AI in Healthcare News

PwC Report: AI Making Medical Bills Higher

According to a PwC report, AI is driving up medical bills rather than reducing them. The report's findings highlight the complex economic effects of AI in healthcare.

Reddit user shares how ChatGPT helped with mental health struggles

A Reddit user recounts a decade-long struggle with depression and how ChatGPT provided meaningful support, contrasting with a widely reported case of misuse for suicide planning. The post highlights the dual nature of AI tools in mental health contexts.

Abridge inks deals with NVIDIA and Eli Lilly

Healthcare AI company Abridge announced partnerships with NVIDIA to build a foundation model for clinical conversations and with Eli Lilly. The company plans to expand beyond clinical documentation into hospital billing and operations.

Ilant Health Raises $15M for AI-Supported Obesity Care

Ilant Health raised $15M to deliver AI-supported precision obesity care. The platform aims to replace fragmented interventions with continuously adapted treatment pathways.

MONAI Tutorial: 3D Spleen Segmentation with UNet

Tutorial walks through building a 3D spleen segmentation pipeline using MONAI and UNet on the Medical Segmentation Decathlon Task09 dataset. Covers orientation alignment, voxel-spacing normalization, and other medical imaging transformations. Code included for training and inference.

Google Research explores AI to help users understand skin conditions

Google Research blog details a project using AI to help users interpret skin conditions from images. The work focuses on improving accessibility and accuracy of dermatological understanding.

General-purpose LLMs beat specialized clinical AI tools on medical benchmarks

Frontier LLMs outperformed specialized clinical AI tools in all three evaluations: medical knowledge, clinician alignment, and real-world clinical queries. Clinical AI tools performed comparably to auto-enabled Google Search AI Overview, despite 65% of doctors using OpenEvidence.

Trust is key to healthcare professionals' AI adoption, Scale AI report finds

Khal Ismail's BCI headphone aims to read 10 thoughts

AMA and lawmakers push back on AI care denials

The American Medical Association and lawmakers are opposing the use of AI algorithms to deny healthcare coverage. The pushback highlights concerns over transparency and patient rights.

From Fragmented Data to Actionable Intelligence

Paul Brockington, VP of Integrations at ONCare Alliance, discusses how AI and modern tools help healthcare providers turn fragmented data into actionable insights for business and clinical decisions. The interview covers challenges of data silos and the potential for AI to enable real-time, integrated analytics.

Deregulation enables AI innovation but adds liability risk

Video from HIMSS discusses how deregulation allows AI innovation in healthcare but increases liability risk. References upcoming HIMSS AI Executive Leadership Summit (June 24, 2026, Boston) and the AI in Healthcare Forum.

Four AI scribe adoption scenarios analyzed

AI scribes, which convert patient-doctor conversations into electronic medical records, have seen rapid adoption in the past 1-2 years. The article analyzes four potential adoption scenarios for this technology.

New methods improve respiratory sound classification

Lung-SRAD uses dual-axis patch-mix contrastive learning and spectral-aware regularization. QLung introduces quality-adaptive angular margin learning to improve feature generalization.

Sepsis algorithm should not require a time machine

STAT article critiques sepsis prediction algorithms for using retrospective data, arguing they should only rely on data available at the point of care. The piece highlights common data leakage pitfalls in healthcare AI development.

Numan's AI health coach Nu built with LangGraph, focuses on safety

Numan built Nu, an AI health coach using LangGraph, operating safely outside medical device regulation. The system uses agent evaluations and automated improvement loops for compliance and quality.

NVIDIA GTC 2026 healthcare address highlights AI transformation

Kimberly Powell, VP of Healthcare at NVIDIA, presented on how AI, accelerated computing, and robotics are driving a once-in-a-generation transformation in healthcare. She covered open foundation models, agentic AI, and physical AI.

Rad AI expands partnership with Yale New Haven Health System

Rad AI extends partnership with Yale New Haven Health System to deploy its generative AI reporting technology across the health system's imaging network. Dr. Elizabeth Bergey noted Yale was Rad AI's first big academic site.

Philips exec: AI in health care 'barely scratching the surface'

Jeff DiLullo, CEO of Philips North America, said AI adoption in healthcare is still in early stages. He discussed practical applications and challenges in a Bloomberg interview.

