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Clinical tool predicts adoptive therapy response in eye cancer patients

April 16, 2024 - Researchers from the University of Pittsburgh Medical Center (UPMC) have developed a predictive model to forecast metastatic uveal melanoma patients’ response to adoptive therapy, according to a study published today in Nature Communications. The research team indicated that uveal melanoma is resistant to conventional immunotherapies, but...

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Machine learning framework captures uncertainty in medical images

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Researchers from the Massachusetts Institute of Technology (MIT), Massachusetts General Hospital and the Broad Institute of MIT and Harvard have developed a machine learning approach to help capture...

Machine learning characterizes cardiac function, drug response

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Columbia University researchers have developed a machine learning-based approach to assess cardiac function and drug response, according to a study published recently in IEEE Open Journal of...

Deep learning tool may reduce false-positives in screening mammography

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Researchers have developed a deep learning tool capable of reducing false positives without missing true cases of breast cancer identified by screening mammography, according to a study published this...

National Academy of Medicine publishes AI Code of Conduct draft

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The National Academy of Medicine (NAM) has published a draft framework for the responsible implementation of artificial intelligence (AI) technologies in healthcare and biomedical sciences and is...

10 high-value use cases for predictive analytics in healthcare

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As healthcare organizations pursue improved care delivery and increased operational efficiency, digital transformation remains a key strategy to help achieve these goals. Many health systems’...

AI biomarker identifies aortic stenosis development, progression

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A multi-institutional team of researchers has identified an artificial intelligence (AI)-based video biomarker capable of helping clinicians more accurately understand which patients are likely to...

Machine learning predicts hospitalization during cancer treatment

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Machine learning tools can accurately forecast an unplanned hospitalization event during concurrent chemoradiotherapy (CRT) using patient-generated health data from wearable devices, according to a...

Machine learning predicts risk of suicide in patients initiating care

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Kaiser Permanente researchers have demonstrated that a machine learning-based predictive model can stratify suicide risk among patients scheduled for an intake visit to outpatient mental healthcare,...

Clinical deterioration AI contributes to reduced care escalation risk

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Researchers have demonstrated that an artificial intelligence (AI) model designed to detect clinical deterioration was associated with a significantly decreased risk of inpatient escalations in care,...

Computational model uses biomarkers to predict Alzheimer’s progression

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Researchers from Duke University School of Medicine and Pennsylvania State University have demonstrated that a personalized model using individual biomarker data can accurately forecast Alzheimer's...

Machine learning approach may help tailor precision medicine treatments

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A research team from Arizona State University has developed a machine learning (ML) model capable of predicting whether a patient’s immune system will recognize pathogens and other foreign cells,...

NIH funding development of AI tools for health disparity research

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George Washington University (GW) School of Medicine and Health Sciences (SMHS) and the University of Maryland Eastern Shore (UMES) have been awarded a two-year, $839,000 National Institutes of Health...

AI reveals race-based differences in the expression of depression

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Researchers from the University of Pennsylvania, Philadelphia, and the National Institute on Drug Abuse (NIDA) have demonstrated that artificial intelligence (AI) models designed to predict depression...

Analysis highlights five preventable suicide risk profiles

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Researchers from Weill Cornell Medicine, Columbia University, UC Berkeley School of Public Health, the University of Hong Kong and University of Kentucky have identified five preventable suicide risk...

Online big data dashboard to help map enteric infectious diseases

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A team from the University of Virginia (UVA) is developing an online big data dashboard to map enteric infectious disease burden in low- and middle-income countries, which researchers and public health...

Machine learning tools predict COVID-19 vaccine hesitancy, uptake

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Researchers from the University of Cincinnati (UC) and Northwestern University have developed machine learning (ML) models that can accurately predict trends in COVID-19 vaccine uptake using reward and...

Deep learning model detects COVID-19 infection using lung imaging

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Johns Hopkins researchers have developed a deep learning-based model to detect COVID-19 infection using lung ultrasound images, according to a study published recently in Communications Medicine. The...

Healthcare leaders launch Trustworthy & Responsible AI Network

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Healthcare leaders came together recently to launch the Trustworthy & Responsible AI Network (TRAIN), a consortium created to explore and set standards for the safe application of artificial...

How do population health, public health, community health differ?

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The rapid proliferation of value-based care arrangements, driven by electronic health record (EHR) adoption and the subsequent explosion of big data, has given providers the opportunity and the...

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