Healthcare is plagued with many problems that Artificial Intelligence (AI) can ameliorate or sometimes amplify. Regardless, AI is changing the way we reason towards solutions, especially at the frontier of public health applications where autonomous ...
A machine learning model was developed and validated to predict postoperative complications in patients with acute type A aortic dissection (ATAAD) who underwent total arch replacement combined with frozen elephant trunk (TAR + FET), with the goal of...
Ankylosing spondylitis (AS) and rheumatoid arthritis (RA) are closely related autoimmune diseases with shared mechanisms that remain unclear. This study aims to identify shared molecular signatures and hub genes underlying the co-occurrence of AS and...
Emerging evidence suggests a bidirectional relationship between colorectal cancer (CRC) and type 2 diabetes mellitus (T2DM), yet the shared molecular mechanisms and prognostic biomarkers remain poorly characterized. This study aimed to identify novel...
Early warning scores are used to assess acute patients' risk of being in a critical situation, allowing for early appropriate treatment, avoiding critical outcomes. The early warning scores use changes in vital signs to provide an assessment, however...
This study evaluated the discriminative potential of a machine learning model using movement features during functional tasks to distinguish between patients with non-traumatic chronic neck pain and asymptomatic controls. The study included patients ...
Plasma proteomics provides a unique opportunity to enhance disease prediction by capturing protein expression patterns linked to diverse pathological processes. Leveraging data from 2,923 proteins measured in 53,030 UK Biobank participants, we develo...
This study aimed to identify the risk factors associated with spontaneous rupture and bleeding in hepatocellular carcinoma, establish a prediction model for spontaneous rupture bleeding via a machine learning algorithm, and validate and evaluate the ...
Classifying chondroid tumors is an essential step for effective treatment planning. Recently, with the advances in computer-aided diagnosis and the increasing availability of medical imaging data, automated tumor classification using deep learning sh...
The majority of patients with epithelial ovarian cancer (EOC) continue to be diagnosed at an advanced stage despite great advances in this disease treatment. To impact overall survival, we need better methods of EOC early diagnosis. We performed a ca...
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