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Microsoft and Mayo Clinic unveil a new ‘safe and trusted’ AI for healthcare
The organisations said the model is being initially deployed within Mayo Clinic’s clinical environment, where it can be tested and refined through real-world use. Microsoft and the nonprofit American academic medical centre Mayo Clinic are developing a new artificial intelligence (AI) model designed specifically for healthcare, in a move aimed at supporting patients, clinicians and consumers, according to an announcement. The organisations said the model will combine Mayo Clinic’s medical...
Appraisal Dimensions Generalise Better than Emotion Labels for Cross-Age Affect Recognition in AI-Assisted Healthcare
arXiv:2604.27938v2 Announce Type: replace Abstract: The integration of artificial intelligence (AI) into healthcare has advanced significantly, yet affect recognition remains a major challenge, particularly in AI-assisted interventions such as Computerized Cognitive Training (CCT). The THERADIA-WoZ corpus was developed to enable multimodal affect recognition in the context of AI-driven CCT, focusing on an older adult population. This study extends the corpus by introducing a dataset...
Incentives, Equilibria, and the Limits of Healthcare AI: A Game-Theoretic Perspective
arXiv:2603.28825v2 Announce Type: replace Abstract: Using a stylised coordination problem drawn from inpatient capacity management, three archetypal forms of AI deployment are described: effort-reducing technologies, observability-oriented systems, and interventions that alter underlying incentive structures. Effort reduction and observability may improve performance within existing patterns of behaviour but do not, in general, change which actions are individually rational. As a result,...
Perspective on Bias in Biomedical AI: Preventing Downstream Healthcare Disparities
Announce Type: replace Abstract: Healthcare disparities persist across socioeconomic boundaries, often attributed to unequal access to screening, diagnostics, and therapeutics. However, this perspective highlights that critical biases can emerge much earlier, during data collection and research prioritization, long before clinical implementation, particularly in studies focused on molecular and omics data. A vast number of studies focus on collecting omics data, but the demographic...
Large AI Models in Dental Healthcare: From General-Purpose Systems to Domain-Specific Foundation Models
Announce Type: replace Abstract: Background: Oral diseases affect nearly 3.5 billion people worldwide, yet the comparative clinical potential of large-scale AI models in dentistry remains poorly understood. Three distinct model categories have emerged: language-generative models, discriminative vision foundation models, and dental-specific foundation models, with no unified review examining their relationships and collective limitations. Methods: Following PRISMA-ScR guidelines, we...
Large AI Models in Dental Healthcare: From General-Purpose Systems to Domain-Specific Foundation Models
Announce Type: new Abstract: Background: Oral diseases affect nearly 3.5 billion people worldwide, yet the comparative clinical potential of large-scale AI models in dentistry remains poorly understood. Three distinct model categories have emerged: language-generative models, discriminative vision foundation models, and dental-specific foundation models, with no unified review examining their relationships and collective limitations.
China Healthcare Stocks Fall to Record Low Valuation on AI Drain
China Healthcare Stocks Fall to Record Low Valuation on AI Drain China’s healthcare stocks have slumped to their cheapest level ever, as a rush into local artificial intelligence beneficiaries draws capital away from defensive sectors. The CSI Health Care Index is now trading at about 2.7 times price to book, slipping below even the low set during the global financial crisis. Meanwhile, a popular index of Chinese tech stocks trades at around 8 times.
AI: Doctors risk being sued if tools go wrong, while companies are “shielded,” report warns
Doctors are being left exposed to legal claims by a “widening gulf” between the law and the rapidly changing use of artificial intelligence (AI) in healthcare, the Medical Protection Society (MPS) has warned. In its report Closing the AI Liability Gap,1 the medical defence organisation said that doctors and the NHS were currently expected to absorb all legal responsibility for AI use in healthcare, while AI companies were “shielded.”Under
AI saves clinicians time but most lack training, survey finds
AI saves clinicians time but most lack training, survey finds June 9 : AI is saving clinicians time, but the majority of healthcare professionals say training in the technology is inadequate, inconsistent or unavailable, a global survey by Philips showed on Tuesday. The study, Philips Future Health Index, was carried out through two quantitative surveys, one with 2,011 healthcare professionals and another with 20,085 patients across 10 countries. • Most AI use cases for healthcare...
Clinicians are embracing AI faster than hospitals can handle, report finds
Healthcare professionals are saving weeks of working time each year thanks to AI, but health systems are struggling to keep pace with demand, according to a new report by Philips. Artificial intelligence is reshaping healthcare, from the way clinicians take notes during a consultation to how informed they arrive at an appointment. The report, Future Health Index 2026, carried out by the health technology giant Philips, aimed to quantify and measure the exact impacts of AI on doctors' and...