Artificial Intelligence, Machine Learning in Health Care and Clinical Use

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.

The aim is to impact the decision-making process in the clinical context using AI/ML

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