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Overview

This class starts with a general overview of AI, neural network architecture, and deep learning. Medical image classification and segmentation will be introduced with examples of multi-spectral endoscopic narrowband imaging data classification. The class covers computer vision, image understanding, natural language understanding, such as sentence classification, keyword extraction, and automatic medical report generation, and build a domain-specific speech recognition model using custom language models. This class will provide a hands-on project to build a specialized AI for paramedics procedures.


Highlights

Hands on experience in learning the state-of-the-art AI, deep learning and applications for image analysis and speech understanding.  
 Opportunity to learn how to design and create highly intelligent AI systems  
 Get to know AI systems that can interact with humans and enable health professionals to perform everyday tasks.  

Who Should Take

Data scientists, computer scientists, healthcare researchers and engineers, R&D managers, and hobbyist in big data analysis, AI, image analysis, speech processing, human computer interfaces.


Overall Learning Outcomes

Gain experience in learning basic AI architecture

Explain in non-technical terms the related concepts, including smart contracts, cryptocurrencies, decentralized finance, etc.

Knowledge of building digital “eyes” and “ears” for AI systems

Learn to create specialized AI systems for specific applications


Curriculum Modules

  • General introduction to healthcare AI
  • Diagnosis: Disease diagnosis using big data and deep learning
  • Reporting: Natural language understanding (sentence classification, keywords extraction, automatic medical report generation)
  • Medical Imaging: Medical image classification and segmentation