Biostatistics is the application of statistics to biological and health data. It involves collecting, organizing, summarizing, analyzing, interpreting and drawing valid conclusions from data to make reasonable decisions. Some key areas where biostatistics is applied include medicine, epidemiology, public health, genetics, pharmacology, and environmental science. It helps define normal ranges, identify disease signs and symptoms, evaluate health programs, and conduct genetic and epidemiological studies.
This powerpoint presentation gives a brief explanation about the biostatic data .this is quite helpful to individuals to understand the basic research methodology terminologys
General statistics, emphasis of statistics with regards to healthcare, types of stats, methods of sampling, errors in sampling, different types of tests, measures of dispersion, correlation, types of correlation
This slide explains term biostatistics, important terms used in the field of bio statistics and important applications of biostatistics in the field of agriculture, physiology, ecology, genetics, molecular biology, taxonomy, etc.
Cross over design, Placebo and blinding techniques Dinesh Gangoda
A crossover design is a modified randomized block design in which each block receives more than one treatment at different dosing periods.
A block can be a patient or a group of patients.
Patients in each block receive different sequences of treatments.
A crossover design is called a complete crossover design if each sequence contains all treatments under investigation.
A placebo is a dummy medicine containing no active substance.
This substance has no therapeutic effect, used as a control in testing new drugs.
Latin- ‘ I shall please’
DESIGN OF EXPERIMENTS (DOE)
DOE is invented by Sir Ronald Fisher in 1920’s and 1930’s.
The following designs of experiments will be usually followed:
Completely randomised design(CRD)
Randomised complete block design(RCBD)
Latin square design(LSD)
Factorial design or experiment
Confounding
Split and strip plot design
FACTORIAL DESIGN
When a several factors are investigated simultaneously in a single experiment such experiments are known as factorial experiments. Though it is not an experimental design, indeed any of the designs may be used for factorial experiments.
For example, the yield of a product depends on the particular type of synthetic substance used and also on the type of chemical used.
ADVANTAGES OF FACTORIAL DESIGN.
Factorial experiments are advantageous to study the combined effect of two or more factors simultaneously and analyze their interrelationships. Such factorial experiments are economic in nature and provide a lot of relevant information about the phenomenon under study. It also increases the efficiency of the experiment.
It is an advantageous because a wide range of factor combination are used. This will give us an idea to predict about what will happen when two or more factors are used in combination.
DISADVANTAGES
It is disadvantageous because the execution of the experiment and the statistical analysis becomes more complex when several treatments combinations or factors are involved simultaneously.
It is also disadvantageous in cases where may not be interested in certain treatment combinations but we are forced to include them in the experiment. This will lead to wastage of time and also the experimental material.
2(square) FACTORIAL EXPERIMENT
A special set of factorial experiment consist of experiments in which all factors have 2 levels such experiments are referred to generally as 2n factorials.
If there are four factors each at two levels the experiment is known as 2x2x2x2 or 24 factorial experiment. On the other hand if there are 2 factors each with 3 levels the experiment is known as 3x3 or 32 factorial experiment. In general if there are n factors each with p levels then it is known as pn factorial experiment.
The calculation of the sum of squares is as follows:
Correction factor (CF) = (𝐺𝑇)2/𝑛
GT = grand total
n = total no of observations
Total sum of squares = ∑▒〖𝑥2−𝐶𝐹〗
Replication sum of squares (RSS) = ((𝑅1)2+(𝑅2)2+…+(𝑅𝑛)2)/𝑛 - CF
Or
1/𝑛 ∑▒𝑅2−𝐶𝐹
2(Cube) FACTORIAL DESIGN
In this type of design, one independent variable has 2 levels, and the other independent variable has 3 levels.
Estimating the effect:
In a factorial design the main effect of an independent variable is its overall effect averaged across all other independent variable.
Effect of a factor A is the average of the runs where A is at the high level minus the average of the runs
Role of Biostatistician and Biostatistical Programming in Epidemiological Stu...PEPGRA Healthcare
Pepgra experts provide regulatory biostatistics and epidemiology statistical programming support to all phases of clinical trial process development and commercialization. Our Epidemiological statistical services is are located globally & trained in current methods and standards to support the successful execution of your projects.
