Cerbras Systems, a provider of artificial intelligence computing chips for deep learning applications, will provide both hardware and software development services to Mayo under the deal announced during a presentation at this week’s J.P….
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Parkinson’s disease (PD) exhibits significant clinical heterogeneity, presenting challenges in the identification of reliable electroencephalogram (EEG) biomarkers. Machine learning techniques have been integrated with resting-state EEG for PD diagnosis, but their practicality is constrained…
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AI’s synergy with radiology reshapes healthcare by enhancing diagnostics, streamlining workflows, and amplifying precision. Evolving from early skepticism, AI, especially deep learning and radiomics, redefines diagnostics. AI’s integration spans the patient journey, optimizing processes…
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By Shania Kennedy
December 19, 2023 – Researchers from the Smidt Heart Institute at Cedars-Sinai, Stanford University, and Columbia University have developed and validated a deep learning (DL) model capable of predicting postoperative mortality risk, according…
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The monitoring of physiological parameters is a crucial topic in promoting human health and an indispensable approach for assessing physiological status and diagnosing diseases. Particularly, it holds significant value for patients who require long-term…
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New AI app for facial palsy screeningComputer scientists from Australia and Iraq have developed an AI-based diagnostic tool to detect facial palsy.
They have come up with a detection system for facial palsy featuring a…
Early identification of atrial fibrillation (AF) can reduce the risk of stroke, heart failure, and other serious cardiovascular outcomes. However, paroxysmal AF may not be detected even after a two-week continuous monitoring period. We…
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The UEF Cancer AI team launched a challenge for estimating breast density from mammograms. Addressing limitations in existing tools, the challenge seeks innovative deep-learning architectures. Participants work with a dataset of 569 mammogram images,…
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By Shania Kennedy
December 11, 2023 – Researchers have developed a deep neural network-based model to predict the most successful antihypertensive treatment for an individual, according to a study published recently in Mayo Clinic Proceedings: Digital…
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By Shania Kennedy
December 05, 2023 – A deep learning model can accurately identify non-smokers at high risk for lung cancer using only routine chest X-rays, according to research presented at this year’s meeting of the…
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