Clinical trial matching is the task of identifying trials for which patients may be eligible. Typically, this task is labor-intensive and requires detailed verification of patient electronic health records (EHRs) against the stringent inclusion…
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Rob Juncker, CTO of Code42 (now part of Mimecast)
It’s said that data is the lifeblood of the modern enterprise. While that’s certainly true, it’s also true that there is perhaps no industry as dependent…
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What You Should Know:
– Gradient Health, a leading provider of medical imaging data for AI development, has acquired DataAppraisal, a healthcare AI company specializing in unlocking the value of anonymized data from health systems…
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Robust data privacy regulations hinder the exchange of healthcare data among institutions, crucial for global insights and developing generalised clinical models. Federated learning (FL) is ideal for training global models using datasets from different…
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Environmental factors amplified by climate change contribute significantly to the global burden of disease, disproportionately impacting vulnerable populations, such as individuals with rare diseases. Researchers require innovative, dynamic data linkage methods to enable the…
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A public-private national project in India has introduced what could be the country’s first comprehensive cancer multi-omics database fifteen years after its founding.The Indian Cancer Genome Atlas (ICGA) focuses on studying cancer biology specific…
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The American Society of Anesthesiologist’s Physical Status (ASA-PS) classification system assesses comorbidities before sedation and analgesia, but inconsistencies among raters have hindered its objective use. This study aimed to develop natural language processing (NLP)…
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Healthcare AI startup Qure.ai closed a $65 million Series D financing round on Wednesday. The startup — which is headquartered in India — plans to use the capital to expand its presence in the…
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The dawn of the digital era has ushered in an unprecedented wave of innovation, particularly in the realm of mental health care. With the increasing prevalence of mental health issues like depression, anxiety, addiction and…
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Risk adjustment is often necessary for outcome quality indicators (QIs) to provide fair and accurate feedback to healthcare professionals. However, traditional risk adjustment models are generally oversimplified and not equipped to disentangle complex factors…
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