MedCloud Minute
The MedCloud Minute blog is researched, fact-checked, edited and updated by the editors of MedCloudInsider.com, with writing assistance from AI. To submit your company's press release for consideration, contact [email protected].
Lightbeam Health Solutions, an AI-enabled solutions leader in healthcare, showcased new artificial intelligence and analytics capabilities designed for healthcare organizations that take on financial risk for patient care. At the HIMSS26 conference, the company highlighted copilot-style AI tools and enhanced actuarial analytics intended to help healthcare providers and health systems manage risk-based care models. The capabilities are designed to help organizations analyze population health data, forecast costs and identify opportunities to improve patient outcomes while controlling expenses. Some of the capabilities showcased included, analytics copilot, cohort copilot, support for CMS models, expanded value-based contracting capabilities through Syntax Health and predictive ACO optimization tools.
Risk-bearing organizations, including accountable care organizations and value-based care providers, rely heavily on analytics to manage patient populations and financial performance. Tools that combine actuarial modeling with clinical data can help healthcare leaders evaluate treatment patterns, utilization trends and potential cost drivers. Healthcare providers are increasingly investing in AI and advanced analytics platforms as the industry shifts toward value-based care. Lightbeam will also showcase these new capabilities through the Microsoft Marketplace as a Microsoft Partner.
Posted by MedCloudInsider Editors on 03/09/20260 comments
Betterness, an augmented wellness platform, has introduced what it calls an agentic health and wellness MCP platform designed to support artificial intelligence agents that manage personalized wellness services and related data. The platform provides infrastructure for building AI agents capable of interacting with health and wellness systems, applications and user data. These agents are intended to automate tasks such as tracking health metrics, coordinating services and delivering personalized recommendations based on user information. Through a single MCP connection, AI agents can coordinate diagnostic testing, retrieve biomarker results, compute biological age, collaborate with specialized health agents and discover over 50,000 health and wellness providers.
Betterness aims for the framework to be integrated with existing digital health tools and wellness platforms while maintaining controls over how data is accessed and used. The approach aims to allow developers and organizations to build AI-driven services that interact with multiple health-related systems. Technology vendors and healthcare providers are increasingly exploring AI agents that can manage tasks across digital health platforms. The Betterness MCP is delivered as an open protocol, allowing developers to build agents that interact with Betterness Infrastructure and other health ecosystems.
Posted by MedCloudInsider Editors on 03/09/20260 comments
New research, published in JAMA Ophthalmology by the University of Colorado, reports that artificial intelligence analysis of eye photographs may help detect serious heart and lung conditions in premature infants. The approach uses machine learning to analyze retinal images typically captured during routine screening for retinopathy of prematurity, an eye disorder that can affect infants born early. By examining patterns in the blood vessels of the eye, researchers found the system may be able to identify signs associated with cardiopulmonary conditions affecting the infant. AI analysis of retinal imagery can help clinicians with early detection and can reduce the need for more invasive testing.
Early detection of complications such as pulmonary hypertension and other cardiovascular issues is critical for premature babies receiving care in neonatal intensive care units. Clinicians currently rely on a combination of imaging, monitoring and clinical assessments to identify these conditions. Researchers claim that AI-based screening tools could eventually support clinicians by identifying subtle warning signs earlier in the care process.
Posted by MedCloudInsider Editors on 03/09/20260 comments
Hoth Therapeutics, a clinical-stage biopharmaceutical company, announced that it will be using the OpenAI API to support research and development for its HT-KIT oncology program, a drug candidate being studied for potential cancer treatments. The technology is being used to analyze scientific literature and biomedical data related to KIT mutations and other cancer-related pathways. By applying AI tools to research workflows, Hoth aims to identify insights that could help guide the development of the experimental therapy. The OpenAI API has been integrated into the HT-KIT development workflow for preclinical data analysis, molecular modeling and preparing regulatory documents.
HT-KIT is being developed as a potential orphan drug, a designation used for treatments targeting rare diseases or conditions affecting relatively small patient populations. Drug developers often seek orphan status because it can provide regulatory incentives and market exclusivity if approved. Technology companies and pharmaceutical researchers are exploring ways generative AI can help interpret complex biomedical datasets and shorten development timelines. The integration supports the execution of IND-enabling strategies in HT-KIT research.
