AI in Healthcare Training in Astana, Kazakhstan

This course introduces healthcare professionals, data scientists, and technologists to the transformative role of Artificial Intelligence (AI) in the healthcare sector. Covering clinical applications, medical imaging, predictive analytics, and ethical implications, this course empowers participants to leverage AI tools and frameworks to enhance diagnostics, optimize patient care, and streamline healthcare operations.

Introduction to AI in Healthcare

• Overview of AI and ML concepts

• History and evolution of AI in medicine

• Types of AI: ML, DL, NLP, and their relevance in healthcare

Healthcare Data and Preprocessing

• Types of healthcare data: EHRs, imaging, genomics, wearables

• Data privacy regulations (HIPAA, GDPR, etc.)

• Data cleaning, anonymization, and structuring

• Introduction to tools: Python, pandas, Jupyter, scikit-learn

Medical Imaging and Predictive Analytics

• Deep learning in medical image analysis (e.g., X-rays, MRI)

• Convolutional Neural Networks (CNNs) basics

• Predictive modeling: disease progression, readmission, diagnosis

Natural Language Processing in Healthcare

• Introduction to NLP and its healthcare relevance

• Applications: Clinical notes, chatbots, symptom analysis

• Named Entity Recognition (NER), text classification

Ethics, Deployment & Future of AI in Healthcare

• Ethical considerations: Bias, fairness, explainability

• Deployment challenges: Integration with EMRs, patient safety

• Future trends: Personalized medicine, robotics, AI assistants

Case Studies

Group Discussions