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Development and validation of interpretable machine learning models to predict glomerular filtration rate in chronic kidney disease Colombian patients.
Annals of clinical biochemistry
Sep 21, 2024
BACKGROUND: ML predictive models have shown their capability to improve risk prediction and assist medical decision-making, nevertheless, there is a lack of accuracy systems to early identify future rapid CKD progressors in Colombia and even in South...
Optimized machine learning model for predicting unplanned reoperation after rectal cancer anterior resection.
European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Sep 21, 2024
BACKGROUND: Unplanned reoperation (URO) after surgery adversely affects the quality of life and prognosis of patients undergoing anterior resection for rectal cancer. This study aims to meet the urgent need for reliable predictive tools by developing...
Exploration of fractional flow reservation score based on artificial intelligence post-processing for coronary artery lesions in patients with diabetes and coronary heart disease.
SLAS technology
Sep 21, 2024
In order to evaluate the relationship between coronary heart disease (CHD) and fractional flow reservation (FFR) in patients with different levels of CHD and diabetes, this paper used AI (artificial intelligence) post-processing technology to detect ...
Progression to refractory status epilepticus: A machine learning analysis by means of classification and regression tree analysis.
Epilepsy & behavior : E&B
Sep 21, 2024
BACKGROUND AND OBJECTIVES: to identify predictors of progression to refractory status epilepticus (RSE) using a machine learning technique.
Human-AI collaboration improves adults' oral biomechanical functions: A multi-centre, self-controlled clinical trial.
Journal of dentistry
Sep 21, 2024
OBJECTIVES: Maintenance of oral muscle functions is important for survival and communication. