News 5/14/25
Top News
UnitedHealth Group announces that CEO Andrew Witty has resigned for personal reasons and has been replaced by Chairman and former CEO Stephen Hemsley.
The company also announced that it will suspend its 2025…
Tag: BRIAN
AI Hot Takes: From Hype to Healthcare Impact
Hype alone won’t move the needle. AI has to fit seamlessly into care delivery. In this video, HIMSS members Brian Anderson and Shreya Shah share their hot takes on why generative AI’s value hinges…
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Health AI Myths: Busted
People often worry that AI will edge out care providers. In this video, HIMSS members Troy Keyser and Brian Anderson set the record straight: AI exists to lift administrative burdens so clinicians can deepen…
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Overcoming barriers in the use of artificial intelligence in point of care ultrasound
Point-of-care ultrasound is a portable, low-cost imaging technology focused on answering specific clinical questions in real time. Artificial intelligence amplifies its capabilities by aiding clinicians in the acquisition and interpretation of the images; however,…
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Becoming WHOLE: Practical Steps to Transform Your Health and Life with Brian Seth Hurst
Brian Seth Hurst, an acclaimed author, speaker, and transformation coach whose book WHOLE has inspired countless individuals to achieve personal growth and inner peace joins eHealth Radio and the Health News and Personal Development Channels.
Listen to…
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Healthcare needs to prepare now for automation disruption to come
LAS VEGAS – If there’s one thing everyone can agree on about artificial intelligence in healthcare, it’s that everyone is still unsure about how to manage its many challenges and opportunities, and just where…
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Developing a named entity framework for thyroid cancer staging and risk level classification using large language models
We developed a named entity (NE) framework for information extraction from semi-structured clinical notes retrieved from The Cancer Genome Atlas—Thyroid Cancer (TCGA-THCA) database and examined Large Language Models (LLMs) strategies to classify the 8th…
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Identification of digital twins to guide interpretable AI for diagnosis and prognosis in heart failure
Heart failure (HF) is a highly heterogeneous condition, and current methods struggle to synthesize extensive clinical data for personalized care. Using data from 343 HF patients, we developed mechanistic computational models of the cardiovascular…
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3D convolutional deep learning for nonlinear estimation of body composition from whole body morphology
Body composition prediction from 3D optical imagery has previously been studied with linear algorithms. In this study, we present a novel application of deep 3D convolutional graph networks and nonlinear Gaussian process regression for…
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Machine learning meta-analysis identifies individual characteristics moderating cognitive intervention efficacy for anxiety and depression symptoms
Cognitive training is a promising intervention for psychological distress; however, its effectiveness has yielded inconsistent outcomes across studies. This research is a pre-registered individual-level meta-analysis to identify factors contributing to cognitive training efficacy for…
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