Analysis of Biomedical Data and Application of Machine Learning using R
Transforming Biomedical Data into Insights with R and Machine Learning
Virtual (Google Meet)
Mentor Based
Moderate
3 Days (1.5 hours per day)
18 -March -2025
1:00 – 2:30 PM IST
About
Machine learning (ML) is a branch of artificial intelligence (AI) that concentrates on creating algorithms and statistical models that allow computer systems to learn from data and make predictions or decisions. Essentially, it is a discipline where computers are trained to carry out tasks without the need for explicit programming for each individual task. Recent developments in Artificial Intelligence (AI) and Machine Learning (ML) technology have led to significant progress in predicting and identifying health emergencies, disease demographics, and immune responses, among other areas. However, there is still skepticism about the practical use and interpretation of outcomes from ML-based methods in healthcare environments, even as the adoption of these methods rapidly increases.
In this workshop, we present a concise summary of machine learning techniques and algorithms, which encompass supervised, unsupervised, and reinforcement learning, complete with examples. Additionally, we explore the use of machine learning in the biomedical sector to gain insights into disease prevalence and diagnosis.
Aim
The aim is to assist bio-medical scientists and medical professionals by identifying and summarizing meaningful patterns from large datasets.
Workshop Objectives
- To examine extensive datasets of medical information in order to uncover patterns and forecast disease progression, diagnosis, treatment responses, and patient outcomes.
- To expedite medical discoveries and enhance healthcare by delivering greater insights into intricate biological systems and diseases via data analysis.
This workshop intends to provide an arena for students, faculty and researchers in discussing the following topics as well as to provide hands on training.
Workshop Structure
Day 1: Introductionto ML/AI and its Foundational Principles
- Overview of Artificial Intelligence, Machine Learning, and Deep Learning.
- Supervised Leaning, Unsupervised Learning, Reinforcement learning LDA (Linear Discriminant Analysis), KNN (K-Nearest Neighbours), SVM (Support Vector Machine), Random Forest, AdaBoost (Adaptive Boosting)
Day 2: R studio and Bioconductor packages
- R and Bioconductor packages installation
- Application of Machine Learning for Biomedical Research
Day 3: Biomedical Data analysis and Machine Learning
- Machine learning prediction model via data extraction, data analysis, data visualization and data modelling
- Performance testing of the model
Participant’s Eligibility
- Undergraduate degree in Biomedical Sciences, Bioinformatics, Data Science, or related fields.
- Professionals working in healthcare, clinical research, or biotechnology sectors.
- Individuals with a keen interest in biomedical data analysis and machine learning applications.
Important Dates
Registration Ends
2025-03-18
Indian Standard Timing 12:00 PM
Workshop Dates
2025-03-18 to 2025-03-20
Indian Standard Timing 1:00 – 2:30 PM
Workshop Outcomes
- Master R programming for biomedical data analysis.
- Gain expertise in machine learning techniques for healthcare.
- Learn to build predictive models for disease and drug studies.
- Develop insights into real-world applications of bioinformatics.
- Acquire job-ready skills for roles in health tech and research.
Mentor Profile
Designation: Professor and Head
Affiliation: Shalom New Life College, Bengaluru, Karnataka
Dr. Md Afroz Alam is a Professor and Head in the Department of Bioinformatics, at Shalom New Life College, Bengaluru, Karnataka. He received his Ph.D. Degree in Bioinformatics from Jaypee University of Information Technology, Solan, Himachal Pradesh in 2009. Then he has worked as Assistant Professor, Head and Program Coordinator in the Department of Bioinformatics at Karunya Institute of Technology and Sciences (Deemed University) for 11 Years. He is having 14 years of teaching and research experience in the field of Bioinformatics. His area of expertise includes: Computer Aided Drug Design, Molecular Modeling and Simulation, QSAR and Pharmacophore modeling, Biostatistics, R programming, Unix and Linux. He is the author of 24 research articles, 2 Book Chapter, recipient of short-term research grants, workshop grants, and National Youth leader award by Ministry of Youth Affairs and Sports under the National Service Scheme, Government of India.
Fee Structure
Student
INR. 1399
USD. 50
Ph.D. Scholar / Researcher
INR. 1699
USD. 55
Academician / Faculty
INR. 2199
USD. 60
Industry Professional
INR. 2699
USD. 85
List of Currencies
Key Takeaways
- Access to Live Lectures
- Access to Recorded Sessions
- e-Certificate
- Query Solving Post Workshop
Future Career Prospects
- Biomedical Data Analyst in hospitals or research centers.
- Machine Learning Specialist in healthcare-focused AI companies.
- Bioinformatics Scientist for genomic and proteomic studies.
- Healthcare Consultant in predictive modeling and diagnostics.
- Researcher in drug discovery and personalized medicine.
- Data Scientist specializing in biomedical and health data.
Job Opportunities
- Data Analyst in biotech firms and pharmaceutical companies.
- Machine Learning Engineer for health tech startups.
- Bioinformatics Specialist in genomic research labs.
- Clinical Data Manager in hospitals and CROs.
- Research Scientist in academic or government institutions.
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Recent Feedbacks In Other Workshops
Very good
na
Contents were excellent