What You Should Know:
– HOPPR, the company revolutionizing how AI imaging applications are built, validated, and deployed secures $31.5M in an oversubscribed Series A funding round led by Kivu and Greycroft, with participation from…
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Infantile epileptic spasm syndrome (IESS) is a severe neurological disorder characterized by epileptic spasms (ES). Timely diagnosis is crucial, but it is often delayed due to symptom misidentification. Smartphone videos can aid in diagnosis,…
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Reproductive aging impacts women’s health through fertility decline, disease susceptibility, and systemic aging. This study explores the retinal age gap—the difference between predicted retinal age and chronological age—as a novel biomarker for reproductive aging….
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Perci Health has closed a £3 million round, doubling its original target of £1.5m and raising a total of £7.7m in funding to support its plan to scale its AI-powered virtual cancer clinic.
The funding…
As digital biomarkers gain traction in Alzheimer’s disease (AD) diagnosis, understanding recent advancements is crucial. This review conducts a bibliometric analysis of 431 studies from five online databases: Web of Science, PubMed, Embase, IEEE…
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Combined immunodeficiencies (CID) and common variable immunodeficiencies (CVID), prevalent yet substantially underdiagnosed primary immunodeficiencies, necessitate improved early detection. Leveraging large-scale electronic health records (EHR) from four nationwide US cohorts, we developed a novel causal…
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The ethical integration of artificial intelligence (AI) in healthcare necessitates addressing fairness. AI fairness involves mitigating biases in AI and leveraging AI to promote equity. Despite advancements, significant disconnects persist between technical solutions and…
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The widespread adoption of Electronic Health Records (EHRs) and deep learning, particularly through Self-Supervised Representation Learning (SSRL) for categorical data, has transformed clinical decision-making. This scoping review, following PRISMA-ScR guidelines, examines 46 studies published…
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We explore biases present in publicly available fetal ultrasound (US) imaging datasets, currently at the disposal of researchers to train deep learning (DL) algorithms for prenatal diagnostics. As DL increasingly permeates the field of…
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A new AI model that is capable of simultaneous analysis of different skin images can potentially improve the diagnostic accuracy of both dermatology and non-dermatology professionals. An international research team led by AI and machine…
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