of social media networks to avoid the spread of fake facts. So its miles rising research task to robotically check for
misstatement of information thru its source, content material, or author and save you the unauthenticated
assets from spreading rumours. This paper demonstrates an synthetic intelligence primarily based completely approach for the identification of the fake statements made by way of the use of social network
entities. Versions of Deep neural networks are being applied to evalues datasets and have a look at for
fake information presence. The implementation setup produced most volume 99% category accuracy, even
as dataset is tested for binary (real or fake) labelling with multiple epochs.
Modular web design is a system of reusable design components and patterns. These components can be combined in various ways to create websites fast, with a small effort, and for a smaller budget. But having ready patterns doesn’t mean that modular websites cannot be adjusted to needs or content. Find out more details about modular website design and its benefits in our short overview.
Data Migration Testing Purpose, Test Strategy And Scenarios.pdfElinext
Data migration testing plays a crucial role in a successful move to the cloud environment. During migration resting migrated data is compared with original data. It allows experts to identify any possible discrepancies and fix errors. Learn about the main data migration testing types, strategies, and scenarios in our paper.
ML Times: Mainframe Machine Learning Initiative- June newsletter (2018)Leslie McFarlin
I contributed the featured article in the June 2018 newsletter: Structure and Complexity- Algorithms, Data, and User Experience. In it, I untangle the link between data and algorithms, and how that might limit what design options we have.
The project title “SAP Development Object Testing” is a study of the software testing in the company. The project report is about software testing that is an important part of any system development process. In the initial chapter review we see that for proper functioning of the organization. It defines the organization structure of the company.
When dealing with over 300 hundred thousand of malware samples every day, we had to deploy the state-of-the-art techniques to combat cyberthreats. And among them - machine learning algorithms.
In this whitepaper, we start from describing the basic approaches and proceed to explaining the key applications of machine learning algorithms to automated malware detection. Learn more about how Kaspersky Lab protects businesses like yours => https://kas.pr/8dxv
Machine Learning in Static Analysis of Program Source CodeAndrey Karpov
Machine learning has firmly entrenched in a variety of human fields, from speech recognition to medical diagnosing. The popularity of this approach is so great that people try to use it wherever they can. Some attempts to replace classical approaches with neural networks turn up unsuccessful. This time we'll consider machine learning in terms of creating effective static code analyzers for finding bugs and potential vulnerabilities.
Top Artificial Intelligence Tools & Frameworks in 2023.pdfYamuna5
Artificial intelligence has facilitated the processing and use of data in the business world. With the growth of AI and ML, data scientists and developers now have more AI tools and frameworks to work with. We believe it's important for machine learning platforms to be easy to use for business people who need results, but also powerful enough for technical teams who want to push the boundaries of data analysis with customizable extensions. The key to success is choosing the right AI framework or machine learning library.
The adoption of digital technologies to aid in the introduction of innovative business models or alter the operations of current businesses is known as digital transformation. In the past, developing a technology-driven plan and putting it into practise might take years to complete. KTLO (keeping the Lights On), or the upkeep of current infrastructure and systems, was frequently where corporations would spend 80% of their budget and resources. However, the effects of COVID-19 on firms nearly doubled the rate of adoption of the most recent trends in digital transformation.
Bringing Machine Learning to Mobile Apps with TensorFlowMarianne Harness
Use TensorFlow an open-source platform for machine learning and provide a seamless customer experience through intelligent mobile apps to your customer.
implementing_ai_for_improved_performance_testing_the_key_to_success.pptxsarah david
Experience a revolution in software testing with our AI-driven Performance Testing solutions at Cuneiform Consulting. In a world dominated by technological advancements, implementing AI is the key to unlocking unparalleled software performance. Boost your applications with speed, scalability, and responsiveness, ensuring a seamless user experience. Cuneiform Consulting leads the way in reshaping quality assurance, adhering to the predictions of the World Quality Report for AI's significant role in the next decade. Join us to stay ahead, save costs with constant AI-powered testing, and explore the boundless possibilities of AI/ML development services. Contact us now for a future-proof digital transformation!
