Intraoperative frozen section diagnosis provides essential, real-time histological insights to guide surgical decisions. However, the quality of these time-sensitive sections is often suboptimal, posing significant diagnostic challenges for pathologists. To address these limitations, we…
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The wide usage of artificial intelligence (AI) text-to-image generators raises concerns about the role of AI in amplifying misconceptions in healthcare. This study therefore evaluated the demographic accuracy and potential biases in the depiction…
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Older adults with insomnia face considerable challenges accessing treatment given limited availability to first-line therapy (Cognitive-Behavioral Therapy for Insomnia, CBT-I). This study evaluated the efficacy of Sleep Healthy Using the Internet for Older Adults…
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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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This meta-analysis evaluated diagnostic performance of deep learning (DL) algorithms using whole slide images (WSIs) for detecting microsatellite instability-high (MSI-H) in colorectal cancer (CRC). PubMed, Embase, and Web of Science were searched until January…
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Artificial intelligence applications in liver pathology remain limited, with existing tools either narrowly focused or lacking external validation. This study introduces HOTSPoT, an open-source, validated transformer-based model for automated segmentation of portal tracts in…
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Artificial intelligence (AI) is already having a significant impact on healthcare. For example, AI-guided imaging can improve the diagnosis/treatment of vascular diseases, which affect over 200 million people globally. Recently, Chiu and colleagues (2024)…
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Chronic obstructive pulmonary disease (COPD) leads to high rates of emergency department (ED) visits and hospitalizations. This study evaluated a community-based digital health intervention’s association with acute care utilization among patients with moderate to…
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Large Language Models (LLMs) are increasingly used to support cancer patients and clinicians in decision-making. This systematic review investigates how LLMs are integrated into oncology and evaluated by researchers. We conducted a comprehensive search…
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Real-world data (RWD) from electronic health records and digital health databases present unique opportunities to study causal effects in healthcare. While Difference-in-Differences (DiD) analysis is widely used for such analyses, it can be biased…
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