AIMC Topic: Predictive Value of Tests
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Development and validation of a machine learning model for predicting vulnerable carotid plaques using routine blood biomarkers and derived indicators: insights into sex-related risk patterns.
Cardiovascular diabetology
Aug 10, 2025
BACKGROUND: Early detection of vulnerable carotid plaques is critical for stroke prevention. This study aimed to develop a machine learning model based on routine blood tests and derived indices to predict plaque vulnerability and assess sex-specific...
The Predictive Value of Serum Total IgE for Antihistamine Treatment Outcomes in Chinese Patients with Chronic Spontaneous Urticaria.
Acta dermato-venereologica
Aug 3, 2025
Chronic spontaneous urticaria is a common skin disorder with variable treatment responses. Second-generation H1-antihistamines are the first-line treatment for chronic spontaneous urticaria, yet many patients fail to respond to licensed doses. Predic...
METS-VF as a novel predictor of gallstones in U.S. adults: a cross-sectional analysis (NHANES 2017-2020).
BMC gastroenterology
Jul 31, 2025
BACKGROUND AND AIMS: Obesity is a well-established risk factor for gallstone formation, but traditional anthropometric measures (e.g., BMI, waist circumference) inadequately assess metabolically active visceral adiposity. The novel Metabolic Score fo...
Establishment of predictive models for postoperative delirium in elderly patients after knee/hip surgery based on total bilirubin concentration: machine learning algorithms.
BMC anesthesiology
Jul 30, 2025
BACKGROUND: With the aging demographic on the rise, we're seeing a spike in the occurrence of postoperative delirium (POD). Our research aims to delve into the connection between plasma bilirubin levels and postoperative delirium, with the goal of cr...
Development of a machine learning-based prediction model for serious bacterial infections in febrile young infants.
BMJ paediatrics open
Jul 30, 2025
BACKGROUND: To develop and validate machine learning (ML)-based models to predict serious bacterial infections (SBIs) in febrile infants aged ≤90 days.
Artificial intelligence in coronary angiography: benchmarking the diagnostic accuracy of ChatGPT-4o against interventional cardiologists.
Open heart
Jul 20, 2025
BACKGROUND: The integration of artificial intelligence (AI) into medical diagnostics has significantly impacted cardiology by enhancing diagnostic precision and therapeutic strategies. Coronary artery disease continues to be a leading cause of global...
Predictive Value of Tests
Coronary Angiography
Radiographic Image Interpretation, Computer-Assisted
Coronary Artery Disease
Benchmarking
Coronary Vessels
Cardiologists
Reproducibility of Results
Aged
Male
Middle Aged
Generative Artificial Intelligence
Humans
Artificial Intelligence
Retrospective Studies
Female
AI-Driven segmentation and morphogeometric profiling of epicardial adipose tissue in type 2 diabetes.
Cardiovascular diabetology
Jul 18, 2025
BACKGROUND: Epicardial adipose tissue (EAT) is associated with cardiometabolic risk in type 2 diabetes (T2D), but its spatial distribution and structural alterations remain understudied. We aim to develop a shape-aware, AI-based method for automated ...
The application of super-resolution ultrasound radiomics models in predicting the failure of conservative treatment for ectopic pregnancy.
Reproductive biology and endocrinology : RB&E
Jul 17, 2025
BACKGROUND: Conservative treatment remains a viable option for selected patients with ectopic pregnancy (EP), but failure may lead to rupture and serious complications. Currently, serum β-hCG is the main predictor for treatment outcomes, yet its accu...
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...
Machine learning-based prediction of stone-free rate after retrograde intrarenal surgery for lower pole renal stones.
World journal of urology
Jul 12, 2025
BACKGROUND: Lower pole renal stones (LPS) present unique challenges for retrograde intrarenal surgery (RIRS) due to unfavorable anatomical features, often resulting in suboptimal stone-free rates (SFR). Recent advancements in machine learning (ML) of...
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