OBJECTIVES: Although deep learning has demonstrated substantial potential in automatic quantification of joint damage in RA, evidence for detecting longitudinal changes at an individual patient level is lacking. Here, we introduce and externally vali...
BACKGROUND: The International Study Group of Pancreatic Surgery has established the definition and grading system for postpancreatectomy acute pancreatitis (PPAP). There are no established machine learning models for predicting PPAP following pancrea...
The test-negative design (TND), which is routinely used for monitoring seasonal flu vaccine effectiveness (VE), has recently become integral to COVID-19 vaccine surveillance, notably in Québec, Canada. Some studies have addressed the identifiability ...
Zhonghua zhong liu za zhi [Chinese journal of oncology]
Feb 23, 2025
Using methylation characteristics of human genes to construct machine learning predictive models for screening cervical cancer and precancerous lesions. Human DNA methylation detection was performed on 224 cervical exfoliated cell specimens from th...
Zhongguo fei ai za zhi = Chinese journal of lung cancer
Feb 20, 2025
BACKGROUND: Epidermal growth factor receptor (EGFR) sensitive mutation is one of the effective targets of targeted therapy for non-small cell lung cancer (NSCLC). However, due to the difficulty of obtaining some primary tissues and the economic facto...
European heart journal. Acute cardiovascular care
Feb 20, 2025
AIMS: Acute heart failure (AHF) poses significant diagnostic challenges in the emergency room (ER) because of its varied clinical presentation and limitations of traditional diagnostic methods. This study aimed to develop and evaluate a deep learning...
BACKGROUND: Borrmann type-4 (B-4) advanced gastric cancer is challenging to diagnose through routine endoscopy, leading to a poor prognosis. The objective of this study was to develop an artificial intelligence (AI)-based system capable of detecting ...
Disorders of the central nervous system, including neurodegenerative diseases, frequently affect the brainstem and can present with focal atrophy. This study aimed to (1) optimize deep learning-based brainstem segmentation for a wide range of patholo...
Venous thromboembolic events (VTE) is a frequent complication in multiple myeloma (MM) patients, raising mortality. This study aims to use machine learning to identify VTE risk factors in MM, helping to pinpoint high-risk individuals for better clini...
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