AI research deciphers cell behavior behind varied cancer drug response

NVIDIA launches tool for clinical ASR evaluation with Nemotron Speech

The tool uses Agent Skills and NVIDIA Nemotron Speech to evaluate clinical ASR models, addressing difficulties with medical terminology. It aims to speed up evaluation and improve recognition of drug names and clinical terms.

Over 40% of clinicians in India now use AI

A new Elsevier report shows over 40% of clinicians in India use AI in their work, up from 12%. The article explores the implications for healthcare delivery and trust in AI platforms.

Triomics raises $22M for oncology AI platform

Triomics, an oncology AI company helping cancer centers manage clinical information, raised $22 million in Series B funding led by Battery Ventures. The round will scale its platform across cancer centers nationwide and deepen life sciences partnerships.

Developer fine-tunes NeuroBait model for ADHD brain dopamine

A Hugging Face blog post details a fine-tuned model called NeuroBait designed to spark dopamine responses for ADHD brains. The project was created as part of a build-small hackathon.

Stanford HAI hosts 2026 AI for Mental Health Symposium

The symposium on June 8, 2026, featured sessions on academic research, industry deployment, and a keynote panel. Speakers included Stanford leaders and industry experts discussing responsible AI for psychiatric care.

Study: AI most used for therapy and emotional support

Survey: small practices embrace AI in healthcare

A guest article by Chris Knotts cites athenahealth's 2025 Physician Sentiment survey showing increased AI adoption in small practices. The shift is from hype to practical deployment, with focus on administrative and clinical workflows.

AI model provides brain health insights from MRI scans

The AI model, demonstrated at HIMSS AI Executive Leadership Summit, offers brain health insights from MRI scans. No further details on accuracy or availability were provided.

NHS England scales Microsoft 365 Copilot to over 500,000 staff

34% of patients would allow AI assistant to read full medical record

A survey found 34% of patients would let an AI assistant access their entire medical record. Meanwhile, 74% of clinicians worry that over-reliance on AI will erode their skills.

AI Executive Leadership Summit in Boston June 2026

HIMSS will host the AI Executive Leadership Summit on June 24, 2026, in Boston. The one-day event will be followed by the AI in Healthcare Forum.

Owkin and Sanofi expand AI collaboration for drug development agents

The multi-year agreement will co-develop AI-enabled biopharma agents for drug R&D. Owkin will lead development of AI agents purpose-built for Sanofi's research pipeline.

Commure raises $70M at $7B valuation to transform healthcare with AI

The round was led by General Catalyst with participation from Sequoia Capital and Morgan Stanley. Commure's AI platform aims to digitize and streamline healthcare workflows.

TopoPult-SSL segments meibomian glands without dense masks

The method uses weak clinical priors like eyelid outlines and Pult grades, combined with self-distillation, to enable cross-device gland segmentation. It addresses domain shifts across new clinical imaging devices where dense gland masks are expensive.

PSEBench evaluates LLMs for patient safety triage

PSEBench is a benchmark designed to evaluate LLMs on patient safety event triage, a high-stakes clinical task. It tests whether LLMs can correctly determine reportability under jurisdiction-specific policies.

Noise-Aware Visual Learning for Med-VQA

The paper proposes a noise-aware visual representation learning method for medical visual question answering (Med-VQA). It improves performance on standard benchmarks by addressing noise in medical images.

InfoShield: Privacy-preserving speech representations for mental health screening

The method aims to enable scalable depression detection while protecting demographic privacy via information-theoretic optimization. It removes demographic information from speech representations while retaining clinical clues.

Paper restores 3D retinal microvasculature in OCT angiography

The paper introduces a method for three-dimensional restoration of retinal microvasculature from optical coherence tomographic angiography (OCTA) images. It aims to improve reliable quantification of blood flow and areas of nonperfusion.

FiLM-Based Speaker Conditioning of a SpeechLLM for Pathological Speech Recognition

The paper applies Feature-wise Linear Modulation (FiLM) to condition a SpeechLLM for pathological speech recognition, targeting the challenge of ASR for neurological conditions. The method aims to improve performance on non-standard speech patterns.

AI vs headache specialists for clinical literature summarization

Study compares AI systems against ten headache specialists for summarizing clinical literature. Evaluation includes critical assessment of accuracy and efficiency from a team of researchers.

Cross-linguistic model for Alzheimer's detection from speech proposed

A new approach using transfer learning enables multilingual Alzheimer's disease detection from speech, reducing the need for language-specific model training. The paper explores cross-linguistic transfer to improve detection across languages.

Severity-Aware Curriculum Learning with Multi-Model Response Selection for Medical Text

The paper introduces a severity-aware curriculum learning approach combined with multi-model response selection to improve LLM performance in medical text generation for telehealth. Existing LLMs struggle with consistent contextually appropriate responses; this method addresses varying query severity.

ORACLE-CT: Anatomy-aware pooling for CT classification

The paper proposes ORACLE-CT, a method using anatomy-aware support pooling to classify abdominal CT scans, addressing the challenge of organ-specific diagnostic evidence in large 3D volumes. It aggregates features from relevant anatomical compartments learned via a support pooling mechanism.

LightVesselNet: sub-100K parameter model for retinal vessel segmentation

LightVesselNet achieves retinal blood vessel segmentation with fewer than 100K parameters, enabling deployment on resource-constrained devices. The model aids in early detection of diabetic retinopathy and glaucoma.

Deep learning model grades AMD severity using OCT and OCTA

Study uses 271 participants aged 50+ to develop deep learning models for automated AMD staging from OCT and OCT angiography data. Models aim to improve grading consistency and efficiency.

New stress test evaluates safety of ambient clinical scribes

Paper proposes a paired acoustic stress test to evaluate ambient clinical scribes beyond traditional Word Error Rate, which masks systemic safety degradation. The test aims to systematically assess safety of these systems.

Interpretable AI for osteoarthritis structure-pain studies from OAI

Framework combines deep learning-based MOAKS prediction with interpretable statistical modeling to analyze structure-pain relationships. Uses longitudinal data from the Osteoarthritis Initiative (OAI) to scale the study.

GRPO with variance-aware rubric rewards boosts heart-focused medical QA

The paper introduces variance-aware rubric rewards with GRPO to improve LLM accuracy on cardiology-related medical questions, achieving significant gains over standard supervised fine-tuning. The method addresses both answer correctness and confidence calibration without requiring additional annotated data.

Meta AI chief sees opportunity in models giving health advice

Meta AI chief Yann LeCun says he sees opportunity for AI models to give health advice. Bloomberg reports the stance as Meta expands its AI focus into healthcare.

SS Innovations explores flying surgical robot concept

CEO Dr. Sudhir Srivastava aims for a functional flying surgical robot by mid-2026. The Vimana Aero concept would combine drone mobility with teleoperated surgery for remote and battlefield care.

Wolters Kluwer, OpenAI expand enterprise AI partnership

The expanded partnership aims to integrate generative AI into professional workflows across sectors including healthcare. Wolters Kluwer provides information services for legal, tax, and health professionals.

Codex Helps Amgen Focus on Patients

The video features Amgen's Sean Bruich highlighting how Codex automates tedious coding tasks, allowing scientists to focus on patient care. It showcases Codex's role in accelerating biotech research.

Podcast features AI tools for solopreneurs, therapy, and science

The Cognitive Revolution podcast interviews founders of AI tools for solopreneurs, mental health, and scientific research. Guests include Hooman Radfar (Collective), Taras Pohrebniak (ElomiaHealth), and Peter Jansen (Allen AI).

Century Health raises $5M seed, achieves 97% accuracy in clinical data

The round was led by Origin Ventures with participation from several other investors. The Century Health Abstraction & Retrieval Model (CHARM) has achieved 97% accuracy compared to clinical expert judgment.

8 examples of AI's current capabilities in healthcare

The article highlights eight real-world applications of AI in healthcare, from addressing provider shortages to improving patient engagement. It provides an overview of current AI uses across the medical field.

Implicit Fuzzification via noise injection improves medical segmentation

The method uses bounded noise injection during training to address boundary ambiguity in medical image segmentation. Evaluations on medical datasets show improved robustness compared to standard U-Net models.

Radiomic feature selection via deep neural network gradient loss for lung cancer detection

Proposes a radiomic feature selection method using gradient loss from a deep neural network to classify lung cancer stages. Addresses high-dimensional, low-sample radiomics datasets. Evaluated on lung cancer imaging data.

Evaluating LLM decision-making in OTC dosing QA

Study evaluates LLMs on over-the-counter medication dosing questions, testing their ability to handle temporal uncertainty and safety. The work highlights risks of relying on LLMs for everyday health decisions.

