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.
A narrative review maps how machine learning and deep learning now span oral cancer care. The applications range from smartphone lesion triage and whole-slide computational pathology to prognostic modelling.
Read the original →Qritive reports that its tool detected 9 in 10 prostate cancer cases. The article says UAE medical AI faces its real test after the pilot, and that local cloud limits scale.
Read the original →A retrospective cohort study of 64,382 adult emergency department patients in Brazil found that adding natural language processing of chief complaints to machine learning classifiers improved triage.
Read the original →Researchers report a feature-weighted, calibrated explainable AI framework that reached 91.07% accuracy on a cleaned heart disease dataset. The framework exposes its reasoning through SHAP and LIME.
Read the original →Philadelphia-based Jefferson Health's ambient AI rollout was associated with up to 16.6% less after-hours documentation. It was also associated with up to 39.3% faster chart closure.
Read the original →Rising concern about an AI "death spiral" for overleveraged data center players is pushing investors to focus on AI models that solve real problems and can justify their computing costs. Australian AI healthcare companies apply algorithms to diagnoses, treatment decisions and hospital workflows. The article walks through three candidates from a screener.
Read the original →Palantir broadened its sovereign AI offerings for flagship clients across defense, healthcare, construction and manufacturing. Enterprises cited in the expanded rollout include L3Harris, McCarthy Building Companies, NVIDIA, Ondas, Regna AI and Tampa General Hospital. The company also deepened its collaboration with Stagwell to build AI-powered marketing tools focused on data control and operational efficiency.
Read the original →Cuban, known for "Shark Tank" and his involvement in the Dallas Mavericks NBA team, entered healthcare in 2022 by starting the online pharmacy Cost Plus Drug Company. Its standard pricing scheme is the cost the company pays for the drug, plus 15%.
Read the original →The Ramco Cements Ltd has received recognition at the Global Artificial Intelligence (AI) Summit & CII National AI Awards.
Read the original →An opinion article argues that medical AI should strengthen, rather than displace, bedside observation, clinical reasoning and the physician-patient relationship.
Read the original →Google’s multiagent artificial intelligence system outperformed comparison AI systems on several personal health tasks. Expert reviewers, however, rated 17% of
Read the original →A standardized evaluation looked at 56 chatbot responses to 14 real search queries about high-intensity interval training. Perplexity received the highest median quality and transparency scores.
Read the original →Okayama University Hospital in Kita Ward, Okayama, has installed multilingual, AI-based interactive digital signage inside the hospital. The signage automatically guides visitors to consultation and examination locations.
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.
Read the original →Major Chinese internet companies are entering AI doctor services. They train AI on the clinical experience of renowned doctors to create digital doubles that provide 24-hour health consultations for general patients and support for medical staff. The business models are still at an exploratory stage.
Read the original →AI in healthcare holds great potential for Vietnam, but it also comes with very specific requirements. AI systems need to be developed and evaluated using data related to Vietnam's population, disease patterns, resources, professional processes and the way the health system operates.
Read the original →