Human Emotion Recognition using Machine Learningijtsrd
It is quite interesting to recognize the human emotions in the field of machine learning. Using a person's facial expression one can know his emotions or what the person wants to express. But at the same time it's not easy to recognize one's emotion easily its quite challenging at times. Facial expression consist of various human emotions such as sad, happy , excited, angry, frustrated and surprise. Few years back Natural language processing was used to detect the sentiment from the text and then it took a step forward towards emotion detection. Sentiments can be positive, negative or neutral where as emotions are more refined categories. There are many techniques used to recognize emotions. This paper provides a review of research work carried out and published in the field of human emotion recognition and various techniques used for human emotions recognition. Prof. Mrs. Dhanamma Jagli | Ms. Pooja Shetty "Human Emotion Recognition using Machine Learning" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-3 | Issue-5 , August 2019, URL: https://www.ijtsrd.com/papers/ijtsrd25217.pdfPaper URL: https://www.ijtsrd.com/computer-science/artificial-intelligence/25217/human-emotion-recognition-using-machine-learning/prof-mrs-dhanamma-jagli
XYZ Fast Prototyping MGMT 3405 1 Definition – Fa.docxjeffevans62972
XYZ Fast Prototyping MGMT 3405
1
Definition – Fast Prototyping
Fast or rapid prototyping is a methodical exploration of innovative concept(s) by quick assembly
of pieces either tangible or intangible to validate assumptions which are important to
implement the concept. The outline of this concept is described in article “Intuit Inc. Project
AgriNova” published in HBR by Thomas Eisenmann and Tanya Bijlani. Quickly identifying &
rapidly developing solutions for part of the system which could be potential road blocks is key
to ensure success of the product. This does not need complete development of all (or some)
parts
Problem Statement
Our organization is specialized Business Analytics and Data Management expertise. Among
other things, one of the requests often made by our customer is to give guidance on suitability
of tool (or set of tools) for a particular task. Even though this knowledge is available within our
organization, it is dispersed as the consultants are working with different customer.
We set out to address the issue of
- timely availability of comparison metrics across tools
- continuous update to the metrics being used to compared
After discussing with our executives we decided to build a web based application internally so
that we can feed in the comparison data on continuous basis without spending too much time
on reconciliation efforts.
There were few challenges to be resolved while addressing the issues given in problem
statement. We conducted a brainstorming session within our organization. The outcome of this
session was a list of important components outline of which is as follows:
- User Interface: The UI should be easy to use and intuitive enough to hide the complexity
underneath. Unless the tool is easy to use people will be reluctant to use it.
- Data Update: The data should be fed in on continuous basis to ensure updates for the
tools to be compared are captured on regular basis. If the data is stale it will raise the
credibility issue of the presented comparison. We cannot compare data of outdated
version of the tools.
- Contextual Text Mapping: The biggest issue is contextual mapping of text which
describes a particular feature of tool, product or application.
Of course this list is not comprehensive, but we need to address these points to ensure viability
of the entire efforts.
I think using “Fast Prototyping” to validate the feasibility of the components is best course of
action before attempting to build this product.
Leap of Faith
Can we build & expand? As the data volume increase the methods employed, especially the
algorithm employed will perform satisfactorily? We decided to find this out.
Can we win? We did not spend great amount of time with user experience. We took a leap of
faith by assuming that the team who participated in building UX is representative of future
users. I think we should be able to tweak UI based on usage analytics and.