Continue Reading: http://bit.ly/2OBq9EZ
Youtube: https://youtu.be/2NORssElgFg
Contact Us:
Website : https://bit.ly/33Fwsye
Email us: sales.cro@pepgra.com
India: +91 9884350006
United Kingdom: +44- 74248 10299
Clinical data science is a rapidly evolving field that utilizes advanced analytics and machine learning techniques to extract meaningful insights from large scale healthcare data. In recent years, there has been a significant increase in the availability of electronic health records, genomic data, wearable devices, and other digital health technologies, generating vast amounts of data. This article presents a comprehensive review of the current state of clinical data science and its future prospects. The review begins by providing an overview of the foundational concepts and methodologies employed in clinical data science. It explores various data sources, including structured and unstructured data, and highlights the challenges associated with data quality, privacy, and interoperability. The role of artificial intelligence and machine learning algorithms in data analysis and prediction is examined, along with the importance of data preprocessing and feature selection techniques. G. Dileepkumar | Nimisha Prajapati | Simhavalli Godavarthi "Clinical Data Science and its Future" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-3 , June 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd58588.pdf Paper URL: https://www.ijtsrd.com.com/pharmacy/pharmacy-practice/58588/clinical-data-science-and-its-future/g-dileepkumar
This powerpoint presentation gives a brief explanation about the biostatic data .this is quite helpful to individuals to understand the basic research methodology terminologys
General statistics, emphasis of statistics with regards to healthcare, types of stats, methods of sampling, errors in sampling, different types of tests, measures of dispersion, correlation, types of correlation
This slide explains term biostatistics, important terms used in the field of bio statistics and important applications of biostatistics in the field of agriculture, physiology, ecology, genetics, molecular biology, taxonomy, etc.
Cross over design, Placebo and blinding techniques Dinesh Gangoda
A crossover design is a modified randomized block design in which each block receives more than one treatment at different dosing periods.
A block can be a patient or a group of patients.
Patients in each block receive different sequences of treatments.
A crossover design is called a complete crossover design if each sequence contains all treatments under investigation.
A placebo is a dummy medicine containing no active substance.
This substance has no therapeutic effect, used as a control in testing new drugs.
Latin- ‘ I shall please’
DESIGN OF EXPERIMENTS (DOE)
DOE is invented by Sir Ronald Fisher in 1920’s and 1930’s.
The following designs of experiments will be usually followed:
Completely randomised design(CRD)
Randomised complete block design(RCBD)
Latin square design(LSD)
Factorial design or experiment
Confounding
Split and strip plot design
FACTORIAL DESIGN
When a several factors are investigated simultaneously in a single experiment such experiments are known as factorial experiments. Though it is not an experimental design, indeed any of the designs may be used for factorial experiments.
For example, the yield of a product depends on the particular type of synthetic substance used and also on the type of chemical used.
ADVANTAGES OF FACTORIAL DESIGN.
Factorial experiments are advantageous to study the combined effect of two or more factors simultaneously and analyze their interrelationships. Such factorial experiments are economic in nature and provide a lot of relevant information about the phenomenon under study. It also increases the efficiency of the experiment.
It is an advantageous because a wide range of factor combination are used. This will give us an idea to predict about what will happen when two or more factors are used in combination.
DISADVANTAGES
It is disadvantageous because the execution of the experiment and the statistical analysis becomes more complex when several treatments combinations or factors are involved simultaneously.
It is also disadvantageous in cases where may not be interested in certain treatment combinations but we are forced to include them in the experiment. This will lead to wastage of time and also the experimental material.
2(square) FACTORIAL EXPERIMENT
A special set of factorial experiment consist of experiments in which all factors have 2 levels such experiments are referred to generally as 2n factorials.
If there are four factors each at two levels the experiment is known as 2x2x2x2 or 24 factorial experiment. On the other hand if there are 2 factors each with 3 levels the experiment is known as 3x3 or 32 factorial experiment. In general if there are n factors each with p levels then it is known as pn factorial experiment.
The calculation of the sum of squares is as follows:
Correction factor (CF) = (𝐺𝑇)2/𝑛
GT = grand total
n = total no of observations
Total sum of squares = ∑▒〖𝑥2−𝐶𝐹〗
Replication sum of squares (RSS) = ((𝑅1)2+(𝑅2)2+…+(𝑅𝑛)2)/𝑛 - CF
Or
1/𝑛 ∑▒𝑅2−𝐶𝐹
2(Cube) FACTORIAL DESIGN
In this type of design, one independent variable has 2 levels, and the other independent variable has 3 levels.
Estimating the effect:
In a factorial design the main effect of an independent variable is its overall effect averaged across all other independent variable.
Effect of a factor A is the average of the runs where A is at the high level minus the average of the runs
Role of Biostatistician and Biostatistical Programming in Epidemiological Stu...PEPGRA Healthcare
Pepgra experts provide regulatory biostatistics and epidemiology statistical programming support to all phases of clinical trial process development and commercialization. Our Epidemiological statistical services is are located globally & trained in current methods and standards to support the successful execution of your projects.
