Image quality variation is a prominent cause of performance degradation for intelligent disease diagnostic models in clinical applications. Image quality issues are particularly prominent in infantile fundus photography due to poor patient cooperation, which…
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Congenital malformations of the central nervous system are among the most common major congenital malformations. Deep learning systems have come to the fore in prenatal diagnosis of congenital malformation, but the impact of deep…
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Preterm birth (PTB) is the leading cause of infant mortality globally. Research has focused on developing predictive models for PTB without prioritizing cost-effective interventions. Physical activity and sleep present unique opportunities for interventions in…
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Skin diseases affect one-third of the global population, posing a major healthcare burden. Deep learning may optimise healthcare workflows through processing skin images via neural networks to make predictions. A focus of deep learning…
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By Shania Kennedy
September 19, 2023 – Machine learning (ML) may help define personalized temperature norms and improve the clinical utility of oral temperature measurements, according to a study published this month in JAMA Internal Medicine.
Oral…
The University of Houston has secured a $3 million NIH grant to develop an AI tool for accurately classifying lupus nephritis (LN) from histopathology data, addressing the imprecision of traditional methods. Led by Chandra…
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The electrocardiogram (ECG) is the most frequently performed cardiovascular diagnostic test, but it is unclear how much information resting ECGs contain about long term cardiovascular risk. Here we report that a deep convolutional neural…
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For hemodialysis patients, arteriovenous fistula (AVF) patency determines whether adequate hemofiltration can be achieved, and directly influences clinical outcomes. Here, we report the development and performance of a deep learning model for automated AVF…
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What You Should Know:
DoMore Diagnostics, a leader in deep learning precision diagnostics for digital pathology, and Proscia®, a leading provider of digital and computational pathology solutions, have partnered to help pathologists predict outcomes for colorectal cancer…
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By Shania Kennedy
August 30, 2023 – Researchers at Yale School of Medicine have developed a deep learning (DL) approach that can accurately detect aortic stenosis by analyzing heart ultrasound scans, according to a study published…
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