Motion-Guided Causal Disentanglement for Cardiac MRI

Paper proposes a motion-guided causal disentanglement method for robust multi-view cardiac MRI diagnosis. The approach uses transformer-based models to capture complementary anatomical information from different views.

Paper proposes latent-space motion tracking for real-time 3D MRI

A new prospective reconstruction method uses latent-space motion tracking to enable dynamic 3D MRI from a single measurement. The approach aims to improve motion estimation accuracy for applications like MRI-guided radiotherapy.

Study examines feasibility of DNN-based speech enhancement on FPGA for hearing aids

Paper characterizes the latency and power gap between DNN-based speech enhancement and hearing aid constraints. Lightweight models for speech separation and denoising are deployed on embedded FPGA.

Large study finds RAG may not improve biomedical QA

Study of retrieval-augmented generation for medical question answering shows retrieval does not boost accuracy and can even hurt. Contradicts prior claims of substantial gains.

LLM counseling framework uses strategic client simulation

The paper identifies a 'counselor-following' phenomenon in existing LLM counseling benchmarks. It introduces a new framework and benchmark that simulates less cooperative clients for more realistic evaluation.

MCP-based biomedical agent system for graph planning

arXiv paper proposes a biomedical agent system using MCP for heterogeneous tool integration and graph-based planning. The system aims to overcome bottlenecks in bioinformatics tool interfaces and execution environments.

Differentiable Auditory Loop framework for hyper-personalized hearing aids

The paper presents DAL, an ML framework for hearing aids that learns personalized auditory processing via differentiable signal processing. It aims to outperform traditional fixed amplification in complex multi-speaker environments.

ADAPTOOD: Uncertainty-aware fine-tuning for ECG time series

ADAPTOOD proposes uncertainty-aware fine-tuning to enhance out-of-distribution detection in ECG time series models. The approach addresses performance issues when annotated data is limited.

Explainable ML model detects Alzheimer's from clinical biomarkers

The study uses explainable machine learning for multi-class classification (normal, mild cognitive impairment, Alzheimer's) from clinical biomarkers in the ADNI dataset. It aims to improve early detection accuracy and interpretability.

SANE: LLM method for natural-language querying of biological data

The paper introduces SANE, a schema-aware approach that uses LLMs to translate natural-language questions into SQL queries for high-throughput microscopy datasets. It aims to make biological data accessible without SQL expertise.

New 3D model characterizes kidney lesions from CT scans

Reformulates kidney CT characterization as per-lesion set-prediction task, predicting type, size, enhancement, and attenuation for each lesion. The multi-granularity approach captures lesion-level details beyond patient- or organ-level predictions.

XSSR: Cross-Domain Self-Supervised Selection for Medical Image Annotation

XSSR introduces a cross-domain self-supervised representative selection method to reduce annotation costs for medical image segmentation. It selects the most informative samples from the target domain without requiring labels, addressing domain shifts due to differences in imaging equipment or clinical sites.

Purrble robot improves emotion regulation in LGBTQ+ youth at risk of self-harm

In a randomized controlled trial, LGBTQ+ youth at risk of self-harm who used Purrble, a socially assistive tactile robot, showed improvements in emotion regulation. The robot was integrated into safety planning.

AccurKardia receives patent for AI-ECG cardiac amyloidosis detection

AccurKardia granted U.S. patent for ML-based system to detect cardiac amyloidosis from standard 12-lead ECG. Patent positions company to expand investigational AI-ECG pipeline into disease often delayed in diagnosis.

Microsoft, Mayo Clinic partner to develop frontier AI model for healthcare

Microsoft and Mayo Clinic announced a partnership to develop a frontier AI model for healthcare, owned by Mayo Clinic. The model will combine Mayo's clinical expertise with Microsoft's technologies.

Beyond the screen: How ambient AI is changing the exam room

Ambient AI listens to patient-clinician conversations and automatically generates clinical notes, reducing the time physicians spend on screens. The technology allows doctors to focus more on patients during appointments.

AI finds revenue leaks hidden in documentation

AI system can identify revenue leakage from healthcare documentation. HIMSS will host events in Boston on June 24-26, 2026 to discuss AI in healthcare.

