Efficient and accurate identification of genetic alterations of non-small cell lung cancer is a critical diagnostic process for targeted therapies. Utilizing advanced modern deep learning is a potential solution that can accurately predict genetic…
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Microsoft launches a free, AI-powered claims denial navigator from its Rural Health AI Innovation Lab.
The VA updates its AI strategy, which includes deploying tools for scheduling, real-time transcription, claims processing, and administrative tasks….
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To address the diversity of skin conditions and the low prevalence of skin cancers, we curated a large hospital dataset (National Information Society Agency, Seoul, Korea [NIA] dataset; 70 diseases, 152,443 images) and collected…
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Researchers from Indiana University have created an algorithm that helps clinicians search through patient data from health information exchanges and other sources. The tool identifies the most relevant data for a given visit such…
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Mark Coetzer, VP of Business Development, IMAT Solutions
Artificial intelligence (AI) continues to hold the spotlight in healthcare transformation, promising everything from predictive care to streamlined administrative processes. Visionary use cases include anticipating patient deterioration,…
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As complex AI systems become more common in clinical decision-making, a new type of physician-data science specialist is needed to bridge the gap between these AI tools and practicing clinicians. Analogous to how clinical…
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Personalising psychotherapies for depression may enhance their efficacy. We conducted a randomised controlled trial of smartphone cognitive-behavioural therapy (CBT) among 4,469 adults in Japan (RESiLIENT trial, UMIN-CTR UMIN000047124). Participants received one of nine CBT…
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Hepatocellular carcinoma (HCC) ultrasound screening encounters challenges related to accuracy and the workload of radiologists. This retrospective, multicenter study assessed four artificial intelligence (AI) enhanced strategies using 21,934 liver ultrasound images from 11,960 patients…
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Brain-based technologies for human augmentation face challenges in personalization and real-world translation. We present an AI-driven personalized Bayesian optimization algorithm that remotely adjusts neurostimulation parameters based on baseline ability and head anatomy to enhance…
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The widespread adoption of real-world data has given rise to numerous healthcare-distributed research networks, but multi-site analyses still face administrative burdens and data privacy challenges. In response, we developed a Collaborative One-shot Lossless Algorithm…
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