# Healthcare Published articles for Healthcare. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Improving HCLS AI reasoning with open-source agent skills DevFeed: [Improving HCLS AI reasoning with open-source agent skills]() Original publisher: [Read original article]() Author: Michael Hsieh Published: 2026-09-16T19:00:00Z Content type: article Language: en Sources: [Artificial Intelligence]() Topics: [Agent Skills](), [Artificial Intelligence](), [foundation-models](), [Open Source](), [Bioinformatics](), [Medical imaging]() Tags: [agent-skills](), [agents](), [ai](), [ai-agents](), [amazon-bedrock](), [amazon-quick-suite](), [announcements](), [artificial-intelligence](), [foundation-models](), [generative-ai](), [healthcare](), [healthcare-and-life-sciences](), [intermediate-200](), [kiro](), [life-sciences](), [medical-imaging](), [open-source](), [strands-agents]() ### AI overview This post presents 38 open-source agent skills spanning 11 healthcare and life sciences domains. The skills encode domain decision procedures for AI agents, and the reported evaluation found a 70-86% head-to-head win rate over agents without the skills. ### Source excerpt AI agents on foundation models often misapply healthcare and life sciences decision frameworks, citing the right guideline but applying it incorrectly. This post shares 38 open-source agent skills across 11 HCLS domains that close this gap, with installation steps, three worked use cases, and a 410-prompt evaluation showing a 70-86% win rate. ## University of Manchester Uses NVIDIA Earth-2 to Forecast Air Pollution Across the UK DevFeed: [University of Manchester Uses NVIDIA Earth-2 to Forecast Air Pollution Across the UK]() Original publisher: [Read original article]() Author: Isha Salian Published: 2026-09-16T05:00:42Z Content type: article Language: en Sources: [NVIDIA Blog]() Topics: [Artificial Intelligence](), [AI Models](), [Supercomputing](), [DGX Spark](), [Simulation](), [Training AI Models](), [data](), [Inference](), [real-time]() Tags: [ai](), [ai-for-good](), [ai-models](), [climate](), [compute](), [dgx-spark](), [government](), [healthcare](), [inference](), [nvidia](), [open-source](), [real-time](), [science](), [supercomputing](), [training](), [uk]() ### AI overview The University of Manchester is working with NVIDIA to use Earth-2 generative AI models to forecast air pollution across the U.K. The team trained Earth-2 CorrDiff on chemistry-climate simulation data using Isambard-AI, added StormCast for time-dependent forecasts using air-quality observations, and demonstrated workflows on DGX Spark. ### Source excerpt Air pollution is a serious public health risk, contributing to an estimated 30,000 deaths in the U.K. alone last year. Data-driven insights can help -- but computing air quality with traditional chemistry-based models is expensive, which limits how detailed they can be and how regularly they can be run. David Topping, a professor in the [...] ## The 6 best HIPAA-compliant form builders for sensitive information DevFeed: [The 6 best HIPAA-compliant form builders for sensitive information]() Original publisher: [Read original article]() Author: Adam Lehman Published: 2026-09-12T00:00:00Z Content type: comparison Language: en Sources: [Webflow Blog]() Topics: [data](), [data-processing](), [Encryption](), [Software](), [cloud-infrastructure]() Tags: [compliance](), [data](), [encryption](), [enterprise](), [forms](), [healthcare](), [strategy](), [workflows]() ### AI overview A comparison of six HIPAA-compliant form builders for healthcare teams collecting protected health information (PHI). It evaluates Business Associate Agreement requirements, safeguards such as encryption and audit logging, pricing and plans, form capabilities, and suitability for workflows ranging from patient intake to complex clinical questionnaires. ### Source excerpt Compare the 6 best HIPAA-compliant form builders for healthcare teams collecting PHI, from affordable to enterprise options. ## Health Plans: Your BI Tells You MLR Moved. Can Your AI Tell You Why? DevFeed: [Health Plans: Your BI Tells You MLR Moved. Can Your AI Tell You Why?]