Omega Healthcare CEO: AI RCM needs more than good tech

Anurag Mehta, CEO of Omega Healthcare, discusses how hospitals must consider unique data and population factors when deploying AI for revenue cycle management. HIMSS will host an AI Executive Leadership Summit on June 24, followed by an AI in Healthcare Forum on June 25-26, both in Boston.

HSCC releases cybersecurity guide for healthcare AI

The Healthcare and Public Health Sector Coordinating Council (HSCC) released a new guide addressing cybersecurity risks specific to healthcare AI. The guide covers clinical and operational use cases and aims to help provider organizations establish effective AI cybersecurity governance beyond existing regulations.

Stem-cell microrobots reconnect severed spinal cords in mice

ChristBERT: domain-specific BERT for German medical NLP

Introduces ChristBERT, a BERT model pre-trained on German clinical and biomedical text for medical NLP tasks. Aims to overcome limitations of older architectures and restricted training data in German biomedical language models.

ClinicalMC benchmark evaluates LLMs on multi-course clinical decisions

ClinicalMC is a new benchmark designed to assess LLMs on multi-course clinical decision-making tasks. It includes diverse patient cases and evaluates models across multiple treatment stages.

Graph Mamba Survival Analysis for Whole Slide Images

Paper proposes Graph Mamba Survival Analysis (GMSA) with topology-aware ordering for patient prognosis from Whole Slide Images. The method combines Graph Neural Networks and State Space Models to capture long-range dependencies in computational pathology, addressing challenges of high resolution and spatial irregularity.

Large AI Models in Dental Healthcare: From General-Purpose to Domain-Specific

Oral diseases affect nearly 3.5 billion people worldwide. The survey compares language-generative, vision-language, and domain-specific large AI models for dental clinical applications.

MedCUA-Bench: A Screenshot-Only Benchmark for Clinical Computer-Use Agents

MedCUA-Bench is a new benchmark designed to evaluate the reliability of computer-use agents in clinical medical graphical user interfaces. It addresses the gap left by existing benchmarks that focus on general web or desktop tasks. The benchmark is screenshot-only, reflecting real-world clinical workflows.

Robust Uncertainty-aware Segmentation via Whitening

The paper proposes ROBUST-WT, a segmentation method using whitening transform and probabilistic shape regularization to improve generalization across medical imaging domains. The approach targets robustness to domain shifts caused by different devices and protocols.

GLINT: Sparse-gated VLM for fine-grained radiology

GLINT introduces sparse gating for vision-language alignment in radiology, addressing the scale mismatch between image regions and report findings. The model focuses on fine-grained representations for chest X-rays.

Multi-modal ML predicts breast cancer recurrence

The paper proposes a multi-modal model combining structured clinical data and medical images to predict breast cancer recurrence risk. It aims to improve accuracy over traditional unimodal approaches.

Traj-Evolve: Self-Evolving Multi-Agent System for Lung Cancer Patient Trajectory Modeling

Traj-Evolve leverages LLM-based multi-agent collaboration to model patient trajectories from longitudinal EHRs, addressing sparse and long-context data. The system is designed to improve early detection of lung cancer.

New VQA benchmark evaluates VLMs on 3D medical imaging

The Oncology VQA benchmark tests vision-language models on 3D medical images, with tasks derived from clinical reports. It aims to provide a scalable, clinically grounded evaluation for VLMs in oncology.

CP-Agent: multimodal reasoning for cellular morphological profiling

The paper introduces CP-Agent, a context-aware multimodal reasoning model for analyzing cell imaging data under chemical perturbations. It aims to support mechanism-of-action inference and toxicity prediction.

FCUS-rPPG: Fast-Converging Unsupervised rPPG via Gradient Oscillation Suppression

New unsupervised rPPG method suppresses gradient oscillations for faster convergence without requiring ground-truth physiological annotations. The FCUS-rPPG framework learns BVP representations using consumer-grade cameras.

CoughSense paper classifies five respiratory diseases from cough sounds

The system uses Whisper encoder fine-tuning with dual-encoder cross-attention fusion and balanced contrastive learning to distinguish five respiratory conditions. It is designed for low-cost screening on consumer devices, going beyond binary COVID-19 detection.

DMT-CBT: LLM-based model for longitudinal CBT counseling

The paper proposes DMT-CBT, a model that uses LLMs for longitudinal therapeutic state modeling in Cognitive Behavioral Therapy. It aims to move beyond local empathetic responses to track client progress over time.