UNCOVERING FAKE NEWS BY MEANS OF SOCIAL NETWORK ANALYSISpijans
The short access to facts on social media networks in addition to its exponential upward push also made it tough to distinguish among faux information or actual facts. The quick dissemination thru manner of sharing has more high quality its falsification exponentially. It is also essential for the credibility of social media networks to avoid the spread of fake facts. So its miles rising research task to robotically check for misstatement of information thru its source, content material, or author and save you the unauthenticated assets from spreading rumours. This paper demonstrates an synthetic intelligence primarily based completely approach for the identification of the fake statements made by way of the use of social network entities. Versions of Deep neural networks are being applied to evalues datasets and have a look at for fake information presence. The implementation setup produced most volume 99% category accuracy, even as dataset is tested for binary (real or fake) labelling with multiple epochs.
UNCOVERING FAKE NEWS BY MEANS OF SOCIAL NETWORK ANALYSISpijans
The short access to facts on social media networks in addition to its exponential upward push also made it
tough to distinguish among faux information or actual facts. The quick dissemination thru manner of sharing has more high quality its falsification exponentially. It is also essential for the credibility of social media networks to avoid the spread of fake facts. So its miles rising research task to robotically check for
misstatement of information thru its source, content material, or author and save you the unauthenticated
assets from spreading rumours. This paper demonstrates an synthetic intelligence primarily based completely approach for the identification of the fake statements made by way of the use of social network
entities. Versions of Deep neural networks are being applied to evalues datasets and have a look at for
fake information presence. The implementation setup produced most volume 99% category accuracy, even
as dataset is tested for binary (real or fake) labelling with multiple epochs.
Modular web design is a system of reusable design components and patterns. These components can be combined in various ways to create websites fast, with a small effort, and for a smaller budget. But having ready patterns doesn’t mean that modular websites cannot be adjusted to needs or content. Find out more details about modular website design and its benefits in our short overview.
Data Migration Testing Purpose, Test Strategy And Scenarios.pdfElinext
Data migration testing plays a crucial role in a successful move to the cloud environment. During migration resting migrated data is compared with original data. It allows experts to identify any possible discrepancies and fix errors. Learn about the main data migration testing types, strategies, and scenarios in our paper.
Building a social network website from scratchElinext
In 2020, there were 3.6 billion social media users worldwide. Half of the world's population was active on social media before the pandemic. In the last two years, our online presence has only strengthened. Social websites are an essential part of our daily life. TikTok, Facebook, Instagram, and YouTube crashes frighten people more than ever. So, creating a new social site could be a profitable project. But where to start? Learn in our new guide.
Software Testing QA: Automated Testing vs. Manual Testing. Which to Use, and ...Elinext
The average hourly rate of software testers is between $25 to $35. Could testing automation speed up the process and lower the price? Some analysts say that software testing costs make up between 15 to 25% of the total project cost. So why not automate this expensive process? We compared manual and automated testing in our new study.
Development Standards and Regulations for HealthTechElinext
Wearables, surgery robots, wellness platforms, and digital doctors. The new healthcare landscape is bright, full of novelties and breaking ideas. But before entering this market, you should learn the basic regulations and standards for HealthTech products. We gathered all the information for you in our new infographic.
Virtual medicine is a controversial topic. It unburdens the staff, makes the healthcare services more accessible, but at the same time, it’s often perceived as the “medicine for the poor”. Learn how telemedicine is doing in the US in our new white paper.
App notifications. This word evokes stress, doesn’t it? We are overloaded with messages of all kinds, and when you add another source of information flow when installing a new app, it can become too much. But some apps, like health apps, do not have any choice. They have to function like Neville Longbottom’s Rememberball. So, we devoted this infographic to an actual issue - how to build a non-annoying notification system.
Сomparison table of culture parameters for major outsourcing countriesElinext
Despite the processes of globalization in business, cultural characteristics still play a huge role in communication. And communication plays a huge role in the success of your project.
History and Trends of FinTech in Germany, Austria and SwitzerlandElinext
The German-speaking region is traditionally perceived as strong and financially successful . Germany is believed to be a financial talent foundry, while Austrian Raiffeisen Bank is known in the whole world, and Switzerland is generally associated with money. But what’s behind these successes? What were the barriers the region had to overcome to be where they are now? And what are the possibilities and peculiarities of Fintech development in Germany, Austria, and Switzerland? Can the DACH region compete for the FinTech champion crown?