() Original publisher: [Read original article]() Author: Aaron Zavora; Jonathan Thompson Published: 2026-09-11T18:26:59Z Content type: article Language: en Sources: [Databricks]() Topics: [databricks](), [Conversational AI](), [Artificial Intelligence](), [data]() Tags: [ai](), [conversational-ai](), [dashboards](), [data](), [databricks](), [healthcare](), [healthcare-life-sciences](), [industries](), [metrics]() ### AI overview The article explains how AI can help health plan finance teams move beyond BI dashboards that identify a higher medical loss ratio (MLR) and instead determine the causes and appropriate corrective actions. It describes Databricks and Abacus as combining governed enterprise data with payer-specific data, business context, and operational knowledge, while conversational AI lets finance leaders ask questions in plain language and receive answers more quickly. ### Source excerpt A health plan CFO closes the month after the usual round of extracts, spreadsheets,... ## Figma launches data residency in Japan DevFeed: [Figma launches data residency in Japan]() Original publisher: [Read original article]() Author: Figma Published: 2026-09-11T15:25:00Z Content type: release Language: en Sources: [Figma Blog]() Topics: [Figma](), [data]() Tags: [availability](), [collaboration](), [data](), [data-management](), [enterprise](), [figma](), [financial-services](), [healthcare](), [hosting](), [japan](), [launch](), [product-development](), [public-sector](), [security]() ### AI overview Figma launches data residency in Japan, allowing enterprise customers to host Figma file data domestically. The announcement highlights data protection, security, and data management needs across sectors including the public sector, healthcare, and financial services. ### Source excerpt Figma strengthens data protection and security for enterprise customers with local data hosting. ## Ling 3.0 Flash Sante is now available on AI Gateway for free DevFeed: [Ling 3.0 Flash Sante is now available on AI Gateway for free]() Original publisher: [Read original article]() Author: Jerilyn Zheng Published: 2026-09-04T00:00:00Z Content type: release Language: en Sources: [Vercel News]() Topics: [Artificial Intelligence](), [context window]() Tags: [agentic](), [ai](), [ai-gateway](), [coding](), [context-window](), [free](), [healthcare](), [model](), [retrieval]() ### AI overview Ling 3.0 Flash Sante, a healthcare-focused model from inclusionAI, is available on AI Gateway for free through October 4. It supports medical reasoning, research, evidence retrieval, multi-step healthcare tasks, function calling, and a 256K-token context window. ### Source excerpt Ling 3.0 Flash Sante from inclusionAI is now available on AI Gateway, and free through October 4. Ling 3.0 Flash Sante is the healthcare-focused version of Ling 3.0 Flash. It's built for medical reasoning, research, evidence retrieval, and multi-step healthcare tasks. It has a 256K-token context window, supports function calling, and retains the base model's general reasoning, coding, and agentic capabilities. Choose a model ID based on what should happen after the free period: inclusionai/ling-3.0-flash-sante continues serving requests at standard rates after October 4. inclusionai/ling-3.0-flash-sante-free stops serving requests after October 4. Free requests remain visible in your usage and traces but show a cost of $0. Use the model: Try Ling 3.0 Flash Sante in the model playground, or see the free model page. Read more ## Transfer learning for genomic prediction in underrepresented populations DevFeed: [Transfer learning for genomic prediction in underrepresented populations]() Original publisher: [Read original article]() Published: 2026-09-03T18:20:31Z Content type: article Language: en Sources: [The latest research from Google]() Topics: [Fine-tuning](), [Model Development](), [Google](), [datasets]() Tags: [datasets](), [evaluation](), [general-science](), [google](), [healthcare](), [learning](), [machine-intelligence](), [research](), [training]() ### AI overview Google Research evaluates transfer learning for polygenic risk-score prediction across populations. European-cohort transfer learning improves prediction for small underrepresented target cohorts but can reduce accuracy as target cohorts grow, particularly for population-specific traits. ### Source excerpt General Science ## Healthcare organizations can now connect EHR and additional industry data to ChatGPT DevFeed: [Healthcare organizations can now connect EHR and additional industry data to ChatGPT]() Original publisher: [Read original article]() Published: 2026-09-01T12:00:00Z Content type: news Language: en Sources: [OpenAI News]() Topics: [data](), [datasets]() Tags: [ai](), [chatgpt](), [compliance](), [data](), [datasets](), [healthcare](), [integration](), [product](), [workflow]() ### AI overview ChatGPT for Healthcare can connect authorized Epic patient context and structured public healthcare data, helping healthcare teams review records, research, and official sources within governed workflows. ### Source excerpt ChatGPT can now connect to trusted healthcare data, helping clinicians securely access patient context, medical research, and more. ## Why Smart Professionals Use Personas to