Posted by MedCloudInsider Editors on 03/09/20260 comments
Pivot Point Consulting, an IT consulting leader in the healthcare sector, has joined the Microsoft Rural Health Resiliency Program, an initiative designed to support rural hospitals and healthcare organizations in strengthening cybersecurity and advancing digital transformation. The collaboration focuses on helping underserved providers adopt secure cloud technologies and modern IT practices. The collaboration will implement Dragon Copilot readiness assessments, provide national webinars and demo, ensure workflow design governance is adhered to and provide education at major rural and digital health conferences. Rural hospitals can request a no-cost Dragon Copilot readiness assessment from Pivot Point Consulting.
Rural healthcare systems often face limited IT resources and heightened cybersecurity risks, particularly as ransomware and phishing attacks increasingly target smaller hospitals. Microsoft’s Rural Health Resiliency Program seeks to address these gaps by combining technology access, security guidance and partner expertise. Through the program, Pivot Point Consulting will provide advisory and implementation services aimed at improving infrastructure resilience, compliance posture and cloud adoption strategies. For healthcare IT leaders, the initiative reflects broader efforts to close the digital divide between urban and rural providers while strengthening cybersecurity defenses across the healthcare ecosystem.
Posted by MedCloudInsider Editors on 03/05/20260 comments
Quest Diagnostics, a leader in diagnostic information services, has introduced an AI-powered companion, called Quest AI Companion, within the MyQuest platform, designed to help patients better understand and act on their lab test results. The tool provides personalized explanations, contextual health information and suggested next steps based on individual diagnostic data, with the goal of improving patient engagement and clarity. Users can prompt the AI Companion to assist with composing questions to ask healthcare providers, empowering patients to have informed conversations with clinicians.
As access to digital health records expands, patients increasingly review lab results directly through online portals, often without immediate clinical interpretation. The AI companion integrates into its digital patient experience, supporting users in understanding results and preparing for follow-up discussions with healthcare providers. For healthcare IT leaders, the launch reflects a broader trend of embedding generative AI into patient-facing platforms to enhance comprehension, streamline communication, and support more informed health decisions.
Posted by MedCloudInsider Editors on 03/03/20260 comments
Aingens, a life sciences software company, has released the findings of a clinical AI reliability test for its platform, MACg (Medical Affairs Content generator), designed to evaluate the performance and safety of AI systems deployed in healthcare environments. The initial results showed zero hallucinations during testing, with 100% accuracy for numerical data, positioning the framework as a benchmark for validating AI accuracy in clinical use cases. The aim of releasing the results is to establish clearer benchmarks and governance standards for AI evaluation and deployment in evidence-critical workflows.
Hallucinations in AI remain a significant concern in healthcare applications, where inaccuracies can carry serious consequences. Aingen's reliability test evaluates AI outputs against verified clinical data and structured medical knowledge to assess consistency and factual accuracy. While broader validation across diverse real-world scenarios will be necessary to confirm long-term performance, the announcement highlights growing emphasis on measurable reliability standards in healthcare AI.
Posted by MedCloudInsider Editors on 03/02/20260 comments
XtalPi, a leading AI and robotics-driven drug discovery platform, announced that its platform has supported a clinical milestone for ReviR Therapeutic's investigational therapy RTX-117, a candidate targeting a rare neurological disorder. The platform helped accelerate key stages of research and development leading up to the clinical advancement. The discovery amplifies how AI-driven precision drug discovery can overcome traditional economic barriers in rare disease R&D. The success of RTX-117 validates the scalability and clinical impact of AI and robotics in expanding treatment options for minority patient groups.
AI-enabled drug discovery platforms are increasingly used to optimize molecular design, predict compound behavior and automate laboratory workflows. Robotics integration allows for high-throughput experimentation and data generation, potentially reducing timelines compared to traditional discovery processes. For life sciences and technology observers, the announcement underscores continued momentum behind AI-enabled drug development models that combine computational prediction with automated laboratory execution.