ChatHealthAI aligns EHR and LLMs for grounded clinical reasoning

Paper introduces ChatHealthAI, which integrates structured EHR data with LLMs via a time-aware encoder and feature alignment module. The model is evaluated on diagnosis and mortality prediction tasks.

MoPE method integrates transcriptomics and histopathology for better cancer risk models

MoPE (Mixture of Pathway Experts) uses privileged distillation to learn from both transcriptomics and histopathology during training but deploys using only histopathology images, solving the RNA profiling scarcity problem. The method improves cancer risk stratification compared to histopathology-only models.

Cross-modal contrastive learning for severe stenosis classification

The paper proposes a cross-modal contrastive learning approach that jointly learns representations from ECG and X-ray angiography data to classify severe coronary artery stenosis. The method aims to improve diagnostic accuracy by combining non-invasive and invasive modalities.

Study finds demographic bias in skin lesion classification

Researchers evaluate ResNet-based skin lesion classifiers, focusing on performance bias due to patient sex and age variations. The study uses linear programming to analyze demographic disparities in training data.

Limited evidence of AI superiority in influenza vaccine strain selection

A Nature Medicine correspondence argues that current evidence does not show AI models outperform traditional methods for selecting seasonal influenza vaccine strains. The original authors reply, defending their AI approach and methodology.

Peritas AI and NVIDIA deploy humanoid robotics at AdventHealth

Peritas AI, in collaboration with NVIDIA, deployed assistive humanoid robotics at AdventHealth to enhance surgical workflows and patient experience. The system brings real-time AI data intelligence to physical healthcare environments.

Joint Commission launches voluntary AI responsibility certification for healthcare

The new Responsible Use of AI in Healthcare certification is voluntary and targets healthcare organizations' practices, not individual AI tools. It aims to promote safe, reliable, transparent, and ethical AI deployment.

AI-driven revolution in medicine: Eli Lilly's retatrutide combats obesity

How AI can give community oncology clinics a clearer view of the future

Community oncology practices use AI to forecast demand, manage drug inventory, and navigate payer contracts. Oklahoma Cancer Specialists leverages the tool to purchase costly specialty drugs more efficiently.

Podcast: Non-CFO leaders driving AI investment decisions

Healthcare AI investments increasingly involve leaders beyond the CFO, according to a HIMSSCast podcast. The episode explores shifting decision-making dynamics for AI adoption.

AI decision support adoption suffers when benefits unclear

Duke University study finds clinical decision support adoption varies widely across health systems. End-users often discontinue use because they cannot directly see AI tools' impact.

Anomaly raises $17M for AI-powered payer intelligence platform

Sound Ventures led the round with Alumni Ventures joining. Anomaly's AI platform expands from revenue cycle operations into managed care, arming providers with payer intelligence across contract negotiations and claims.

Rehumanizing global health care with agentic AI

Agentic AI offers a path to rehumanize global healthcare by addressing chronic underinvestment and staff shortages. It aims to improve access and reduce fragmentation in care delivery.

SNUH, Harvard unveil world's first virtual hospital for validating medical AI

Researchers from Seoul National University Hospital and Harvard Medical School created the Clinical Environment Simulator (CES), the first virtual hospital framework for dynamically evaluating LLM-based medical AI. CES simulates real clinical scenarios to test AI performance and safety before real-world deployment.

AI and Robotics Reshape Surgical Precision in Operating Rooms

A guest article from FPT Software's VP highlights the convergence of AI, robotics, and connectivity in surgery. The piece argues that these technologies will redefine precision and outcomes in operating rooms.

OpenAI spotlights voice-first surgical triage workflow

1 in 8 medical practices deploy AI receptionists

A survey reported in Healthcare IT Today's roundup indicates that 12.5% of medical practices have adopted AI receptionist technology. The trend reflects increasing automation in healthcare front-office tasks.

General-purpose promptable model for 3D medical segmentation

Segments over 100 anatomical structures in CT and MR images

H1 secures $40M for AI healthcare provider directory

CVS Health Ventures led the $40M round. H1's AI platform identifies and vets healthcare providers. The company has recently collaborated with CVS Health on several projects.

Peer AI medical writing platform targets FDA submissions

Peer AI, a medical writing acceleration tool for pharma/biotech, is repositioning as a submission platform. The platform was featured on the Life Sciences Today Podcast.

