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Using Data and AI to Create Better Health Care Systems

Academic medical centers could transform patient care by adopting principles from learning health systems principles, according to researchers from Weill Cornell Medicine and the University of California, San Diego. In this approach, information from electronic health records, clinical trials and day-to-day hospital operations is analyzed in real-time to uncover insights that continuously improve patient care.

AI Medical Receptionist Modernizing Doctor Appointments

A virtual medical receptionist named "Cassie," developed through research at Texas A&M University, is transforming the way patients interact with health care providers.

Cassie is a digital-human assistant created by Humanate Digital, a startup founded by three Aggies, including Dr. Mark Benden, professor in the Texas A&M School of Public Health and director of the Center for Worker Health.

AI Tool Set to Transform Characterisation and Treatment of Cancers

A multinational team of researchers, co-led by the Garvan Institute of Medical Research, has developed and tested a new AI tool to better characterise the diversity of individual cells within tumours, opening doors for more targeted therapies for patients.

Findings on the development and use of the AI tool, called AAnet, have today been published in Cancer Discovery, a journal of the American Association for Cancer Research.

Northern Ireland Completes Nationwide Roll-out of Clinisys WinPath

Go-lives at Western and Southern health and social care trusts mean every pathology service is using the same laboratory information management system; improving efficiency and quality.

An ambitious technology project to support the transformation of pathology services across Northern Ireland has been completed, with the go-live of the Clinisys WinPath laboratory information management system at the final two health and social care trusts.

Human-AI Collectives Make the Most Accurate Medical Diagnoses

Diagnostic errors are among the most serious problems in everyday medical practice. AI systems - especially large language models (LLMs) like ChatGPT-4, Gemini, or Claude 3 - offer new ways to efficiently support medical diagnoses. Yet these systems also entail considerable risks - for example, they can "hallucinate" and generate false information.

MHP-Net: A Revolutionary AI Model for Accurate Liver Tumor Segmentation for Diagnosis and Therapy

Liver cancer is the sixth most common cancer globally and a leading cause of cancer-related deaths. Accurate segmentation of liver tumors is a crucial step for the management of the disease, but manual segmentation by radiologists is labor-intensive and often results in variations based on expertise.

AI Detects Hidden Heart Disease Using Existing Scans Stored in Patient Records

Mass General Brigham researchers have developed a new AI tool in collaboration with the United States Department of Veterans Affairs (VA) to probe through previously collected CT scans and identify individuals with high coronary artery calcium (CAC) levels that place them at a greater risk for cardiovascular events.

DIGITAL HEALTH NEWS

Using Data and AI to Create Better Health Care Systems

AI Medical Receptionist Modernizing Doctor Appointments

AI Tool Set to Transform Characterisation and Treatment of Cancers

Northern Ireland Completes Nationwide Roll-out of Clinisys WinPath

Human-AI Collectives Make the Most Accurate Medical Diagnoses

MHP-Net: A Revolutionary AI Model for Accurate Liver Tumor Segmentation for Diagnosis and Therapy

AI Detects Hidden Heart Disease Using Existing Scans Stored in Patient Records

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