# Health & Bioscience Published articles for Health & Bioscience. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## A connectomics milestone: Mapping the complete male fruit fly brain DevFeed: [A connectomics milestone: Mapping the complete male fruit fly brain]() Original publisher: [Read original article]() Published: 2026-09-03T16:00:03Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [datasets](), [Google]() Tags: [ai](), [datasets](), [general-science](), [google](), [health-bioscience](), [machine-intelligence](), [open-source](), [open-source-models-datasets](), [research](), [science]() ### AI overview Google Research describes a complete wiring map of the male fruit fly's brain and central nervous system, containing over 166,000 neurons and 125 million synaptic connections. The connectome was produced through a decade-long partnership using computing and AI, and is available to explore and download via Neuroglancer. ### Source excerpt General Science ## GlucoFM: Foundation model for continuous glucose monitoring DevFeed: [GlucoFM: Foundation model for continuous glucose monitoring]() Original publisher: [Read original article]() Published: 2026-08-26T18:42:43Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [foundation-models](), [Google](), [data](), [datasets]() Tags: [data](), [foundation-models](), [google](), [health-bioscience](), [machine-intelligence](), [model](), [research]() ### AI overview GlucoFM is a lightweight, self-supervised foundation model for continuous glucose monitoring. Its dual-stream design separates slower glycemic trends from short-term deviations while preserving time-of-day and missingness information. Evaluated across four cohorts and seven clinical prediction tasks, it achieved higher average PR-AUC than the evaluated GluFormer variant. ### Source excerpt Health & Bioscience ## An AI tool for prioritizing candidate biomarkers from wearable sensor data DevFeed: [An AI tool for prioritizing candidate biomarkers from wearable sensor data]() Original publisher: [Read original article]() Published: 2026-08-21T17:02:24Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Artificial Intelligence](), [Generative AI](), [data](), [Time Series](), [datasets](), [Temporal data](), [Training AI Models](), [Model Development]() Tags: [agents](), [ai](), [analysis](), [data](), [datasets](), [generative-ai](), [health-bioscience](), [memory](), [reasoning](), [research](), [series](), [time-series](), [training](), [validation](), [workflow]() ### AI overview The Biomarker Discovery Framework is a supervised multi-agent system for prioritizing biomarker candidates from wearable-sensor data. It combines hypothesis generation, statistical analysis, model training, adversarial validation, and literature-grounded reasoning in a traceable six-phase workflow. Across three cohorts, it recovered known clinical signals, found convergent biomarkers across independent datasets, and improved downstream prediction when demographic features were included. ### Source excerpt Generative AI ## Seeing beyond BMI: Estimating cardiometabolic risk with smartphone imagery DevFeed: [Seeing beyond BMI: Estimating cardiometabolic risk with smartphone imagery]() Original publisher: [Read original article]() Published: 2026-08-17T10:34:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Deep neural networks](), [Deep learning](), [Machine learning](), [Google]() Tags: [deep-learning](), [general-science](), [google](), [health](), [health-bioscience](), [machine-intelligence](), [machine-learning](), [monitoring](), [multimodal](), [science]() ### AI overview Google Research presents PhotoScan, a deep learning approach that estimates body composition from smartphone photos and predicts insulin resistance with accuracy comparable to DXA scans in a clinical research setting. The article explains how body-composition measures such as fat distribution and visceral fat may complement wearable data for earlier cardiometabolic risk assessment. ### Source excerpt General Science ## Advancing AMIE towards expert-level audio-visual clinical consultations DevFeed: [Advancing AMIE towards expert-level audio-visual clinical consultations]() Original publisher: [Read original article]() Published: 2026-08-11T17:04:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Artificial Intelligence](), [Google](), [real-time]() Tags: [ai](), [audio](), [communication](), [health-bioscience](), [machine-intelligence](), [multimodal](), [partnership](), [reasoning](), [research](), [video]() ### AI overview Google Research describes an advance to AMIE, a medical AI system designed for real-time video consultations. In simulated consultations, AMIE demonstrated expert-level performance in a randomized controlled study while integrating spoken history with visual and auditory clinical cues. ### Source excerpt Health & Bioscience ## SymptomAI: Towards a conversational AI agent for everyday symptom assessment DevFeed: [SymptomAI: Towards a conversational AI agent for everyday symptom