Get Ahead (And You Should Too) DevFeed: [Why Smart Professionals Use Personas to Get Ahead (And You Should Too)]() Original publisher: [Read original article]() Author: James Newhook Published: 2026-08-27T05:00:00Z Content type: article Language: en Sources: [UX Daily - User Experience Daily]() Topics: [User experience (UX)](), [User Experience]() Tags: [career](), [healthcare](), [user-experience](), [ux](), [ux-design]() ### AI overview The article explains how user personas help professionals turn research into specific, human-centered representations of users. It presents personas as a practical UX design tool for creating focused products, services, and experiences, improving understanding of customer needs, and aligning teams. ### Source excerpt Imagine your next product launch soaring beyond expectations. Your customers raving about experiences crafted just for them. Your ideas finally connecting with the people who matter most. This isn't wishful thinking--it's what happens when you master personas, user experience (UX) design's secret weapon. Whether you're an executive tired of guessing what customers want, a healthcare administrator struggling with patient satisfaction, or an entrepreneur desperate to stand out, personas give you the power to stop designing for everyone (and pleasing no one). Instead, you'll create laser-focused solutions that make people feel understood and transform your career from constantly guessing to conf... ## Healthcare UX: Design that Saves Lives DevFeed: [Healthcare UX: Design that Saves Lives]() Original publisher: [Read original article]() Author: Laia Tremosa Published: 2026-08-24T16:00:00Z Content type: article Language: en Sources: [UX Daily - User Experience Daily]() Topics: [User experience (UX)](), [User interface design](), [Usability](), [Artificial Intelligence](), [Virtual reality]() Tags: [artificial-intelligence](), [design](), [health-tech](), [healthcare](), [ui-design](), [usability](), [ux](), [ux-design]() ### AI overview This article explains why UX design is especially consequential in healthcare, where poorly designed interfaces can contribute to dangerous mistakes. It discusses healthcare products and services, the growth of digital health and telemedicine, and the role of UX/UI design in improving engagement, usability and retention. It also notes how emerging technologies such as virtual reality and artificial intelligence may shape healthcare design. ### Source excerpt UX (user experience) design has the potential to improve people's everyday lives. The stakes are even higher if you work as a UX designer in the healthcare industry. The health-tech sector is among the fastest-growing in the world, with expected revenue of USD 1,305.1 billion in 2030, according to Grand View Research. As a UX designer, you have the opportunity to help define the future of healthcare. Let's look at the role of UX design within the healthcare field, the impact of the COVID-19 pandemic on digital health solutions, the aging population phenomenon, and the pivotal role of design for emerging technologies such as Virtual Reality (VR) and Artificial Intelligence (AI).Most digital h... ## The search multiplier: Driving revenue, productivity, and AI at scale DevFeed: [The search multiplier: Driving revenue, productivity, and AI at scale]() Original publisher: [Read original article]() Author: Nicole Volk Published: 2026-08-20T00:00:00Z Content type: article Language: en Sources: [Elastic Blog - Elasticsearch, Kibana, and ELK Stack]() Topics: [elasticsearch](), [AI search](), [AI Infrastructure](), [Generative AI](), [idc](), [Resilience]() Tags: [accelerate](), [agentic-ai-cloud-search-context-engineering-customer-experience-deployment-end-user-experience](), [ai](), [ai-infrastructure](), [analysis](), [business-value](), [customer-story-elasticsearch-workplace-search](), [elasticsearch](), [elasticsearch-platform](), [financial-services](), [government](), [healthcare](), [resilience](), [retail](), [retrieval](), [search]() ### AI overview An IDC study of 11 large enterprises reports that the Elasticsearch Platform, used as a search and retrieval foundation, helped organizations deliver AI products faster while improving revenue, productivity, search relevance, and operational resilience. The study reports a 517% three-year ROI, $13.4 million in annual benefits per organization, and an 11-month payback period. ### Source excerpt An independent IDC study found organizations deploying the Elasticsearch Platform for enterprise search and agentic AI deliver AI products faster, drive higher revenue, boost productivity, and strengthen operational resilience across the business. ## How Clario technology detects