We talked about this and all else in our newest white paper. Read, enjoy and share!
Since1997, Elinext has been accumulating knowledge and experience to build secure healthcare solutions for hospitals, pharmacies, clinics, and more.
In our services, we focus on:
•Custom healthcare software development from scratch
•Healthcare solution enhancement
•Enterprise-grade system integrations
•Dedicated quality assurance
Source: https://www.elinext.com/presentations/
The document covers the role of SMEs in Europe, and assesses the current digitalization level in this region. We researched on the benefits for the enterprises if these turn to the digital completely.
Source: https://www.elinext.com/researches/
CHAPTER 1 SEMESTER V - ROLE OF PEADIATRIC NURSE.pdfSachin Sharma
Pediatric nurses play a vital role in the health and well-being of children. Their responsibilities are wide-ranging, and their objectives can be categorized into several key areas:
1. Direct Patient Care:
Objective: Provide comprehensive and compassionate care to infants, children, and adolescents in various healthcare settings (hospitals, clinics, etc.).
This includes tasks like:
Monitoring vital signs and physical condition.
Administering medications and treatments.
Performing procedures as directed by doctors.
Assisting with daily living activities (bathing, feeding).
Providing emotional support and pain management.
2. Health Promotion and Education:
Objective: Promote healthy behaviors and educate children, families, and communities about preventive healthcare.
This includes tasks like:
Administering vaccinations.
Providing education on nutrition, hygiene, and development.
Offering breastfeeding and childbirth support.
Counseling families on safety and injury prevention.
3. Collaboration and Advocacy:
Objective: Collaborate effectively with doctors, social workers, therapists, and other healthcare professionals to ensure coordinated care for children.
Objective: Advocate for the rights and best interests of their patients, especially when children cannot speak for themselves.
This includes tasks like:
Communicating effectively with healthcare teams.
Identifying and addressing potential risks to child welfare.
Educating families about their child's condition and treatment options.
4. Professional Development and Research:
Objective: Stay up-to-date on the latest advancements in pediatric healthcare through continuing education and research.
Objective: Contribute to improving the quality of care for children by participating in research initiatives.
This includes tasks like:
Attending workshops and conferences on pediatric nursing.
Participating in clinical trials related to child health.
Implementing evidence-based practices into their daily routines.
By fulfilling these objectives, pediatric nurses play a crucial role in ensuring the optimal health and well-being of children throughout all stages of their development.
The dimensions of healthcare quality refer to various attributes or aspects that define the standard of healthcare services. These dimensions are used to evaluate, measure, and improve the quality of care provided to patients. A comprehensive understanding of these dimensions ensures that healthcare systems can address various aspects of patient care effectively and holistically. Dimensions of Healthcare Quality and Performance of care include the following; Appropriateness, Availability, Competence, Continuity, Effectiveness, Efficiency, Efficacy, Prevention, Respect and Care, Safety as well as Timeliness.
Defecation
Normal defecation begins with movement in the left colon, moving stool toward the anus. When stool reaches the rectum, the distention causes relaxation of the internal sphincter and an awareness of the need to defecate. At the time of defecation, the external sphincter relaxes, and abdominal muscles contract, increasing intrarectal pressure and forcing the stool out
The Valsalva maneuver exerts pressure to expel faeces through a voluntary contraction of the abdominal muscles while maintaining forced expiration against a closed airway. Patients with cardiovascular disease, glaucoma, increased intracranial pressure, or a new surgical wound are at greater risk for cardiac dysrhythmias and elevated blood pressure with the Valsalva maneuver and need to avoid straining to pass the stool.
