AIMC Topic: Female

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Clinical Efficacy of Real-Time Artificial Intelligence-Assisted Colonoscopy in Colorectal Polyp Detection: A Prospective Multicenter Randomized Controlled Trial.

Gut and liver
BACKGROUND/AIMS: Early detection and removal of colon polyps are critical for preventing colorectal cancer. Computer-aided detection (CADe) systems have been introduced to increase the polyp detection rate (PDR) during colonoscopy, potentially enhanc...

Structured Integration of an Artificial Intelligence-Based System for the Optical Diagnosis of Colorectal Polyps.

Gut and liver
BACKGROUND/AIMS: Recent advances in computer-aided diagnosis (CADx) systems have demonstrated expert-level accuracy in the optical diagnosis of colorectal polyps. High-confidence (HC) diagnoses have been defined as those made within 3 seconds without...

Solving gaps in clinical reasoning is the cure to neurophobia in artificial intelligence.

Journal of the neurological sciences
BACKGROUND AND OBJECTIVES: This is an observational study that assesses the clinical reasoning of an artificial intelligence chatbot using previously published cases. The primary objective of the study is to assess the unique challenges neurologic ca...

Genome wide DNA methylation and transcriptome integration analysis reveals potential markers in type A aortic dissection pathogenesis.

Scientific reports
Type A aortic dissection (TAAD) is a vascular disease with high mortality; however, the role of gene methylation in its pathogenesis has received little attention. This study aimed to identify candidate markers of TAAD by integrating methylation and ...

Integrating inflammatory biomarkers and demographic variables with machine learning to predict endometriosis risk.

Scientific reports
This study explores the relationship between inflammatory biomarkers and the risk of endometriosis, aiming to develop a predictive model using National Health and Nutrition Examination Survey (1999-2006) data. The dataset included 4,089 females with ...

An interpretable machine learning approach to prognosis of melioidosis pneumonia via computed tomography quantification and clinical data.

Scientific reports
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...

Development and validation of nomogram and machine learning models to predict sarcopenia in patients with chronic kidney disease.

Scientific reports
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...

Construction of the prediction model and analysis of key winning factors in world women's volleyball using gradient boosting decision tree.

Scientific reports
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 ...

Higher-order sonification of the human brain.

Scientific reports
Sonification, the process of translating data into sound, has recently gained traction as a tool for both disseminating scientific findings and enabling visually impaired individuals to analyze data. Despite its potential, most current sonification m...

Prediction of longitudinal outcomes and novel cluster identification in epilepsy.

Scientific reports
The longitudinal course of epilepsy remains largely unpredictable. This study aimed to predict final outcome and classify dynamic longitudinal trajectories using artificial intelligence. A total of 2586 patients who first visited our epilepsy special...