Lorenzo Righetto

Agentic A.I. to predict body-wide and organ specific biological aging with associated health outcomes nature.com/articles/s4159…

I will soon be transitioning to a new position, so Nature Medicine is now looking for a new medical AI editor! Please find the link to apply below and let me know if you have any questions about what the position entails springernature.wd3.myworkdayjobs.com/SpringerNature…

A panel of 9 LLMs was exposed to simulated clinical cases with switched sociodemographic features exploring various dimensions and showed differences in recommendations for patient treatment, referral and follow-up @girish_nadkarni @EyalKlang nature.com/articles/s4159…

Two early studies reveal capabilities and shortcomings of @deepseek_ai in clinical uses, with evaluation on pre-existing benchmark data nature.com/articles/s4159… nature.com/articles/s4159…

In an implementation study involving 51,760 hospitalizations, an EHR-based risk prediction model informed clinicians of patients needing consultation on Opioid Use Disorder and decreased readmissions to the hospital @Majeans2011 nature.com/articles/s4159…

In a large pragmatic cluster-randomized trial involving 74 sites in 2 health systems in the US, a real-time alert system assisting nurses decreased mortality risk by 35.6%, with positive effects also on length of stay nature.com/articles/s4159…

New AI chatbot for parents improves #HPV vaccine uptake 1st trial of #AI tool designed to answer parents' questions about HPV, and reduce health disparities, shows increase in uptake and engagement with #health professionals. 👉lshtm.ac.uk/newsevents/new…

A commentary on our recently published trial on LLM assistance to physicians highlights challenges in translating these tools into actual clinical use @NatureMedicine nature.com/articles/s4159…

Making #LLMs into reliable physician assistants: In their News & Views article, Sílvia Mamede and Henk Schmidt argue that future research should harness our understanding of the cognitive processes underlying clinical reasoning to optimize LLM utility. nature.com/articles/s4159…

An AI model defines a data-driven set of Total Parenteral Nutrition compositions to assist clinicians in personalized treatment of neonates in intensive care, with validation from external cohorts and a blinded reader study @NimaAghaeepour @msirota84 nature.com/articles/s4159…

In a randomized controlled trial in individuals with persistent atrial fibrillation, an individualized ablation procedure informed by AI led to improved efficacy for reducing arrhythmia recurrence at 12 months following the ablation procedure nature.com/articles/s4159…

By simulating the implementation of airport-based wastewater surveillance sites at global level, a modelling study shows how this early warning system would perform in identifying sources of pandemic outbreaks @stonge_g @alexvespi nature.com/articles/s4159…

Getting your real-time heart rhythm monitored for 10 days now requires an ECG technician to review and notify your doctor of a critical arrhythmia. A new study showed A.I. did better than technicians (98.6% vs 80.3%) for identifying these abnormalities nature.com/articles/s4159……

In a large-scale analysis of ambulatory electrocardiographic recordings, a deep learning algorithm had a substantially higher sensitivity for detection of critical arrhythmias as compared to technicians nature.com/articles/s4159…

A randomized trial of GPT-4 vs 92 physicians with or without this #AI LLM for performance on patient care tasks. AI improved physician performance, on par with AI alone (based on 5 clinical vignettes) nature.com/articles/s4159… @NatureMedicine @AdamRodmanMD @jonc101x

In a prospective study involving 92 physicians from multiple institutions, access to large language model assistance on top of conventional resources increased the quality of patient care reasoning @jonc101x @AdamRodmanMD @robjgallo nature.com/articles/s4159…

Preventing cognitive decline through lifestyle intervention, results of a large randomized trial nature.com/articles/s4159… Conducted online, 4 modules, personalized, targeting physical activity, nutrition, cognitive activity, depression/anxiety, in at-risk individuals, mean age 65…