This study aimed to develop a dataset comprising computed tomography (CT) images and clinical data for melioidosis pneumonia and to utilize machine learning for assisting in prognosis prediction of the disease. We retrospectively analyzed multicenter...
Chronic kidney disease (CKD) is a growing public health problem worldwide. CKD not only leads to renal function decline but also increases the risk of multiple complications, sarcopenia being particularly common and severe. At present, there is a lac...
This study aims to analyze the key factors contributing to victories in world women's volleyball matches and predict match win rates using machine learning algorithms. Initially, Grey Relational Analysis (GRA) was employed to analyze the fundamental ...
Rapid identification of T cell receptors (TCRs) that specifically bind patient-unique neoepitopes is a critical challenge for personalized TCR-based therapies in oncology. Due to enormous diversity of both TCR and neoepitope repertoires, a machine le...
Recent advancements in precision agriculture have introduced innovative approaches to addressing plant stress, a critical factor influencing crop productivity and agricultural sustainability. Accurate, real-time prediction of plant stress has become ...
Heart attacks remain a major cause of morbidity and mortality, particularly among middle-aged and older adults, often aggravated by unhealthy lifestyles and limited preventive care. Early identification and prioritization of at-risk individuals are e...
Accurately predicting human perception of tactile roughness remains challenging because previous models often used limited mechanical properties, small sample sizes, and insufficient validation methods. To address these limitations, we developed a pr...
Primary vitreoretinal lymphoma (PVRL) is a rare and aggressive intraocular malignancy that is frequently misdiagnosed because of its nonspecific early manifestations and the lack of effective screening tools. We conduct a multicentre case-control stu...
The adoption of whole genome sequencing (WGS) in clinical oncology is challenged by low data quality and increased artifacts in standard-of-care formalin-fixed paraffin-embedded (FFPE) samples. Analysis of 56 fresh frozen (FF) and FFPE matched pairs ...
BACKGROUND: Preoperative endometrial cancer (EC) diagnosis often depends on radiologists' expertise, which introduces subjectivity. Recent studies have explored radiomics-based machine learning (ML) models for detecting myometrial invasion (MI), but ...
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