
Artificial Intelligence, Machine Learning in Health Care and Clinical Use
Transforming Healthcare with the Power of AI and Machine Learning
Skills you will gain:
About Program:
This 3-day workshop focuses on leveraging AI and Machine Learning techniques in healthcare and clinical sciences. Machine learning has revolutionized multiple domains, and its application in healthcare can significantly enhance clinical decision-making processes. Participants will explore foundational concepts, algorithms, and tools for building AI/ML models, focusing on supervised and unsupervised learning techniques. Real-world applications like predictive models for diabetes will be a key highlight.
Participants will gain hands-on experience with R programming and Bioconductor packages, which are essential tools for computational statistics and bioinformatics. By the end of the workshop, attendees will be equipped to apply AI/ML algorithms in healthcare scenarios, critically evaluate model performance, and understand the ethical implications of AI in clinical use.
Aim: The aim is to impact the decision-making process in the clinical context using AI/ML
Program Objectives:
- To find the algorithm that best classifies to predict the diabetes and evaluate the best algorithm.
- To help clinicians make better decisions by providing them with insights derived from vast datasets.
What you will learn?
Day 1: Introduction to AI/ML and Its Foundational Principles
- Basics of Artificial Intelligence, Machine Learning, Deep Learning.
- Supervised Leaning, Unsupervised Learning Naive Bayes, Decision Tree, and Random Forest
Day 2: R Studio and Bioconductor Packages
- R and Bioconductor packages installation
- Examples of AI/ML for Health Care and Clinical Use
Day 3: Application of AI/ML in Healthcare and Clinical Use
- Diabetes Prediction model based on AI/ML Algorithm
- Model evaluation and validation
Mentor Profile
Fee Plan
Get an e-Certificate of Participation!

Intended For :
- Undergraduate or postgraduate degree in Computer Science, Data Science, Life Sciences, Bioinformatics, or related fields.
- Clinicians, Data Scientists, Healthcare Analysts, or IT professionals working in the healthcare domain.
- Individuals with a keen interest in AI/ML and healthcare innovation.
Career Supporting Skills
Program Outcomes
- Understand foundational concepts of AI/ML in healthcare.
- Gain hands-on experience with R and Bioconductor packages.
- Build and validate a diabetes prediction model.
- Learn to evaluate the effectiveness of AI/ML models.
- Discuss ethical considerations in deploying AI/ML in healthcare.