PHI/PII in DICOM images using Amazon Bedrock DevFeed: [How Clario technology detects PHI/PII in DICOM images using Amazon Bedrock]() Original publisher: [Read original article]() Author: Alex Boudreau Published: 2026-08-19T14:29:31Z Content type: article Language: en Sources: [AWS Architecture Blog]() Topics: [Amazon Bedrock](), [Medical imaging](), [Amazon Textract](), [Amazon Web Services](), [data]() Tags: [amazon](), [amazon-bedrock](), [amazon-textract](), [analysis](), [architecture](), [aws](), [customer-solutions](), [data](), [healthcare](), [images](), [medical-imaging](), [pii](), [technology](), [workflow]() ### AI overview Clario uses Amazon Bedrock and Amazon Textract to automate the detection of PHI and PII in DICOM image slices from clinical trials, including information stored in metadata and text embedded in image pixels. ### Source excerpt Clario, part of Thermo Fisher Scientific, uses Amazon Bedrock and Amazon Textract to automatically detect protected health information (PHI) and personally identifiable information (PII) across thousands of DICOM image slices in clinical trials, covering both metadata tags and text burned into the image pixels. ## India's Internet ecosystem in 2026: Growth, resilience, and the road ahead DevFeed: [India's Internet ecosystem in 2026: Growth, resilience, and the road ahead]() Original publisher: [Read original article]() Author: Samantha Douglas Published: 2026-08-17T01:30:48Z Content type: article Language: en Sources: [APNIC Blog]() Topics: [Internet](), [Networks](), [Resilience](), [5G](), [cloud-infrastructure]() Tags: [5g](), [apnic-62](), [community](), [development](), [digital-platforms](), [digital-transformation](), [economy-report](), [education](), [finance](), [global](), [government](), [growth](), [healthcare](), [india](), [infrastructure](), [internet](), [ipv6](), [measurement](), [mobile](), [networks](), [resilience](), [scale]() ### AI overview India's Internet ecosystem has expanded through affordable mobile broadband, major digital infrastructure investment, and strong IPv6 adoption. The article examines the shift from rapid growth toward resilient, secure, and inclusive connectivity, while highlighting persistent rural and remote access gaps and the continued expansion of 4G, 5G, and fixed broadband. ### Source excerpt India has built one of the world's largest Internet ecosystems through affordable mobile broadband, digital infrastructure investment, and IPv6 leadership. As it prepares to host APNIC 62, the challenge is ensuring connectivity remains resilient, secure, and inclusive. ## A new benchmark for evaluating patient-facing health AI agents DevFeed: [A new benchmark for evaluating patient-facing health AI agents]() Original publisher: [Read original article]() Author: Korosh Vatanparvar; Ashutosh Joshi Published: 2026-07-29T15:16:52Z Content type: article Language: en Sources: [Amazon Science homepage]() Topics: [AI Bots]() Tags: [agentic-ai](), [agents](), [ai](), [benchmark](), [conversational-ai](), [evaluation](), [foundation-models](), [health](), [healthcare](), [safety](), [synthetic]() ### AI overview The article introduces PatientAgentBench, a clinician-vetted benchmark for evaluating the safety and task performance of patient-facing healthcare AI agents in realistic, multiturn conversations. ### Source excerpt PatientAgentBench generates a synthetic patient health record, a realistic clinical vignette, and a patient agent that converses with the AI system under evaluation, to capture what a patient-facing agent actually has to do. ## Developing Healthcare Robotics with GPU-Native Medical Physics Simulation DevFeed: [Developing Healthcare Robotics with GPU-Native Medical Physics Simulation]() Original publisher: [Read original article]() Author: Michelle Horton Published: 2026-07-28T20:49:21Z Content type: article Language: en Sources: [NVIDIA Developer](), [NVIDIA Technical Blog]() Topics: [Isaac for Healthcare](), [Robotics](), [Reinforcement learning](), [GPU](), [datasets](), [Medical imaging](), [Cosmos](), [Open Source](), [real-time](), [Nvidia]() Tags: [agentic-ai-generative-ai](), [data](), [datasets](), [featured](), [gpu](), [healthcare](), [isaac](), [isaac-for-healthcare](), [isaac-sim](), [medical-imaging](), [nvidia](), [open-source](), [physical-ai](), [physics](), [real-time](), [reinforcement-learning](), [robotics](), [simulation-modeling-design](), [warp](), [world-model]() ### AI overview The article presents NVIDIA's open source, GPU-accelerated Medical Physics Simulation framework for healthcare robotics. It addresses limited medical robotics data, poor generalization, and slow development by enabling anatomical digital twins, device-anatomy