AI can aid faster, cost-effective diagnosis but clinical validation and data safeguards needed: experts
Experts say AI can speed diagnosis and expand access. They add that clinical validation and data safeguards are essential.
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Experts say AI can speed diagnosis and expand access. They add that clinical validation and data safeguards are essential.
Read the original →When a clinician's judgment and AI output diverge, what each side contributed disappears with the decision, because current interfaces capture the outcome and not the interaction. The authors propose that the clinician-AI interaction requires its own account and describe how divergence can be made visible. They say doing so supports transparent patient communication, better grounds moral responsibility, may mitigate liability, and reframes divergence as clinical AI's highest-signal moment.
Read the original →OpenEvidence and Johns Hopkins Medicine announced a strategic collaboration on October 13, 2026. It aims to reshape medical education and clinical care for the era of artificial intelligence.
Read the original →This is the second story in a series on AI in healthcare. Healthcare leaders discuss the challenges of getting AI tools to work as intended amid EHR integration and interoperability problems.
Read the original →Experts at the TIS-H Clinical AI Summit 2026 highlighted the need for real-world evaluation of AI solutions in healthcare. They said promising results from development or pilot programmes do not guarantee effective and safe deployment in hospitals. They emphasised clinical relevance, validation, and integration into existing workflows.
Read the original →Accenture argues that as AI becomes widely available, companies will be differentiated less by access to AI tools. It says operating models that define decision-making, accountability, workforce management, cost measurement and organizational learning will matter more.
Read the original →The Technology Development Board will provide ₹86 crore to Peptris. The funding will advance four AI-discovered drug candidates through preclinical development.
Read the original →SR One's Simeon George argues that the biggest returns from AI in drug development come from improving early-stage decisions. He says they do not come from predicting late-stage outcomes.
Read the original →New research describes an improved calibration framework for deep learning-based genetic perturbation models.
Read the original →Browne Jacobson's legal expert covers what the Tube map reveals about navigating AI in healthcare. Topics include regulation, patient safety, NHS adoption and innovation.
Read the original →President William Lai said the government is supporting physical therapists with resources and policies to build a healthy Taiwan. He pledged to use artificial intelligence to improve healthcare while balancing it with professional expertise. Lai met with World Physiotherapy.
Read the original →A small epilepsy monitoring study shows that a moderated, large language model-based chat interface lets patients converse with their electroencephalography monitoring in real time using a smartphone. Patient feedback cut seizure-detector false alarms by about 80% without clinician input.
Read the original →Large language models are increasingly used clinically in many non-English languages, yet most safety and performance evidence comes from English. The authors reviewed PubMed, Scopus and Embase from January 2022 to February 2026. They identified 806 studies evaluating large language models on clinical tasks across 62 non-English languages.
Read the original →J-Stream announced on October 13 that its consolidated subsidiary Big MWY has signed a business partnership agreement with an overseas literature service.
Read the original →Siemens unveiled its enterprise agentic system "Intelligence Center X" in Seoul on the 13th. Siemens said 74% of enterprise AI pilot projects are discarded.
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