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Quick Facts

Medium Of InstructionsMode Of LearningMode Of DeliveryFrequency Of Classes
EnglishSelf Study, Virtual ClassroomVideo Based, Text BasedWeekends

Courses and Certificate Fees

Certificate AvailabilityCertificate Providing Authority
yesNUS

The Syllabus

  • Biomedical informatics for solving problems
  • Types of data
  • Sources of data: healthcare system
  • Relational data model
  • Structured Query Language (SQL)
  • Data interoperability

  • Data repository
  • Data privacy
  • Data errors and measures to improve data quality
  • Data transformation
  • Data management

  • Introduction to terminologies:
    •  Business intelligence
    •  Data mining
    •  Data analytics
    •  Artificial intelligence
    •  Machine learning/deep learning
    •  Big data
  • A brief modern history of AI

  • Biological neuron
  • Perceptron
  • Activation function
  • AI and gradient descent
  • Convolution neural network for medical image understanding
  • The Digital mammography dream challenge - problem, approach, results, mistakes, solution

  • Challenges of drug discovery and development
  • Innovations in drug discovery, development, and diagnostics
  • AI in drug innovation continuum
  • Bridging early discovery with commercialisation

  • The evolution of technology in healthcare
  • Rethinking drug development using AI
  • Operationalising AI in healthcare

  • Clinical AI Development Process
  • Challenges in developing AI tools
  • Architecture for AI development in clinical practice

  • Production deployment in clinical AI
  • Ethics and regulatory considerations of clinical AI
  • AI implementation and success in Healthcare

Instructors

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