ENG: Researchers at McGill University have created an artificial intelligence tool called DOLPHIN that can detect disease markers inside single cells that were previously invisible. The study, published in Nature Communications, shows how this tool could help doctors identify diseases earlier and choose treatments more accurately. According to senior author Jun Ding, DOLPHIN could reduce the trial-and-error process in medicine by matching patients with therapies that are most likely to be effective.
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AI-driven wearable device accelerates personalized wound healing
ENG: As a wound heals, it progresses through several key stages: clotting to stop bleeding, immune response, scabbing, and scarring. Engineers at the University of California, Santa Cruz, have developed a wearable device called “a-Heal” to optimize each stage using artificial intelligence and bioelectronics. The device integrates a miniature camera and AI system to detect the wound’s healing stage and automatically deliver targeted treatment in the form of medication or an electric field. By adapting to the patient’s individual healing process, a-Heal provides personalized care. Portable and wireless, it could make advanced wound therapy accessible to patients in remote or low-mobility situations. Early preclinical results show that wounds treated with a-Heal healed about 25% faster than with standard care.
Read MoreHuntington’s Disease Successfully Treated for the First Time with Gene Therapy
ENG: Huntington’s disease, one of the most devastating inherited neurological conditions, has been successfully treated for the first time, according to UK doctors leading a groundbreaking trial. The gene therapy, developed by uniQure and tested at University College London, slowed disease progression by an average of 75% over three years. This means the decline that would normally occur in one year took four, offering patients decades of better quality life. Delivered through 12-18 hours of precise neurosurgery, the treatment uses a modified virus to insert genetic material into brain cells, enabling them to produce microRNA that silences the faulty huntingtin gene responsible for killing neurons.

AI Model Detects Fatty Liver Disease from Chest X Ray Images
ENG: Fatty liver disease, a condition caused by the buildup of fat in the liver, affects roughly one in four people worldwide and can lead to cirrhosis or liver cancer if left untreated. While ultrasounds, CT scans, and MRIs are the standard diagnostic tools, they require specialized equipment and are costly. Chest X-rays, by comparison, are inexpensive, widely available, and involve lower radiation exposure. Although they are mainly used to assess the lungs and heart, they also capture part of the liver, which makes them a potential tool for detecting fatty liver disease.
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