Oral potentially malignant disorder poses a significant risk of malignant transformation, particularly in cases with epithelial dysplasia (OED). Current OED assessment methods are invasive and lack reliable decision-support tools for cancer risk evaluation and…
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For patients with locally advanced cervical cancer (LACC), precise survival prediction models could guide personalized treatment. We developed and validated CerviPro, a deep learning-based multimodal prognostic model, to predict disease-free survival (DFS) in 1018…
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Endovascular aortoiliac revascularization is a common treatment option for peripheral artery disease that carries non-negligible risks. Outcome prediction tools may support clinical decision-making but remain limited. We developed machine learning algorithms that predict 30-day…
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Routinely collected blood tests can reflect underlying pathophysiological processes. We demonstrate that the dynamics of routinely collected blood tests hold prediction validity in acute Spinal Cord Injury (SCI). Using MIMIC data (n = 2615) for modeling…
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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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Steps I and II periodontal therapy is the first-line treatment for periodontal disease, but has varying success. This study aimed to develop machine learning models to predict changes in periodontal probing depth (PPD) after…
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Early identification of cerebral small vessel disease related cognitive impairment (CSVD-CI) is crucial for timely clinical intervention. We developed a Transformer-based deep learning model using white matter hyperintensity (WMH) radiomics features from T2-fluid-attenuated inversion…
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Retinal photography is a valuable non-invasive tool for assessing vascular health, but genetic evidence linking retinal microcirculation to major vascular-related diseases (e.g., myocardial infarction [MI], stroke, and chronic kidney disease [CKD]) remains scarce. This…
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