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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Drug Toxicity Predicted by Differences Between Preclinical Models and Humans

In the UK, there was a case where TGN1412, an immunotherapy under development, triggered a cytokine storm within hours of administration to humans, leading to multiple organ failure. Another example, Aptiganel, a stroke drug candidate, was also highly effective in animals but was discontinued in humans due to side effects such as hallucinations and sedation.

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AXREM and Highland Extend Partnership to Drive Growth and Visibility for the UK's Diagnostic Health Tech Sector

UK trade association AXREM and health tech growth specialist Highland have extended their partnership for two further years, reaffirming a shared commitment to supporting growth across the UK’s diagnostic and health technology markets.

AXREM represents member companies that collectively provide the majority of diagnostic medical imaging and radiotherapy equipment used in UK hospitals.

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AI Can Speed Antibody Design to Thwart Novel Viruses

Artificial intelligence (AI) and "protein language" models can speed the design of monoclonal antibodies that prevent or reduce the severity of potentially life-threatening viral infections, according to a multi-institutional study led by researchers at Vanderbilt University Medical Center.

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How Mayo Clinic Experts Are Using AI to Better Detect Sleep Apnea, Especially in Women

Mayo Clinic researchers have developed an artificial intelligence (AI) algorithm that can identify obstructive sleep apnea (OSA) using the results from an electrocardiogram (ECG) - a common heart test. The innovation could make it faster, cheaper, and easier to spot sleep apnea, particularly in women, who are often underdiagnosed.

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Team's Biosensor Technology may Lead to Breath Test for Lung Cancer

University of Texas at Dallas researchers have developed biosensor technology that when combined with artificial intelligence (AI) shows promise for detecting lung cancer through breath analysis.

The electrochemical biosensor identifies eight volatile organic compounds (VOCs) that are potential biomarkers for thoracic cancers, which include lung and esophageal cancers.

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