AI in Healthcare: Revolutionising Diagnosis, Treatment and Patient Care
From reading scans to cutting paperwork, artificial intelligence is changing healthcare. Where it helps today, and the risks to manage.
Artificial intelligence is already part of modern medicine. More than a thousand AI-enabled medical devices have been authorised by the U.S. Food and Drug Administration, the majority in radiology, and hospitals worldwide are testing AI to ease pressure on stretched staff.
Faster, earlier diagnosis
AI systems can flag suspicious areas on X-rays, CT scans and mammograms for a specialist to review, helping prioritise urgent cases. In some screening programmes, AI acts as a second reader alongside human experts.
Less paperwork, more patient time
Clinical documentation consumes a large share of doctors' time. AI tools that draft notes from consultations, with the clinician reviewing and approving them, are being adopted to give time back to patients.
Smarter health systems
Singapore has been an early adopter, with its public health sector exploring AI for tasks such as predicting patient deterioration and supporting administrative work. Hospitals elsewhere use similar tools to forecast demand and manage beds.
The risks
- Bias: models trained on unrepresentative data can perform worse for some groups.
- Errors: AI output must be checked by qualified professionals.
- Privacy: health data needs the strongest protection.
The most successful uses keep clinicians in charge, with AI handling the pattern-spotting and paperwork that machines do well.
