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How and When could AI be Used in Emergency Medicine?

While artificial intelligence (AI) technology is increasingly being used - formally and informally - to support medical diagnoses, its utility in emergency medical settings remains an open question. Can AI support doctors in situations where split-second decision making can mean the difference between life and death? Researchers at Drexel University broached the question with clinicians at Children’s National Medical Center in Washington, D.C., to better understand how and when the technology could help them save lives.

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AI-Assisted Interviews Increase Accuracy in Diagnosing Mental Illness

A new study shows that an AI assistant can conduct assessment conversations with patients with higher accuracy than the rating scales used in healthcare today. In the study, 303 participants were interviewed by the AI ​​assistant Alba, who then suggested possible psychiatric diagnoses.

In addition to being interviewed by an AI assistant, the participants also had to fill out standardized rating scales for the nine most common psychiatric diagnoses.

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Studies Suggest Ambient AI Saves Time, Reduces Burnout and Fosters Patient Connection

When physicians don’t have to type detailed clinical notes while simultaneously talking to their patients, the visit feels different. Eye contact lasts longer, follow-up questions become sharper, and - crucially - clinicians go home less drained.

That’s the promise of ambient clinical documentation, an artificial intelligence (AI)-assisted technology that records healthcare conversations and transforms them into clear,

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AI Tool Spots Blood Cell Abnormalities Missed by Doctors

An AI tool that can analyse abnormalities in the shape and form of blood cells, and with greater accuracy and reliability than human experts, could change the way conditions such as leukaemia are diagnosed.

Researchers have created a system called CytoDiffusion that uses generative AI - the same type of technology behind image generators such as DALL-E - to study the shape and structure of blood cells.

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AI Tool can Analyse Complex Cancer Images Rapidly

Complex digital images of tissue samples that can take an experienced pathologist up to 20 minutes to annotate could be analysed in just one minute using a new AI tool developed by researchers at the University of Cambridge.

SMMILe, a machine learning algorithm, is able not only to correctly detect the presence of cancer cells on slides taken from biopsies and surgical sections,

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A New Heart Monitoring System Combining 3D Printing and AI

A new heart monitoring system combining 3D printing and artificial intelligence (AI) could transform the way doctors measure and diagnose patients' heart health.

Developed at SFU’s School of Mechatronic Systems Engineering, the system features reusable dry 3D-printed electrodes embedded in a soft chest belt - the folding origami-shaped design uses gentle suction to stick to the skin.

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AI may Help Save Lives in ICUs

A study published in the Journal of Critical Care, conducted with the participation of the D’Or Institute for Research and Education (IDOR), investigated how to measure efficiency in the use of resources for patients with severe community-acquired pneumonia (CAP), an illness contracted outside hospital settings and most common among older adults.

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AI can Improve Psychiatric Diagnosis

Large language models can help improve questionnaires used to diagnose mental illness by optimizing symptom generalizability and reducing redundancy. They can even contribute to new conceptualizations of mental disorders. That is the result of an international study led by Professor Dr Joseph Kambeitz and Professor Dr Kai Vogeley from the University of Cologne’s Faculty of Medicine and University Hospital Cologne.

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Visionary Healthcare Ideas Wanted: Applications Now Open for the DMEA Sparks Award 2026

21 - 23 April 2026, Berlin, Germany.
Students and graduates in the field of digital health can now apply for the DMEA sparks Award 2026. Each year, the award recognises the best theses that contribute to the digitalisation of healthcare with innovative ideas and research results.

The competition is aimed at young talents from the fields of IT, medicine, health economics and related disciplines who focus on new technologies, concepts or applications in their bachelor's and master's theses.

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Computational Pathology in Precision Oncology: From Task-Specific to Foundation Models

Driven by the rapid advancements in artificial intelligence, computational pathology is emerging as a critical engine in the era of precision oncology. Traditional computational pathology primarily relies on task-specific models, which require the development of independent models for each distinct task.

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