PURPOSE: The study aimed to develop and validate a predictive model for preoperative APF using computed tomography (CT) radiomics combined with deep learning, and validating the performance of the model in an independent cohort.
BACKGROUND: Combination immunotherapies, such as pembrolizumab plus lenvatinib (PL), are commonly used in treatment for unresectable hepatocellular carcinoma (uHCC). However, it remains challenging to predict which patients will benefit from this the...
BACKGROUND: Rapid diagnostic tests (RDTs) have improved malaria case management by enabling point-of-care confirmation of infection, particularly in low-resource settings. In addition to clinical use, RDT results recorded in health facility registers...
Journal of neuroengineering and rehabilitation
Oct 22, 2025
BACKGROUND: This study utilized artificial intelligence (AI)-based machine learning algorithms, alongside the shapley additive explanations (SHAP) framework, to identify lower-limb muscle force patterns associated with recurrent patellofemoral pain (...
BACKGROUND: The clinical significance and contribution of the lipid profile in atherosclerosis are well established. However, further investigation is needed in stroke patients, particularly regarding apolipoprotein B100 (ApoB100), a novel non-tradit...
OBJECTIVE: Pan-intestinal capsule endoscopy (PCE) offers a safer, more effective alternative to colonoscopy for detecting potentially haemorrhagic lesions (PHL) in suspected mid-lower gastrointestinal bleeding (MLGIB), though it is limited by time-co...
INTRODUCTION: Prognosis estimation is the basis for establishing the personal interventions in sepsis patients. Serum biomarkers are potential tools for predicting the outcomes of sepsis patients admitted to the intensive care unit (ICU). Here, we pl...
Artificial intelligence (AI) is transforming healthcare through tools like large language model chatbots. AI chatbots can simulate human conversation, provide personalized information, and interact with patients in real time. Their ease of use and co...
INTRODUCTION: Difficult intubation is one of the most challenging scenarios to deal with due to increased morbidity and mortality. Machine learning systems can help predict this process in advance. This study aimed to predict whether patients had dif...
INTRODUCTION: Community health workers (CHWs) are critical to healthcare delivery in low-resource settings but often lack formal clinical training, limiting their decision-making. Large language models (LLMs) could provide real-time, context-specific...
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