and medical imaging simulation, and GPU-scale reinforcement learning within Isaac for Healthcare, Isaac Sim, and Isaac Lab. ### Source excerpt Unlike autonomous driving or industrial robotics, healthcare robotics can't rely on internet-scale data collection or unlimited real-world experimentation.... ## Mastering the 50-state AI maze: A platform strategy for sovereignty DevFeed: [Mastering the 50-state AI maze: A platform strategy for sovereignty]() Original publisher: [Read original article]() Author: Marc Mangus Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [AI Strategy](), [Artificial Intelligence](), [Generative AI](), [Azure](), [Microsoft](), [cloud-infrastructure]() Tags: [ai](), [azure](), [compliance](), [developer](), [healthcare](), [microsoft](), [platform](), [policy](), [regulatory](), [strategy](), [vendor-lock-in]() ### AI overview The article argues that healthcare organizations need platform sovereignty to manage conflicting AI regulations across U.S. states. It presents policy-as-code, golden paths, and internal developer portals as scalable defenses against compliance risk and vendor lock-in, illustrated by a health insurer's costly replacement of Microsoft AI and Azure-based services. ### Source excerpt As state AI laws collide, healthcare organizations face mounting compliance risk and vendor lock-in. Learn why platform sovereignty--policy-as-code, golden paths, and internal developer portals--is the only scalable defense against a 50-state regulatory civil war ## How TEFCA is impacting platform engineering in Healthcare DevFeed: [How TEFCA is impacting platform engineering in Healthcare]() Original publisher: [Read original article]() Author: Marc Mangus Published: 2026-07-23T05:40:01Z Content type: opinion Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [Architecture & Design](), [data-governance](), [API](), [Orchestration]() Tags: [api](), [architecture](), [compliance](), [engineering](), [governance](), [healthcare](), [orchestration](), [platform](), [platform-engineering](), [policy](), [regulatory]() ### AI overview The article argues that TEFCA is making healthcare data-exchange compliance effectively mandatory, creating substantial platform-engineering challenges. Teams must address consent management, data governance, purpose-of-use restrictions, audit trails, varying state privacy laws, and differing QHIN interpretations. It advocates composable architectures and policy-as-code approaches to manage this complexity at scale. ### Source excerpt TEFCA is turning "voluntary" healthcare data exchange into de facto mandatory compliance - forcing platform teams to rebuild consent, governance, and multi-state policy controls. Here's how to scale it with policy-as-code. ## Do no harm: Implementing AI responsibly in the healthcare industry DevFeed: [Do no harm: Implementing AI responsibly in the healthcare industry]() Original publisher: [Read original article]() Author: Marc Mangus Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Artificial Intelligence](), [Platform Engineering](), [Security](), [Deployment]() Tags: [ai](), [article](), [ethics](), [governance](), [healthcare](), [platform-engineering](), [privacy](), [regulatory](), [security]() ### AI overview This article explains how platform engineering can support responsible AI adoption in healthcare by embedding safety, ethics, governance, security, and regulatory compliance into development and deployment workflows. It highlights risks including bias, unequal access to care, harmful outcomes, insecure AI-generated code, and inadequate representation in training data. ### Source excerpt AI is transforming healthcare, but ethical, security, and privacy risks demand strong governance. Platform engineering ensures safe, transparent, and compliant AI deployment that truly "does no harm." ## 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 ## Forward Deployed Engineering Faces Rapid Expansion and Talent Constraints DevFeed: [Forward Deployed Engineering Faces Rapid Expansion and Talent Constraints]() Original publisher: [Read original article]() Author: SeattleDataGuy Published: 2026-07-06T14:28:59Z Content type: opinion Language: en Sources: [SeattleDataGuy's Newsletter]() Topics: [Artificial Intelligence](), [Microsoft](), [Amazon Web Services]() Tags: [ai](), [aws](), [banking](), [engineering](), [enterprise](), [healthcare](), [microsoft]() ### AI overview The article examines the rapid growth of Forward Deployed Engineering (FDE) organizations as Microsoft and AWS invest heavily in the model. It argues that AI vendors need FDEs to help enterprises apply AI beyond chat, combining technical expertise with knowledge of domains such as healthcare and banking. The author predicts the role may eventually resemble systems integrators or contractors and become less distinct as adoption expands. ### Source excerpt But AI vendors need enterprise adoption at any cost ## MosaicLeaks: Can your research agent keep a secret? DevFeed: [MosaicLeaks: Can your research agent keep a secret?]