Posted by MedCloudInsider Editors on 03/02/20260 comments
b.well Connected Health, specialists in digital experiences, has introduced bailey, a ready-to-deploy, white-label AI health assistant designed for healthcare organizations, payers and digital health platforms. bailey can be customized and embedded into existing patient engagement applications, allowing organizations to offer AI-driven guidance under their own brand. Built on the same core infrastructure used by OpenAI and Samsung to power health agents, bailey is built on the b.well Health AI SDK connects data through a 13-step data refinery for a longitudinal health record. bailey offers complete health data integration, agentic AI architecture developed at scale, action-oriented AI, healthcare-grade security, consumer-first privacy and rapid deployment that is white-label ready.
The assistant is built to integrate with clinical and administrative data sources, enabling users to access personalized health information, navigate benefits, and receive support for care coordination. By offering a white-label model, b.well is targeting organizations seeking to maintain brand ownership while adding conversational AI capabilities. For healthcare IT leaders, the launch reflects broader efforts to combine data aggregation platforms with generative AI to create more accessible, patient-centered digital experiences.
Posted by MedCloudInsider Editors on 02/24/20260 comments
Mammotome, a breast cancer treatment company, has launched the Mammotome Prime MR system, described as the first in-room MR vacuum-assisted breast biopsy system, designed to allow clinicians to perform MRI-guided biopsies within the MRI suite. The system enables tissue sampling without requiring patients to be moved to a separate procedure area, aiming to streamline workflow and reduce procedure time. The Mammotome Prime MR system enables a stronger vacuum with larger tissue samples and an 8-gauge needle.
MRI-guided breast biopsy is typically used when lesions are visible only through magnetic resonance imaging. Traditional setups often require additional equipment positioning or patient transfer, which can add complexity to procedures. Advances in vacuum-assisted biopsy systems have focused on improving precision and efficiency while minimizing patient discomfort.
By integrating vacuum-assisted biopsy capabilities directly into the MRI environment, Mammotome is targeting workflow optimization in breast imaging centers. For radiology departments, the development reflects ongoing efforts to improve procedural efficiency and diagnostic accuracy as imaging volumes and demand for minimally invasive interventions continue to grow.
Posted by MedCloudInsider Editors on 02/24/20260 comments
Researchers at the University of Missouri are developing methods to make AI-driven scientific predictions more trustworthy by improving model transparency and reliability. The team is focused on strengthening confidence in machine learning systems used to analyze complex scientific data, particularly in areas where inaccurate predictions could have significant downstream consequences. The database, called PSBench includes 1.4 million annotated protein structure models that give scientists reliable information needed to build AI systems to assess the quality of protein structure models. Previous tools lack the information required to accurately predict every type of protein, but PSBench provides a solution to this marking a significant step in applying protein models to develop treatments.
AI models are increasingly used in scientific research to predict molecular behavior, climate patterns, and biological interactions. However, many of these systems function as “black boxes,” offering limited insight into how conclusions are reached. The Missouri team’s work aims to improve model confidence and create AI predictions that are more reliable. By incorporating validation techniques and explainability tools, the researchers hope to bridge the gap between computational speed and scientific rigor. As AI becomes more embedded in research workflows, ensuring that predictions are both accurate and transparent is emerging as a central priority for the scientific community.
Posted by MedCloudInsider Editors on 02/20/20260 comments
Metabolon, a global leader in metabolomics, announced that its metabolomics platform enabled what the company describes as the largest metabolomic analysis to date in CAR-T cell therapy, generating new insights into severe neurotoxicity associated with the treatment. The study analyzed metabolic profiles from patients undergoing CAR-T therapy and identified distinct metabolite patterns correlated with immune effector cell-associated neurotoxicity syndrome (ICANS), a potentially life-threatening complication. Researchers were able to identify clear, reproducible metabolic signatures that classified patients who developed high-grade NEs using metabolomics to reveal mechanisms that are invisible to genomic, proteomic and cellular assays.
CAR-T therapies have transformed treatment for certain hematologic cancers, but serious side effects such as cytokine release syndrome and neurotoxicity remain significant clinical challenges. By applying high-throughput metabolomics to CAR-T patients, Metabolon’s platform supports more detailed biomarker discovery efforts. For oncology researchers and biopharma developers, the findings underscore how multi-omics approaches are becoming central to managing risk and refining next-generation cell therapies.
Posted by MedCloudInsider Editors on 02/18/20260 comments