Should We use AI for Therapy in Berlin?
People are turning to AI for mental health support. The article asks whether that is helpful.
Read the original →Every story in this issue with a short summary, so you can decide what to read before leaving the site. Summaries are written by AI (Claude) only from each publisher's own description and checked by Jev for anything not in that description. They are not full translations. Follow "Read the original" for the full story.
People are turning to AI for mental health support. The article asks whether that is helpful.
Read the original →Researchers from the Faculty of Social Sciences at The University of Hong Kong (HKU) worked with collaborators on an AI Supported Dynamic Clinical State Model.
Read the original →BITS Pilani has revised its undergraduate curriculum with new subjects, research pathways and experience-based activities. The overhaul responds to artificial intelligence's growing influence and concerns about student mental health.
Read the original →Sam Hupert said hospitals are signing seven-year deals with his software company. This defies fears that artificial intelligence will make it obsolete.
Read the original →The Frenz brainband talks to the wearer as they fall asleep. It connects to a phone and uses AI to curate audio to help them fall asleep faster.
Read the original →An explainable machine-learning analysis of NHANES data found only modest, nutrient-level predictive signals for psoriasis comorbidity among adults with anxiety disorder. Niacin was the leading signal.
Read the original →The Korean Academy of Family Medicine, chaired by Kim Cheol-min, held its 2026 Fall Conference at the Yeosu Convention Center. The conference ran over two days, on the 24th and 25th.
Read the original →HealthifyMe was founded in 2012 by Tushar Vashisht, Sachin Shenoy and Mathew Cherian and offers nutrition and calorie tracking alongside fitness coaching. Its commercial model is freemium. The CEO told reporters in 2018 that the company began monetising through nutritionist and trainer subscriptions about two years earlier, and concluded that much of that work could be done by AI.
Read the original →AI helps detect difficult lesions, aids in diagnosis and drug development. Algorithmic errors can be dangerous if doctors become overly reliant on the technology.
Read the original →Artificial intelligence has the potential to significantly improve the early detection of tuberculosis (TB) and lung cancer, according to Dr. Randeep Guleria.
Read the original →Prevention is becoming personalised, starting from a young age. An algorithm that combines genetics, lifestyle factors and medical tests will allow ischaemia risk to be assessed more accurately.
Read the original →Gujarat plans AI courses with real-world case studies across 8 higher-education tracks. The courses aim to train 5 lakh students, from basic literacy to job-ready skills.
Read the original →EverNear was founded by 17-year-old Jaswanth Chintala. It offers AI voice companionship for older adults with Alzheimer's.
Read the original →A machine learning study reports that dynamic diameter changes of retinal blood vessels during flicker light stimulation can be used to estimate chronological age. The mean absolute error was 9.3.
Read the original →The most consequential shift in European healthtech over the past three years has happened in the middle of the market, not at the top. The companies changing hands and giving founders their first real liquidity are businesses with $25M to $250M enterprise value. They built revenue and won regulated customers.
Read the original →The final day also featured a chat from LRS' Robeert Rustman and influencer Joey Price.
Read the original →Some of the hottest MSP products on display at XChange NexGen 2026 were pitched as ways to monitor, govern and secure customer AI use. Others were pitched as ways to reduce manual tasks for security and legal work.
Read the original →American scientists have developed an artificial intelligence tool that can detect abnormal electrocardiogram (ECG) signals. It is intended to help identify people at risk of sudden cardiac death.
Read the original →An artificial intelligence model has been developed that can assess a cancer patient's general health condition and life expectancy from a facial photograph. It is expected to serve as a tool to help doctors judge patients' survival chances and identify the best treatment.
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