AI for Healthcare Professionals

This initiative helps researchers commercialize ideas by assessing institutional readiness and mapping Bangladesh’s innovation landscape to drive growth.

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Course Outline

Module 1 Introduction to AI in Healthcare

What is AI? Key concepts (ML, NLP, Deep Learning)
Overview of AI applications in healthcare
Benefits and risks of AI in clinical practice

Module 2 Data in Healthcare AI

Types and sources of healthcare data
Data quality and preprocessing
Ethical issues around health data usage

Module 3 Clinical Applications of AI

Diagnostic tools (e.g., radiology, pathology)
Predictive analytics in patient care
AI in treatment personalization

Module 4 AI Tools & Techniques

Overview of popular AI frameworks and libraries
Introduction to building simple models
Understanding model evaluation and metrics

Module 5 Hands-On Practice

Guided project using real-world datasets
Model training and evaluation
Interpreting AI outputs in healthcare context

Module 6 Future of AI in Healthcare

Emerging trends and research areas
Regulatory challenges and policies
The evolving role of healthcare professionals with AI

Course Mentor

Dr. Mahmudul Haque

MBBS, MPH, PhD (Health Informatics)

Current Role

Director, Center for Health Innovation & AI Associate Professor, Department of Public Health Informatics, Bangabandhu Sheikh Mujib Medical University (BSMMU)

Expertise

AI in epidemiology and public health
Clinical decision support systems (CDSS)
EHR and health data infrastructure in LMICs
Health data ethics and governance

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