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AI in Healthcare: Opportunities & Challenges

Taipei Medical University via Coursera

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Provider

Coursera
Pricing

Paid Course
Languages

English
Certificate

Certificate Available
Effort

4 weeks, 3 hours a week
Sessions

Self-Paced
Level

Beginner
Subtitles

English

Found in

Overview

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Artificial Intelligence (AI) has become the most influential advancement in healthcare, marking the fourth medical industrial revolution after antibiotics and imaging. This course provides a comprehensive framework for understanding how AI optimizes clinical decisions through complex data analytics. Regarding opportunities, the curriculum explores how AI moves beyond "one-size-fits-all" care toward preventive care and precision medicine. Students will learn to integrate multi-dimensional data—genotype, phenotype, environment, and behavior—using real-world examples like Taiwan’s “My Health Bank” and liver cancer prediction. We also cover cutting-edge applications such as reinforcement learning, AR-assisted surgery, and Large Language Models (LLMs) within the smart clinic ecosystem. The course also addresses critical challenges, analyzing how a lack of semantic interoperability and inherent machine bias in "black box" algorithms impact ethics and patient safety. Highlighting that medicine is far riskier than video games, we position AI as Augmented Assisted Natural Intelligence (ANI) designed to correct human error. Ultimately, participants will reflect on clinical wisdom, learning to “unlearn and relearn” to become ideal clinicians who balance technological mastery with human empathy.

Syllabus

Why do we need Artificial Intelligence in healthcare?

This unit explores the necessity of AI as the fourth medical industrial revolution, following breakthroughs like X-rays and antibiotics. It addresses critical gaps in modern medicine, such as the neglect of participatory health, the limitations of "one-size-fits-all" treatments, and medical errors. Students will examine how AI enables a shift from curative to preventive care through precision medicine and patient empowerment, exemplified by Taiwan’s "My Health Bank". Additionally, the unit introduces the evolution and ethical utilization of Large Language Models (LLMs) in academic research.

Opportunities of Artificial Intelligence in Healthcare

This unit traces the evolution of AI from historical "winters" to modern breakthroughs like Convolutional Neural Networks (CNNs). It highlights the shift from imprecise "one-size-fits-all" medicine—which often leads to diagnostic errors and inconsistent quality—to data-driven precision care. Students will explore common algorithms used for classification, prediction, and optimization across clinical dimensions. The curriculum emphasizes AI’s potential to integrate genotype, phenotype, and environmental data to solve medical imprecision. Finally, the unit frames AI as "intelligent infrastructure" designed to enhance clinical decision-making and correct human errors.

The Problem With AI: machines are learning, but can they understand?

This unit examines critical barriers to AI implementation in clinical settings, moving beyond algorithmic patterns to functional understanding. Students will explore Reinforcement Learning (RL) and its unique complexities in high-risk medical environments where trial-and-error is often impossible. The curriculum highlights the challenge of semantic interoperability, addressing how "information-poor" data and a lack of standardized terminology hinder AI performance. Furthermore, the unit dissects the "black box" nature of algorithms, emphasizing the necessity of explainable AI (XAI). Finally, it confronts the "illusion of impartiality," analyzing how machine bias can compromise clinical equity.

Are we moving towards dehumanizing healthcare?

This unit explores whether the rapid integration of advanced technologies—such as AR, VR, and the Internet of Medical Things (HIoT)—leads to the dehumanization of medicine. Students will examine cutting-edge applications like digital twins and genomic immersion designed to achieve "full doctor-patient immersion". However, the curriculum balances technological optimism with a critical reflection on the personal nature of healthcare, emphasizing that "a fool with a tool is still a fool". Ultimately, the unit defines the "ideal clinician" of the digital age: a practitioner who leverages Augmented Assisted Natural Intelligence (ANI) to enhance safety while maintaining deep empathy and humanistic wisdom.