Normal defecation is painless, resulting in passage of soft, formed stool
CONSTIPATION
Constipation is a symptom, not a disease. Improper diet, reduced fluid intake, lack of exercise, and certain medications can cause constipation. For example, patients receiving opiates for pain after surgery often require a stool softener or laxative to prevent constipation. The signs of constipation include infrequent bowel movements (less than every 3 days), difficulty passing stools, excessive straining, inability to defecate at will, and hard feaces
IMPACTION
Fecal impaction results from unrelieved constipation. It is a collection of hardened feces wedged in the rectum that a person cannot expel. In cases of severe impaction the mass extends up into the sigmoid colon.
DIARRHEA
Diarrhea is an increase in the number of stools and the passage of liquid, unformed feces. It is associated with disorders affecting digestion, absorption, and secretion in the GI tract. Intestinal contents pass through the small and large intestine too quickly to allow for the usual absorption of fluid and nutrients. Irritation within the colon results in increased mucus secretion. As a result, feces become watery, and the patient is unable to control the urge to defecate. Normally an anal bag is safe and effective in long-term treatment of patients with fecal incontinence at home, in hospice, or in the hospital. Fecal incontinence is expensive and a potentially dangerous condition in terms of contamination and risk of skin ulceration
HEMORRHOIDS
Hemorrhoids are dilated, engorged veins in the lining of the rectum. They are either external or internal.
FLATULENCE
As gas accumulates in the lumen of the intestines, the bowel wall stretches and distends (flatulence). It is a common cause of abdominal fullness, pain, and cramping. Normally intestinal gas escapes through the mouth (belching) or the anus (passing of flatus)
FECAL INCONTINENCE
Fecal incontinence is the inability to control passage of feces and gas from the anus. Incontinence harms a patient’s body image
PREPARATION AND GIVING OF LAXATIVESACCORDING TO POTTER AND PERRY,
An enema is the instillation of a solution into the rectum and sig
QA Paediatric dentistry department, Hospital Melaka 2020Azreen Aj
QA study - To improve the 6th monthly recall rate post-comprehensive dental treatment under general anaesthesia in paediatric dentistry department, Hospital Melaka
CRISPR-Cas9, a revolutionary gene-editing tool, holds immense potential to reshape medicine, agriculture, and our understanding of life. But like any powerful tool, it comes with ethical considerations.
Unveiling CRISPR: This naturally occurring bacterial defense system (crRNA & Cas9 protein) fights viruses. Scientists repurposed it for precise gene editing (correction, deletion, insertion) by targeting specific DNA sequences.
The Promise: CRISPR offers exciting possibilities:
Gene Therapy: Correcting genetic diseases like cystic fibrosis.
Agriculture: Engineering crops resistant to pests and harsh environments.
Research: Studying gene function to unlock new knowledge.
The Peril: Ethical concerns demand attention:
Off-target Effects: Unintended DNA edits can have unforeseen consequences.
Eugenics: Misusing CRISPR for designer babies raises social and ethical questions.
Equity: High costs could limit access to this potentially life-saving technology.
The Path Forward: Responsible development is crucial:
International Collaboration: Clear guidelines are needed for research and human trials.
Public Education: Open discussions ensure informed decisions about CRISPR.
Prioritize Safety and Ethics: Safety and ethical principles must be paramount.
CRISPR offers a powerful tool for a better future, but responsible development and addressing ethical concerns are essential. By prioritizing safety, fostering open dialogue, and ensuring equitable access, we can harness CRISPR's power for the benefit of all. (2998 characters)
India Clinical Trials Market: Industry Size and Growth Trends [2030] Analyzed...Kumar Satyam
According to TechSci Research report, "India Clinical Trials Market- By Region, Competition, Forecast & Opportunities, 2030F," the India Clinical Trials Market was valued at USD 2.05 billion in 2024 and is projected to grow at a compound annual growth rate (CAGR) of 8.64% through 2030. The market is driven by a variety of factors, making India an attractive destination for pharmaceutical companies and researchers. India's vast and diverse patient population, cost-effective operational environment, and a large pool of skilled medical professionals contribute significantly to the market's growth. Additionally, increasing government support in streamlining regulations and the growing prevalence of lifestyle diseases further propel the clinical trials market.