assessment]() Original publisher: [Read original article]() Published: 2026-07-22T21:32:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [AI Agent](), [Artificial Intelligence](), [Language models](), [Chat Bot](), [Google](), [LLM evaluation / benchmarking]() Tags: [ai](), [ai-agent](), [benchmarking](), [conversational-ai](), [general-science](), [google](), [health-bioscience](), [healthcare](), [language-models](), [natural-language-processing](), [research](), [responsible-ai]() ### AI overview Google Research presents SymptomAI, a study of conversational AI agents for everyday symptom interviews and differential-diagnosis assessment. The national-scale study involved 13,917 participants interacting with one of five Gemini Flash 2.0 SymptomAI agents, with performance compared against clinical assessments for research benchmarking. ### Source excerpt General Science ## Research into how AI can help users understand skin conditions DevFeed: [Research into how AI can help users understand skin conditions]() Original publisher: [Read original article]() Published: 2026-06-12T17:52:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Artificial Intelligence](), [Human-AI evaluation](), [AI Research](), [Google](), [AI Models](), [datasets]() Tags: [ai](), [ai-models](), [datasets](), [google](), [health](), [health-bioscience](), [human-computer-interaction-and-visualization](), [model](), [research](), [validation]() ### AI overview Google Research presents recent and past studies on how AI-powered informational tools may help people understand skin concerns and make better decisions about next steps. The work examines consumer understanding, human factors, model validation, and supporting datasets in dermatology-related health information. ### Source excerpt Health & Bioscience ## Towards passive heart health monitoring via smartphone camera DevFeed: [Towards passive heart health monitoring via smartphone camera]() Original publisher: [Read original article]() Published: 2026-06-04T19:47:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Monitoring](), [webcam](), [dataset](), [Deep learning](), [Google](), [Ground truth / benchmark quality]() Tags: [deep-learning](), [devices](), [google](), [health](), [health-bioscience](), [heart-rate-monitoring](), [human-computer-interaction-and-visualization](), [machine-intelligence](), [model](), [monitoring](), [publication](), [research](), [resource](), [smartphones]() ### AI overview Google Research presents PHRM, a research system that passively estimates heart rate and resting heart rate from facial video captured by a smartphone's front-facing camera during everyday use. The system applies deep learning to video recorded after face unlock events and reports accuracy comparable to electrocardiogram-derived ground truth and wearable trackers. The publication also releases a large, diverse smartphone-video dataset and the pre-trained PHRM-mini model for qualified researchers. ### Source excerpt Health & Bioscience ## Catalyzing scientific impact through global partnerships and open resources DevFeed: [Catalyzing scientific impact through global partnerships and open resources]() Original publisher: [Read original article]() Published: 2026-05-01T16:37:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Open Source](), [datasets](), [Google](), [Transformer architecture]() Tags: [apis](), [architecture](), [australia](), [collaboration](), [community](), [data-mining-modeling](), [developers](), [general-science](), [global](), [google](), [health-bioscience](), [india](), [japan](), [open](), [open-source](), [open-source-models-datasets](), [partnerships](), [publications](), [research](), [science](), [software](), [technology](), [transformer-architecture]() ### AI overview Google Research describes an open-science approach centered on responsible research, open-source software, open-access datasets, and partnerships with scientific organizations and consortia worldwide. It highlights shared technologies and datasets, including Transformer architecture and specialized models used across fields such as medicine, genomics, neuroscience, climate, and energy. ### Source excerpt Data Mining & Modeling ## AI-generated synthetic neurons speed up brain mapping DevFeed: [AI-generated synthetic neurons speed up brain mapping]() Original publisher: [Read original article]() Published: 2026-04-16T12:18:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Artificial Intelligence](), [AI Models](), [Google](), [Point cloud](), [Training AI Models](), [datasets](), [neuron](), [data]() Tags: [3d](), [accelerate](), [ai](), [classification](), [errors](), [general-science](), [generation](), [google](), [health-bioscience](), [iclr](), [iclr-2026](), [images](), [machine-intelligence](), [mapping](), [model](), [models](), [neuron](), [partners](), [research](), [scale](), [science](), [synthetic](), [visualization]() ### AI overview Google Research describes how MoGen generates synthetic neuronal shapes to improve AI models