Workshop on Revolutionizing Healthcare with AI
Fee: PKR 60,000
- 2 Day (In-person)
- PDC building, NUST H-12 Campus, Islamabad.
- 29th & 30th October
- Tuesday & Wednesday 10:00 AM to 4:00 PM
In today’s data-driven world, the ability to interpret data effectively is crucial for making informed business decisions.
Our workshop “Revolutionizing Healthcare With AI” is designed to empower health professionals with the skills needed to equip the power of data.
With future prediction being one of the most valuable skills, this workshop will equip you with the tools to turn data into actionable insights.
Fee
PKR
60,000
-
LUMPSUM
Day 1: Introduction to AI in Healthcare and Global Use Cases
What is AI and How It Works
- AI, Machine Learning (ML), and Deep Learning overview
- The process: how AI learns from data (data + algorithms = insights)
- Examples of AI applications outside of healthcare to relate it to everyday life.
Global Use Cases of AI in Healthcare
- AI in Medical Diagnostics and Imaging
- Case Study: Google’s DeepMind and AI for Eye Disease Diagnosis
- Case Study: Zebra Medical Vision – AI for Radiology
- AI-Powered Patient Care and Personalized Medicine
- Case Study: IBM Watson for Oncology – AI-Assisted Cancer Treatment
- Case Study: Tempus – AI for Personalized Cancer Care
- AI in Healthcare Operations and Efficiency
- Case Study: Qventus – AI for Hospital Efficiency and Workflow Management
- Case Study: AI-Powered Chatbots for Patient Triage (Babylon Health)
- AI in Drug Discovery and Research Advancements
- Case Study: Insilico Medicine – AI-Driven Drug Discovery
- Case Study: Atomwise – AI for Small Molecule Drug Discovery
Ethics in AI for Healthcare
- Algorithmic bias (AI may reflect human biases in medical diagnosis)
- Data privacy concerns with patient data
- Job displacement in healthcare due to automation
- Ethical questions around decision-making in life-critical situations
Day 2: Hands-On Exploration of AI and Machine Learning in Healthcare
Intro to Machine Learning
- Machine learning basics: what it is and how it’s different from AI
- Types of ML: Supervised, Unsupervised, Reinforcement Learning
- Real-life healthcare examples: disease prediction, treatment recommendations
Supervised Learning and Classification
- What is classification? (e.g., classifying X-rays as healthy or diseased)
- Overview of supervised learning in healthcare: AI identifying medical conditions from images.
- Common examples of classification models in healthcare.
AI in Image Classification for Medical Applications
- AI’s role in analyzing radiology images (X-rays, MRIs, etc.)
- How image classification helps with early detection of diseases (e.g., detecting tumors, pneumonia, or eye diseases from scans)
Group Activity—Design an AI-Powered Healthcare Solution
Trainers
Mahnoor Salman
