AI for Healthcare Applications
Transforming Healthcare with Advanced AI Applications
Skills you will gain:
About Program:
This three-day workshop covers AI applications in advanced medical diagnosis, predictive analytics for healthcare outcomes, and personalized medicine. Participants will engage in hands-on sessions and case studies to understand practical implementations and future directions in AI-driven healthcare.
Aim: To equip PhD scholars and academicians with advanced skills in leveraging AI for healthcare applications. This course aims to enhance capabilities in medical diagnosis, predictive analytics, and personalized medicine through AI-driven techniques and tools.
Program Objectives:
- Master AI techniques for advanced medical diagnosis.
- Implement predictive analytics models in healthcare.
- Develop AI-driven personalized treatment plans.
- Ensure ethical use of AI in healthcare applications.
- Analyze and apply real-world case studies in healthcare AI.
What you will learn?
Day 1: AI in Advanced Medical Diagnosis
- Lecture Topics:
- AI techniques for disease detection and classification
- Case studies in radiology and pathology
- Discussion & Case Studies:
- Ethical implications and data privacy
- Practical implementation and validation
Day 2: Predictive Analytics in Healthcare
- Lecture Topics:
- Advanced predictive models for patient outcomes
- Applications in hospital management and resource allocation
- Discussion & Case Studies:
- Real-world examples and case studies
- Hands-on session with healthcare datasets
Day 3: Personalized Medicine with AI
- Lecture Topics:
- AI-driven personalized treatment plans and drug discovery
- Integration of genomics and AI
- Discussion & Case Studies:
- Case studies in personalized healthcare
- Practical implementation and future directions
Mentor Profile
Fee Plan
Get an e-Certificate of Participation!
Intended For :
Medical professionals, data scientists, AI researchers, bioinformaticians, and
Career Supporting Skills
Program Outcomes
- Develop and implement AI models for advanced medical diagnosis.
- Utilize predictive analytics for patient outcome forecasting.
- Create personalized treatment plans using AI.
- Address ethical and data privacy issues in AI healthcare applications.
- Apply and analyze real-world case studies in AI-driven healthcare.