This course aims to teach learners about practical AI solutions within healthcare and biotechnology. The learning outcomes include understanding data strategy and technical use cases involving time-series, text, and image data in healthcare. The course covers skills such as analyzing medical images, electronic health records, and operational data, as well as developing and deploying AI solutions within Fortune 500 companies. The teaching method involves examining real-world problems, discussing challenges, and presenting use cases. The intended audience for this course includes healthcare professionals, data scientists, AI enthusiasts, and individuals interested in the intersection of AI and healthcare.
Practical AI Solutions Within Healthcare and Biotechnology - Michael Segala
Overview
Syllabus
Introduction
Company Overview
Problems
Healthcare
AI in Healthcare
The Problem
Lack of Data Scientists
Huge Opportunity
Image Analysis
Why is it hard
Why is it important
Use case
Challenges
Typical workflow
Histopathology
NLP
The Challenge
Example
Safety
OCR
Sleep Apnea
Heart Failure
Summary
Taught by
Open Data Science
