Introduce the concept of Artificial Intelligence (AI). How does AI help clinical diagnosis? Do you…

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Introduce the concept of Artificial Intelligence (AI). How does AI help clinical diagnosis? Do you perceive any threat to privacy of the individual in the use of AI in healthcare?

Ghissu Editorial · Accepted Answer

AI lets machines learn from data, and in healthcare it reads scans, screens for diseases like tuberculosis and diabetic retinopathy, and supports clinical decisions. The privacy threat is real, as the AIIMS Delhi ransomware attack of 2022 showed, so consent under the DPDP Act, 2023 is essential.

**Introduction**

Artificial Intelligence (AI) is the ability of machines to learn, reason and recognise patterns like humans; through machine learning, algorithms trained on large datasets improve with experience instead of following fixed rules, which makes medical images and records a natural field for it.

**How AI Aids Clinical Diagnosis**

SKETCH: flow | AI-Assisted Diagnosis
- Scan or patient record
- Trained algorithm
- Pattern detected
- Risk flagged
- Doctor confirms

1. **Reading medical images**: Deep-learning tools read X-rays and CT scans at scale; Qure.ai's qXR flags tuberculosis on chest X-rays, and the WHO endorsed computer-aided TB screening in 2021.
2. **Screening where specialists are scarce**: Google's diabetic retinopathy algorithm, validated with Aravind Eye Hospital, and Niramai's thermal breast cancer test take early detection to remote clinics.
3. **Decision support and prediction**: AI combines symptoms, lab values and history to suggest diagnoses, flag drug interactions and warn of sepsis or cardiac events before they peak.

**Threats to Individual Privacy**

1. **Consent and secondary use**: Reusing records without fresh consent breaches the privacy upheld in Puttaswamy (2017); the UK found the Royal Free trust's sharing of 1.6 million records with Google DeepMind unlawful in 2017.
2. **Breach and re-identification**: The November 2022 ransomware attack on AIIMS Delhi showed how exposed health data is, and anonymised records can be re-identified.
3. **Profiling and opacity**: Predictions could reach insurers or employers, and black-box models hide how data shaped a decision.

**Conclusion**

AI can make diagnosis faster and fairer, but the privacy threat is real. The Digital Personal Data Protection Act, 2023, the ICMR's 2023 guidelines on AI in healthcare and privacy by design in the Ayushman Bharat Digital Mission can keep it human-centric.

Introduce the concept of Artificial Intelligence (AI). How does AI help clinical diagnosis? Do you perceive any threat to privacy of the individual in the use of AI in healthcare?

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