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"AI is one of the most influential tech advances of the 21st century… transforming medical services and improving diagnostics, surgery, and monitoring, while raising ethical concerns.”

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AI simulates human thought—learning, reasoning, self-correcting.

Key methods: ML, DL, ANN (Amisha et al. 2019; Chikhaoui 2022).

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ML learns patterns from data.

DL uses layered neural nets for complex data.

ANN analyzes imaging & predicts disease progression.

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Robots improve precision & safety (Bellini et al. 2021).

Benefits: less pain meds, less bleeding/infection, faster recovery (Prabu 2014).

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Virtual rehearsal of operations to reduce risk.

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Creates anatomical models for planning & patient communication (Alexander et al. 2019).

Produces customized prosthetics & implants (Ventola 2014).

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Wearables, in-room sensors, apps track vitals, movement, and sleep.

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AI detects issues and notifies clinicians instantly (Chikhaoui 2022).

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Ideal for diabetes, heart and lung disease reducing readmissions & cost.

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AI can’t truly feel; patients may distrust machine care (Ding & Lu 2019).

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Especially for vulnerable groups machine decisionmaking feels impersonal (Chikhaoui 2022).

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Biases in datasets can harm marginalized patients (Gerke et al. 2020).

Example: Skin cancer tools missing darker skin.

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Hospitals are vulnerable to hacks targeting data and devices (Gerke et al. 2020).

Data corruption risks misdiagnosis or privacy loss.

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Encryption, audits, staff training: crucial to maintain trust.

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AI-tailored treatments based on genetics and lifestyle.

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AI speeds up finding new therapeutics.

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AI tools enabling expert care in underserved regions.

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Real-time monitoring for patients outside hospitals.