that reconstruct brain wiring maps. Adding synthetic training examples reduced reconstruction errors by 4.4%, potentially saving 157 person-years of manual proofreading for a complete mouse brain. ### Source excerpt General Science ## Google Research at The Check Up: from healthcare innovation to real-world care settings DevFeed: [Google Research at The Check Up: from healthcare innovation to real-world care settings]() Original publisher: [Read original article]() Published: 2026-03-17T19:47:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Google](), [Artificial Intelligence](), [AI Research](), [datasets](), [data](), [Ground truth / benchmark quality]() Tags: [ai](), [ai-research](), [data](), [datasets](), [google](), [health](), [health-bioscience](), [healthcare](), [innovation](), [machine-intelligence](), [research](), [science](), [uk](), [us]() ### AI overview Google Research highlights AI applications in healthcare, including a Personal Health Agent for preventative care, multimodal analysis of wearable data, and diagnostic research for improving breast cancer detection. The article emphasizes collaboration with healthcare professionals and the use of diverse datasets and expert-validated ground truth data. ### Source excerpt Health & Bioscience ## Improving breast cancer screening workflows with machine learning DevFeed: [Improving breast cancer screening workflows with machine learning]() Original publisher: [Read original article]() Published: 2026-03-17T16:57:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Machine learning](), [AI Development](), [Google](), [Deployment]() Tags: [ai](), [artificial-intelligence](), [deployment](), [google](), [health](), [health-bioscience](), [human-computer-interaction-and-visualization](), [machine-learning](), [uk](), [workflows]() ### AI overview Google Research reports on large-scale evaluations of a machine-learning mammography system intended to support breast cancer screening workflows. The studies examine standalone performance, integration into clinical workflows, and use as a second reader alongside human radiologists. ### Source excerpt Health & Bioscience ## Exploring the feasibility of conversational diagnostic AI in a real-world clinical study DevFeed: [Exploring the feasibility of conversational diagnostic AI in a real-world clinical study]() Original publisher: [Read original article]() Published: 2026-03-11T16:58:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Artificial Intelligence](), [Google](), [AI Chat]() Tags: [ai](), [generative-ai](), [google](), [health-bioscience](), [machine-intelligence](), [research]() ### AI overview Google Research presents a prospective, single-center feasibility study evaluating AMIE, a conversational medical AI, for gathering clinical history before ambulatory primary care visits. The study examines safety, practical feasibility, and clinician and patient perceptions in a real-world clinical setting. ### Source excerpt Generative AI ## Collaborating on a nationwide randomized study of AI in real-world virtual care DevFeed: [Collaborating on a nationwide randomized study of AI in real-world virtual care]() Original publisher: [Read original article]() Published: 2026-02-03T18:15:01Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Artificial Intelligence](), [Conversational AI](), [Generative AI](), [systems]() Tags: [ai](), [comparisons](), [conversational-ai](), [generative-ai](), [health](), [health-bioscience](), [healthcare](), [machine-intelligence](), [research](), [testing](), [us]() ### AI overview Google Research and Included Health are launching, pending IRB approval, a prospective nationwide randomized study of conversational AI in real-world virtual care. The study will evaluate safety, utility, and impact at scale, building on earlier research into diagnostic reasoning, physician assistance, and clinical workflows. ### Source excerpt Generative AI ## Unlocking health insights: Estimating advanced walking metrics with smartwatches DevFeed: [Unlocking health insights: Estimating advanced walking metrics with smartwatches]() Original publisher: [Read original article]() Published: 2026-01-15T22:56:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Deep learning](), [model architecture](), [data](), [Google]() Tags: [architecture](), [data](), [deep-learning](), [evaluation](), [google](), [health](), [health-bioscience](), [human-computer-interaction-and-visualization](), [model](), [performance](), [portable](), [smartphones](), [validation]() ### AI overview Google researchers report a large-scale validation study showing that consumer smartwatches can accurately estimate comprehensive spatio-temporal gait metrics, including walking speed, step length, and double support time. They describe a multi-output deep learning model using a temporal convolutional network and smartwatch inertial sensor data, with performance comparable to smartphone-based methods. ### Source excerpt Health & Bioscience ## Next generation medical image interpretation