Rise in people using AI for mental health
More people are opening up an app instead of an office door when they need someone to talk to. Therapists say chatbots should only go so far.
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.
More people are opening up an app instead of an office door when they need someone to talk to. Therapists say chatbots should only go so far.
Read the original →Depression affects hundreds of millions of people worldwide. Deep learning systems meant to flag it early have long lacked real clinical interview data.
Read the original →Catalyst Performance, a personal training studio in Singapore, is reported in an October 16, 2026 release to be the first fitness brand to win the National SME AI Impact Awards.
Read the original →A bibliometric analysis of 3,332 publications shows wearable sensor research in Parkinson's disease has grown exponentially since 2019. The research has shifted from basic motion tracking toward AI-driven approaches.
Read the original →A review describes how artificial intelligence and integrative multi-omics are transforming host-microbiome research. They convert complex molecular data into predictive models.
Read the original →AI's growing appetite for electricity is putting pressure on power supplies. Firma Power simplifies the process of securing renewable energy. It helps data centers find suitable projects and gives clean-energy developers more opportunities.
Read the original →Benoit Huet, PhD, will discuss the performance of eyonis LCS. The tool combines pulmonary nodule detection with malignancy assessment to aid in diagnosis.
Read the original →A new graph neural network framework called GlucoSense combines smartphone activity recognition with glucose forecasting to identify early type 2 diabetes risk. It matched HbA1c lab results for all six.
Read the original →An AstraZeneca marketing executive says the ads are aimed at asthma patients. The executive says, "We can make something that seems very scientific more light-hearted, more accessible."
Read the original →A cross-sectional evaluation tested ChatGPT, DeepSeek, Perplexity, and Microsoft Copilot. All four AI chatbots produced hallucinated heart failure education content.
Read the original →The description discusses the distinction between discrimination and calibration when interpreting the reported performance figures. Discrimination, captured by the AUROC, describes how well a model separates outcomes.
Read the original →A vision-based machine learning study of 61 dementia care residents found that ceiling-mounted cameras and gait analysis could detect gait severity changes. The changes were associated with acute antipsychotic dose changes.
Read the original →The global ophthalmic imaging equipment market is set to expand through 2035. Growth is driven by aging populations and rising adoption of AI-enhanced diagnostic imaging systems.
Read the original →Artificial intelligence has long been accused of being a black box, especially in medicine, where a wrong answer can change a life. A research team spanning Pakistan, Saudi Arabia and the United States is involved in this work.
Read the original →A new conceptual framework warns that generative AI could create a double divide in aging societies. It describes unequal opportunities for older adults to use and critically evaluate AI systems.
Read the original →The weekly roundup covers developments across European HealthTech, MedTech and digital health, including corporate investment, early-stage funding rounds and regulatory moves. In MedTech, it notes strategic repositioning by multinational device companies, targeted venture backing for hardware innovation, and regulatory moves around device access.
Read the original →Edgeout added a new feature to MentCare, an AI mentor for care providers. It drafts shift plans from requested days off and night-shift rules, and checks for consecutive workdays and staff shortages. For days with staff shortages, it automatically assigns staff from other facilities based on approved help registrations.
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