AI for Healthcare

Explore AI technologies transforming healthcare, with a leading global university

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Course Dates

STARTS ON

9 December 2022

Course Duration

DURATION

2 months, Live Online
Sessions are usually conducted on Saturdays from 2:30-5:00 PM (SGT)

Course Fee

Apply by 7 December 2022 to avail our Festive Enrolment Benefit of 15%.
Use the code FUTUREYOU15 during payment to avail.
Limited seats available!

To ensure that holiday plans on the occasion of Christmas, New Year and Chinese New Year are not interrupted, no new modules will be released during this time and participants will receive a 2-week extension for submitting assignments. Participants will continue to have access to course material on the platform during this time.

WhatsApp an Advisor on +65 8014 3066
Have questions? Our Advisor will assist you promptly.

What will this Programme do for you?

Programme Highlights

Live Online Lectures

Assignments

Discussion Boards

Real-World Case Analysis

Case Studies

The State of Artificial Intelligence-Based FDA-Approved Medical Devices and Algorithms: An Online Database

Project IDentif.AI: Harnessing Artificial Intelligence to Rapidly Optimize Combination Therapy Development for Infectious Disease Intervention

Addressing COVID-19 Drug Development With Artificial Intelligence

Addressing COVID-19 Drug Development With Artificial Intelligence

AIDAN and AI-LIN vs. Vinny the Virus

Big Data and Machine Learning Algorithms for Healthcare Delivery

AI-Assisted Decision-Making in Healthcare

Capturing Feature-Level Irregularity in Disease Progression Modelling

Programme Modules

    • 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

Why Enrol for the Programme?

Artificial intelligence (AI) technologies are revolutionising nearly every aspect of healthcare. From data management to drug discovery and development to clinical practice and patient care, the innovations of AI continue to optimise and advance medical services.

By understanding the impact of current and emerging AI technologies—including global trends and regulatory constraints—healthcare professionals can drive decision-making, elevate patient care, and improve profitability and performance. Whether you want to gain the knowledge to invest in AI projects that can move healthcare research ahead faster and with greater predictability, design secure solutions for patients and customers, or develop enhanced products related to medical services, this programme can put you on the path to make a real difference within—and beyond—your organisation.

Who is this Programme for?

Professionals with a medical or non-medical background can benefit from the programme. AI for Healthcare is designed for CEOs and directors of small and medium enterprises, mid- to senior-level managers, and entrepreneurs.

Representative roles and industries that can benefit include:

  • Technology-driven sectors where AI applications are critical, including healthcare, medical services, medical devices, pharmaceuticals, biotechnology, ed tech, IT, real estate, and telecommunications
  • CEO, CIO, chairman, director, associate director, senior director of health care, pharmaceuticals, medical devices, information technology, and other relevant industries
  • General manager, product manager, marketing manager, account manager, operations manager, project manager of healthcare, biotechnology, ed tech, and medical devices
  • Founder, co-founder of healthcare, medical services, and pharmaceutical industries

82%

of healthcare and life sciences executives want to see their organisations more aggressively adopt AI technology.

SOURCE: KPMG, 2021

USD 1 trillion

is the potential AI has to add to Southeast Asia’s GDP by 2030.

SOURCE: KEARNEY, 2021

80%

of Southeast Asia is in the early stages of AI adoption.

SOURCE: KEARNEY, 2021

Programme Faculty

Faculty Member Associate Prof Ngiam Kee Yuan

Associate Prof Ngiam Kee Yuan

Faculty, NUS Yong Loo Lin School of Medicine

Associate Professor Ngiam is Senior Consultant at the Division of General Surgery at the National University Hospital (NUH) who specialises in thyroid and endocrine surgical disorders... More info

Faculty Member Prof Dean Ho

Prof Dean Ho

Faculty, NUS Yong Loo Lin School of Medicine

Prof Dean Ho is Provost’s Chair Professor, Director of The N.1 Institute for Health (N.1), Director of the Institute for Digital Medicine (WisDM), and Head of the Department... More info

Dr Feng Mengling

Faculty, NUS Yong Loo Lin School of Medicine

Dr Feng is currently the Assistant Director of Research at the Institute for Data Science, National University of Singapore. He also serves as the Senior Assistant... More info

Dr Kenneth Ban

Faculty, NUS Yong Loo Lin School of Medicine

Dr Ban obtained his BSc (Hons) in Biochemistry and MBBS degrees from NUS and a PhD in Cancer Biology from Stanford University. He completed his postdoctoral... More info

Certificate

Example image of certificate that will be awarded after successful completion of this program

Certificate

Participants who successfully complete the programme and meet the requisite 65% minimum attendance criteria will be awarded a verified digital certificate by NUS Yong Loo Lin School of Medicine.

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Early registrations are encouraged. Seats fill up quickly!

Flexible payment options available. Learn more.