How AI can be employed in emergency response

HIMSS will host an AI Executive Leadership Summit in Boston on June 24, 2026. The event will be followed by its AI in Healthcare Forum on June 25-26.

12 prompts to make ChatGPT/Claude your health OS

Boston Children's Hospital uses AI to diagnose 40+ rare diseases

The hospital diagnosed more than 40 rare disease cases using OpenAI's technology. The AI system also reduced operational burden for clinicians, improving efficiency.

Building an AI voice agent for hospital scheduling: challenges revealed

A developer shares hard-learned lessons from deploying a voice agent for a hospital's real appointment scheduling line. The post covers edge cases, compliance, and patient interaction pitfalls that demos don't show.

OpenAI launches Rosalind Biodefense for biosecurity and public health

Rosalind Biodefense expands trusted access to GPT-Rosalind for vetted developers and U.S. government partners. The initiative aims to strengthen societal resilience against biological threats and improve pandemic preparedness.

Reddit user reports positive experience using ChatGPT in medical work

A medical professional on Reddit shares that paid ChatGPT provided an accurate and useful response to a clinical query. They contrast their positive experience with the negative sentiment toward AI prevalent on other subreddits.

How APAC should deploy AI to find hidden lung cancers

The article examines AI deployment for lung cancer screening across the Asia-Pacific region, focusing on never smokers. It highlights AI's role in addressing the growing lung cancer burden through population-wide screening.

Abridge uses GPT-5.5 for clinical decision support

GPT-5.5 helps Abridge synthesize patient context, clinical conversations, and medical information through stronger reasoning and tool use. The system aims to give clinicians denser, more useful information at the point of care.

Children's Minnesota CIO: AI will dwarf prior health IT shifts

Dave Lundal, CIO at Children's Minnesota, calls AI a 'third era' in healthcare IT that will 'dwarf' prior changes like EHRs. He warns AI's rapid evolution makes strategy difficult, unlike EHR implementations.

AI pushes nursing education to emphasize data standardization and ethics

A new investigation calls for nursing education to focus on standardizing nurse-generated data and building AI systems aligned with patient-care ethics. Nurses must learn to use AI tools effectively to ensure ethical implementation.

Oura unveils AI-enabled Ring 5 with predictive health features

Oura Ring 5 is 40% smaller than Ring 4, has a one-week battery life, and features four times stronger LEDs for improved accuracy. It introduces new predictive health features.

HIMSS sets an AI-centered clinician learning agenda

HIMSS has introduced a learning agenda centered on AI for clinicians. The initiative aims to equip healthcare professionals with AI knowledge.

Sequoia podcast walks through Neuralink's brain-computer interface progress

Neuralink co-founder DJ Seo discusses the company's journey from one human patient to over twenty. He covers the challenges of building a bridge between the human brain and AI and what the future holds.

Inside Optum Health's push to make AI practical for clinicians

Optum Health is deploying AI to reduce the time physicians spend clicking through electronic health records after hours. The initiative integrates AI into clinical workflows to automate documentation and data retrieval.

Making AI and Value-Based Care Work in Rural Health Facilities

Rural healthcare faces $900B-$1T Medicaid cuts, staffing shortages, and transportation challenges. The article discusses how rural providers can leverage AI and value-based care models to improve outcomes and financial sustainability, highlighting advantages like closer community ties.

SOND exits stealth with $7M for AI-powered sleep earbuds

SOND, led by Bose's former head of sleep products, emerged from stealth with $7 million in funding. The startup's AI-powered earbuds offer personalized sleep coaching and soundscapes.

AI tools give clinicians more time with patients

A HIMSS TV video explores how AI tools are freeing up clinicians' time for patient care. The video highlights improvements in workflow efficiency and reduced administrative burden.

Care delivery has a great partner in AI

HIMSS TV video discusses AI as a partner in care delivery. No specific examples or details are provided.

Utah's clinical AI sandbox highlights need for independent oversight

Nature Medicine article examines Utah's clinical AI sandbox, showing how real-world testing reveals the need for independent oversight beyond current regulatory frameworks. The sandbox allows AI tools to be tested in clinical settings, uncovering issues that traditional approval processes miss.