Growing Prevalence of Lifestyle Diseases
The rising incidence of lifestyle diseases such as diabetes, cardiovascular diseases, and cancer is a major trend driving the clinical trials market in India. These conditions necessitate the development and testing of new treatment methods, creating a robust demand for clinical trials. The increasing burden of these diseases highlights the need for innovative therapies and underscores the importance of India as a key player in global clinical research.
Navigating Challenges: Mental Health, Legislation, and the Prison System in B...Guillermo Rivera
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VERIFICATION AND VALIDATION TOOLKIT Determining Performance Characteristics o...
Pneumonia diagnosis tool Case Study
1. Client
A company developing a healthcare platform hired Elinext to help it build a pneumonia
diagnosis tool.
Challenge
The company has been developing a comprehensive healthcare platform. Treating pneumonia
has been one of its focus areas due to COVID, and it wanted to build a pneumonia diagnosis
tool for the platform.
The tool was destined to analyze lung X-ray images and identify signs of pneumonia using
machine learning (ML), an artificial intelligence (AI) technique. The company didn’t have
relevant in-house experts, so they reached out for help and found it with Elinext.
Solution
We began by looking for a neural network that would best analyze lung images and found four
candidates: ResNet (50, 101, 152), VGG (16, 19), MobileNet and Inception (V2, V3). After
digging deeper into each of them, we chose InceptionV3 developed by Google Research Lab.
Once we chose our neural network, we moved on to designing the software architecture and
training the algorithm.
2. Architecture
The software is based on web technology and can be integrated into other systems like desktop
applications and mobile apps.
We used publicly available frameworks, libraries and technologies to develop the software. To
create a static HTML5 web page, we deployed a web server in a Docker container. On that
page, a user can upload a lung image and get feedback. The image is sent for processing
through the HTTP protocol.
Training
Training is the most challenging part in building ML algorithms. Your ability to source enough
data, avoid errors and be consistent throughout the process can make or break the algorithm.
Manual training is often inconsistent. You may forget which steps you have taken and in which
order, or occasionally delete logs. As a result, you won’t be able to accurately repeat a training
session. Therefore, we automated the process from A to Z.
We needed to train complex models with huge datasets fast. To do that, we rented an Amazon
Web Services (AWS) g3s.xlarge instance and used Deep Learning Base AMI (Ubuntu 18.10). The
latter is a powerful machine boasting 16GB of RAM, a 4-core CPU and an Nvidia Tesla M60 GPU.
It was a perfect fit for the task. Once we have chosen the technology, the training could begin.
We built a clean Docker container to isolate the model from outer influences and downloaded a
ton of lung images from Kaggle. To be able to work with the images, we subsampled them,
narrowing them down to a relevant and consistent selection. The dataset and training
environment were ready.
The training began. We faced a challenge in overtraining, whereby the model could memorize
training images and as a result fail to accurately analyze new images in the future. Our solution
was to slightly modify the images’ width, height, graininess and some other parameters. We
also launched Tensorboard to monitor training metrics.
At the final stages, we exported the model to an H5 file, a format commonly used across
industries from healthcare to aerospace, for testing. We tested it manually and automatically,
using preset scripts.
Accuracy
The model we’ve developed has a margin of confidence and uses binary identification. What
does this mean? It means if the algorithm identifies 80% of lungs as unaffected, it will say the
lungs are healthy. If the figure is below 80%, it will assume the lungs might be affected and
require medical attention.
How It Works
The user opens the web application in their browser, uploads a lung image, sends it to the
service and receives feedback. The feedback will show whether the lungs are healthy or if a
doctor should take a look at the image.
Result
The tool we’ve built can help reduce human error in identifying pneumonia. This is particularly
useful during the pandemic when doctors are overloaded and might overlook some signs of
illness. We can also scale the model up to identify some other diseases. Scaling the model down
will help integrate it into other systems, speed things up and allow for the analysis of multiple
images simultaneously.