Continue Reading: http://bit.ly/2OBq9EZ
Youtube: https://youtu.be/2NORssElgFg
Contact Us:
Website : https://bit.ly/33Fwsye
Email us: sales.cro@pepgra.com
India: +91 9884350006
United Kingdom: +44- 74248 10299
Clinical data science is a rapidly evolving field that utilizes advanced analytics and machine learning techniques to extract meaningful insights from large scale healthcare data. In recent years, there has been a significant increase in the availability of electronic health records, genomic data, wearable devices, and other digital health technologies, generating vast amounts of data. This article presents a comprehensive review of the current state of clinical data science and its future prospects. The review begins by providing an overview of the foundational concepts and methodologies employed in clinical data science. It explores various data sources, including structured and unstructured data, and highlights the challenges associated with data quality, privacy, and interoperability. The role of artificial intelligence and machine learning algorithms in data analysis and prediction is examined, along with the importance of data preprocessing and feature selection techniques. G. Dileepkumar | Nimisha Prajapati | Simhavalli Godavarthi "Clinical Data Science and its Future" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-3 , June 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd58588.pdf Paper URL: https://www.ijtsrd.com.com/pharmacy/pharmacy-practice/58588/clinical-data-science-and-its-future/g-dileepkumar
Most people have heard the statistic that heart disease is a leading cause of death in America today source: Centers for Disease Control. But how do we know this fact to be a true where did that information come from
Back in 1948, when a lot wasn't known about the factors leading to the heart disease and stroke, a health research study -- known as the Framingham Heart Study -- was done the on 5,209 people living in the town of Framingham, Mass. These are participants hadn't developed any known symptoms of cardiovascular disease and hadn't had a stroke or heart attack.
Bioinformatics in the Clinical Pipeline: Contribution in Genomic Medicineiosrjce
In this review report we like to focus on the new challenges in methodology of modern biology be
used in medical science. Today human health is a primary issue to cure disease, undoubtedly the answer to this
is bioinformatics or (In-silco) tools has change the concept of treating patients to understand the need of
genomic medicine in use. Those with new modes of action in clinical treatment, is a major health concern in
medical science. On global prospective scientific role in constructing new ideas to remediate health care to
treat disease exciting in nature is challenging task. So awareness needs to accelerate store clinical datasets for
scientific represents to design genomic drugs. This new outline will drive the medical to discover public data
and create a cognitive approach to use technology cheaper at cost effective mode.
Leveraging Publicly Accessible Clinical Trails Data Sharing, Dissemination an...Vaticle
In the broader realm of the advancement of science and the betterment of the human condition, there are several purported benefits for sharing clinical trials and research data. The scientific community has just begun to embrace open-access datasets to build their knowledge base, gain insight into new discoveries, and generate novel data-driven hypotheses that were not initially formulated in the studies. With the increasing amount of clinical trial data available, comes the need to leverage a multitude of shared datasets. Your knowledge base needs to facilitate discovery across research domains.
This talk highlights the data sharing, dissemination, and repurposing of clinical and molecular studies generated by government-funded research consortia. Further, we are building a new knowledge base resource, IMMGRAKN to facilitate translational discovery from crowd-sourced clinical trials data in ImmPort (www.immport.org), an NIH-NIAID funded open-access immunology database and analysis portal. The case studies demonstrating the use of IMMGRAKN will be discussed
Bioinformatics: Bioinformatics, Healthcare Informatics and Analytics for Improved Healthcare System, Intelligent Monitoring and Control for Improved Healthcare System.
An AI-based Decision Platform built using unified data model, incorporating systems biology topics for unit analysis using semi-supervised learning models
This presentation contains
Biological oxidation
Electron transport chain (ETC) and its mechanism.
Oxidative phosphorylation & its mechanism and substrate
phosphorylation level Inhibitors ETC and oxidative phosphorylation/Uncouplers
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
The Indian economy is classified into different sectors to simplify the analysis and understanding of economic activities. For Class 10, it's essential to grasp the sectors of the Indian economy, understand their characteristics, and recognize their importance. This guide will provide detailed notes on the Sectors of the Indian Economy Class 10, using specific long-tail keywords to enhance comprehension.
For more information, visit-www.vavaclasses.com
How to Create Map Views in the Odoo 17 ERPCeline George
The map views are useful for providing a geographical representation of data. They allow users to visualize and analyze the data in a more intuitive manner.
This is a presentation by Dada Robert in a Your Skill Boost masterclass organised by the Excellence Foundation for South Sudan (EFSS) on Saturday, the 25th and Sunday, the 26th of May 2024.
He discussed the concept of quality improvement, emphasizing its applicability to various aspects of life, including personal, project, and program improvements. He defined quality as doing the right thing at the right time in the right way to achieve the best possible results and discussed the concept of the "gap" between what we know and what we do, and how this gap represents the areas we need to improve. He explained the scientific approach to quality improvement, which involves systematic performance analysis, testing and learning, and implementing change ideas. He also highlighted the importance of client focus and a team approach to quality improvement.
The Art Pastor's Guide to Sabbath | Steve ThomasonSteve Thomason
What is the purpose of the Sabbath Law in the Torah. It is interesting to compare how the context of the law shifts from Exodus to Deuteronomy. Who gets to rest, and why?
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Introduction and Applications of Biostatistics.pdf
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assess State of 0Tal health in community
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