with MedGemma 1.5 and medical speech to text with MedASR DevFeed: [Next generation medical image interpretation with MedGemma 1.5 and medical speech to text with MedASR]() Original publisher: [Read original article]() Published: 2026-01-13T20:57:16Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Medical imaging](), [AI Models](), [asr](), [Generative AI](), [Google](), [hugging face](), [Cloud](), [Kaggle]() Tags: [ai-models](), [asr](), [generative-ai](), [google](), [google-cloud](), [health](), [health-bioscience](), [healthcare](), [hugging-face](), [kaggle](), [machine-intelligence](), [medical-imaging]() ### AI overview Google Research describes MedGemma 1.5 4B, an updated open medical generative AI model with improved support for medical imaging, text, medical records, and 2D images. The article also presents MedASR, an open medical speech-to-text model for dictation that can pair with MedGemma for advanced reasoning. The models are available for research and commercial use through Hugging Face and Vertex AI, with a related medical AI hackathon on Kaggle. ### Source excerpt Generative AI ## Spotlight on innovation: Google-sponsored Data Science for Health Ideathon across Africa DevFeed: [Spotlight on innovation: Google-sponsored Data Science for Health Ideathon across Africa]() Original publisher: [Read original article]() Published: 2025-12-12T10:42:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Google](), [Hackathon](), [Google AI](), [AI Models](), [Generative AI](), [Machine Learning & Artificial Intelligence]() Tags: [2025](), [africa](), [ai](), [ai-models](), [collaboration](), [conferences-events](), [developers](), [generative-ai](), [global](), [google](), [hackathon](), [health](), [health-bioscience](), [mentorship]() ### AI overview Google Research describes an Africa-wide Data Science for Health Ideathon in which researchers and developers used Google's open health AI models to address healthcare challenges. Six finalist teams received mentorship and technical resources, and explored MedGemma, TxGemma, and MedSigLIP for applications ranging from diagnostics to policy frameworks. ### Source excerpt Conferences & Events ## Accelerating the magic cycle of research breakthroughs and real-world applications DevFeed: [Accelerating the magic cycle of research breakthroughs and real-world applications]() Original publisher: [Read original article]() Published: 2025-10-31T07:40:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Earth AI](), [Google](), [Artificial Intelligence](), [LLMs](), [data](), [datasets]() Tags: [climate-sustainability](), [discovery](), [earth-ai](), [generative-ai](), [geospatial](), [google](), [health-bioscience](), [innovation](), [llms](), [models](), [quantum](), [research](), [sustainability]() ### AI overview Google Research describes how advances in AI models, agentic tools, and open platforms are accelerating a cycle between scientific research and real-world applications. The article highlights Earth AI, including geospatial models and an LLM-powered reasoning agent that works across imagery, population, environmental data, and multiple datasets. ### Source excerpt Climate & Sustainability ## How we are building the personal health coach DevFeed: [How we are building the personal health coach]() Original publisher: [Read original article]() Published: 2025-10-27T22:36:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Artificial Intelligence](), [Generative AI](), [Google](), [Time Series](), [data](), [Statistics](), [Android](), [iOS]() Tags: [2025](), [ai](), [android](), [gemini](), [generative-ai](), [google](), [health-bioscience](), [ios](), [preview](), [science](), [statistics](), [time-series]() ### AI overview Google describes a Gemini-powered personal health coach designed to provide personalized, adaptive coaching grounded in science and expert oversight. The optional public preview uses Fitbit data to generate health insights and applies numerical reasoning to physiological time-series data such as sleep and activity. ### Source excerpt Generative AI ## Using AI to identify genetic variants in tumors with DeepSomatic DevFeed: [Using AI to identify genetic variants in tumors with DeepSomatic]() Original publisher: [Read original article]() Published: 2025-10-16T16:33:00Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Artificial Intelligence](), [Google](), [Deep neural networks](), [datasets](), [Machine Learning & Artificial Intelligence]() Tags: [2025](), [ai](), [general-science](), [google](), [health-bioscience](), [machine-learning](), [neural-networks](), [open-source-models-datasets](), [research](), [training]() ### AI overview Google Research presents DeepSomatic, an AI-powered tool that uses convolutional neural networks to identify cancer-related genetic variants in tumor sequencing data. The tool supports major sequencing platforms and sample-processing methods, and its software and training dataset are openly available to researchers. ### Source excerpt General Science