() Original publisher: [Read original article]() Author: Alexander Gurung; Rafael Pardinas Published: 2026-06-18T18:13:13Z Content type: article Language: en Sources: [Hugging Face - Blog]() Topics: [Security](), [Machine Learning, Security Attacks]() Tags: [agent](), [agents](), [cloud](), [external](), [healthcare](), [infrastructure](), [local](), [migration](), [models](), [privacy](), [research](), [retrieval](), [rl](), [security](), [tools](), [training]() ### AI overview MosaicLeaks examine how deep-research agents can expose private enterprise information through their external web queries. The proposed Privacy-Aware Deep Research training method improves strict multi-hop task success while substantially reducing answer and full-information leakage. ### Source excerpt Deep research agents increasingly combine private local documents with external tools like web retrieval, creating a privacy risk: an agent's external queries may leak sensitive information. MosaicLeaks proposes a new deep-research task with multi-hop questions that interleave public and private information. Across the models we tested, agents frequently leaked private information, and training only for task performance made it worse. ## Introducing OpenAI for Singapore DevFeed: [Introducing OpenAI for Singapore]() Original publisher: [Read original article]() Published: 2026-05-19T20:30:00Z Content type: news Language: en Sources: [OpenAI News]() Topics: [OpenAI](), [Artificial Intelligence](), [AI Strategy](), [Frontier AI](), [Deployment]() Tags: [ai-strategy](), [applied-ai](), [finance](), [frontier-ai](), [global-affairs](), [healthcare](), [infrastructure](), [net](), [openai](), [partnership]() ### AI overview OpenAI is launching OpenAI for Singapore, a partnership with Singapore's Ministry of Digital Development and Information backed by more than S$300 million. The initiative will support frontier AI deployment, develop local talent, and expand access to AI across organisations, businesses, and public services. ### Source excerpt OpenAI for Singapore launches a multi-year AI partnership to expand deployment, build local talent, and support businesses and public services with AI. ## Strengthening Singapore's AI Future: A New National Partnership DevFeed: [Strengthening Singapore's AI Future: A New National Partnership]() Original publisher: [Read original article]() Author: Google DeepMind Published: 2026-05-16T09:13:34Z Content type: article Language: en Sources: [Google DeepMind News]() Topics: [Frontier AI](), [Google](), [AI Strategy](), [Artificial Intelligence](), [AI research agents]() Tags: [agents](), [ai](), [ai-agents](), [business](), [education](), [frontier-ai](), [google](), [government](), [growth](), [health](), [healthcare](), [innovation](), [partnership](), [partnerships](), [research](), [responsibility-safety](), [science](), [strategy]() ### AI overview Google DeepMind and Singapore are launching national partnership programmes applying frontier AI to healthcare, life sciences, education, scientific research, and workforce development. The initiative aims to support responsible AI deployment, public-sector transformation, and economic growth. ### Source excerpt Google DeepMind and Singapore partner to apply frontier AI to address complex challenges across health, education, and sustainability and more. ## Enabling a new model for healthcare with AI co-clinician DevFeed: [Enabling a new model for healthcare with AI co-clinician]() Original publisher: [Read original article]() Author: Alan Karthikesalingam; Vivek Natarajan; Pushmeet Kohli Published: 2026-04-30T12:14:15Z Content type: article Language: en Sources: [Google DeepMind News]() Topics: [Artificial Intelligence](), [Google](), [Cloud]() Tags: [agent](), [ai](), [architecture](), [australia](), [engineering](), [evaluation](), [google](), [google-cloud](), [healthcare](), [india](), [new-zealand](), [partners](), [research](), [retrieval](), [science](), [standards](), [us]() ### AI overview Google DeepMind describes research into an AI co-clinician for AI-augmented healthcare. The system uses a dual-agent architecture in which a Planner monitors a Talker agent for clinical safety, while retrieval evidence is verified and citations are checked. ### Source excerpt Researching the path to AI-augmented care and development of an AI co-clinician. [Next page]()