CHI-Bench launches as long-horizon healthcare AI benchmark

NVIDIA RTX PRO 4500 Blackwell speeds genomics and protein folding workloads

The new RTX PRO 4500 Blackwell GPU targets precision medicine, offering faster performance for genomics and protein folding computations. It leverages the Blackwell architecture to accelerate drug discovery and molecular analysis tasks.

Sunoh.ai's ambient AI scribe cuts clinician nighttime charting

Family Health Centers in Louisville adopted Sunoh.ai's ambient AI scribe to reduce after-hours documentation. Chief Clinical Informatics Officer Cynthia Cox reports the tool cut 'pajama time' charting during evenings and nights.

No-code AI adoption in healthcare requires partnerships and governance

A HIMSS TV video discusses key factors for successful no-code AI adoption, emphasizing partnerships and governance structures. The piece highlights the need for collaboration between technical and clinical teams.

Fundamental considerations for no-code AI

Healthcare IT News video discusses fundamental considerations for no-code AI. The video is presented by HIMSS TV.

Knit Health Launches with $11.6M Seed for Clinical AI

The UC Berkeley spin-out emerged from stealth with $11.6M in seed funding co-led by Uncork Capital and Moxxie Ventures. Knit Health builds clinical intelligence AI that learns from real clinical decision-making.

AI framework uses blood biopsies to advance precision oncology

Mayo Clinic and Stanford have developed an AI framework that analyzes blood biopsies to reveal tumor microenvironment factors across multiple cancer types. It is the first blood test capable of such analysis, potentially making precision oncology more accessible. The framework could benefit a multitude of cancer patient populations.

Insilico Taps US Partner to Build AI Model for Human Longevity

Insilico Medicine partners with a US company to develop an AI model targeting human longevity. The collaboration aims to combine Insilico's AI platform with the partner's expertise in aging research. Further details are behind a paywall.

Over 200 AI-designed drugs in trials, none approved

Asan Medical Center unveils AI-powered private search system

The on-premises system runs in a closed network, disconnected from the internet, ensuring data privacy. It enables hospital staff to securely search medical knowledge.

Singapore and Bhutan partner on chest X-ray AI

SingHealth and Royal University of Bhutan are collaborating to develop an AI-assisted chest X-ray model for diagnosing lung conditions in rural hospitals. The partnership was announced at a government-hosted AI conference in Singapore.

Roche Enters Into a Definitive Merger Agreement to Acquire PathAI

Roche will acquire PathAI to combine its diagnostics strength with PathAI's AI-powered pathology platform. PathAI's image management system and AI analysis capabilities aim to enhance laboratory efficiency and accelerate companion diagnostics.

Harvard Medical School tests AI diagnoses in ER

Chef Robotics robots assist San Francisco nonprofit meal prep

Project Open Hand, a nonprofit founded during the AIDS crisis, uses Chef Robotics' robots to plate medically tailored meals for patients with chronic conditions, addressing a volunteer shortage. The robots only plate food, not cook, and are also used by Amy's Kitchen and Factor. 'It's not even that they're faster. It's that we don't have the volunteers,' said sous chef Alma Caceres.

New brain implants restore partial vision by stimulating visual cortex

Two brain implants give blind people partial vision by wiring cameras directly to the visual cortex. One device reads brain signals and adjusts itself in real time to improve visual perception.

AI is accelerating drug development

The article explores how artificial intelligence is speeding up drug development. It discusses various ways AI is making an impact on the pharmaceutical industry.

AI's promise meets the pediatric frontline

Article explores how AI can alleviate clinician burnout from EHRs in pediatric settings. Focuses on Children's hospitals' efforts to integrate AI into clinical workflows.

NVIDIA blog details method to synthesize 3D medical images

The approach generates high-quality 3D medical imaging data to overcome data scarcity and privacy constraints. It enables training and shipping pre-trained AI models using synthetic data.

Open-source clinical AI is a neglected niche, says Hugging Face

Insilico on Applying AI to Transform Drug Discovery

Bloomberg interviews Insilico Medicine about its AI-driven approach to drug discovery. The company explains how its platform identifies drug targets and generates candidate molecules.

Perspective outlines risk of AI-induced never-skilling in medical training

The article proposes a precautionary framework to preserve foundational clinical competence as AI tools become prevalent. It warns that over-reliance on AI could prevent trainees from developing independent diagnostic skills.

Google AI breast cancer detection system outperforms radiologists in studies