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Applying binary mixed model to predict knee osteoarthritis pain.
PloS one
Jul 15, 2025
Data used to understand knee osteoarthritis (KOA) often involves knee-level, rather than person-level information. Failure to account for the correlation between joints within a person may lead to inaccurate inferences. The aim of this study was to d...
Multimodal deep learning improving the accuracy of pathological diagnoses for membranous nephropathy.
Renal failure
Jul 14, 2025
OBJECTIVES: Renal biopsy is the gold standard for the diagnosis of glomerular diseases including membranous nephropathy (MN), however, it faces challenges in accuracy, objectivity, and reproducibility of tissue evaluation. This study aims to develop ...
Multimodal Deep Learning Model Based on Ultrasound and Cytological Images Predicts Risk Stratification of cN0 Papillary Thyroid Carcinoma.
Academic radiology
Jul 14, 2025
BACKGROUND: Accurately assessing the risk stratification of cN0 papillary thyroid carcinoma (PTC) preoperatively aids in making treatment decisions. We integrated preoperative ultrasound and cytological images of patients to develop and validate a mu...
Exploring the potential associations between single and mixed volatile compounds and preserved ratio impaired spirometry using five different approaches.
Ecotoxicology and environmental safety
Jul 14, 2025
BACKGROUND: Although the relationship between environmental pollutants and respiratory health has received widespread attention, no studies have explored the association between volatile organic compounds (VOCs) and preserved ratio impaired spirometr...
Synergizing Nanosensor-Enhanced Wearable Devices with Machine Learning for Precision Health Management Benefiting Older Adult Populations.
ACS nano
Jul 14, 2025
Population aging presents significant health challenges and socioeconomic burdens globally, driving an increased demand for precision health management. In the era of big data, the exponential growth of health information is accelerating advances in ...
Mortality and antibiotic timing in deep learning-derived surviving sepsis campaign risk groups: a multicenter study.
Critical care (London, England)
Jul 14, 2025
BACKGROUND: The current Surviving Sepsis Campaign (SSC) guidelines provide recommendations on timing of administering antibiotics in sepsis patients based on probability of sepsis and presence of shock. However, there have been minimal efforts to str...
A radiomics-clinical predictive model for difficult laparoscopic cholecystectomy based on preoperative CT imaging: a retrospective single center study.
World journal of emergency surgery : WJES
Jul 14, 2025
BACKGROUND: Accurately identifying difficult laparoscopic cholecystectomy (DLC) preoperatively remains a clinical challenge. Previous studies utilizing clinical variables or morphological imaging markers have demonstrated suboptimal predictive perfor...
Advancing shock prediction: leveraging prior knowledge and self-controlled data for enhanced model accuracy and generalizability.
BMC medical informatics and decision making
Jul 14, 2025
OBJECTIVES: Timely intervention in shock is vital, as delays over one hour greatly increase mortality. This study aims to develop an enhanced machine learning model that improves predictive performance by utilizing self-controlled data and applying f...
Predicting the molecular subtypes of 2021 WHO grade 4 glioma by a multiparametric MRI-based machine learning model.
BMC cancer
Jul 14, 2025
BACKGROUND: Accurately distinguishing the different molecular subtypes of 2021 World Health Organization (WHO) grade 4 Central Nervous System (CNS) gliomas is highly relevant for prognostic stratification and personalized treatment.
A hybrid learning approach for MRI-based detection of alzheimer's disease stages using dual CNNs and ensemble classifier.
Scientific reports
Jul 14, 2025
Alzheimer's Disease (AD) and related dementias are significant global health issues characterized by progressive cognitive decline and memory loss. Computer-aided systems can help physicians in the early and accurate detection of AD, enabling timely ...
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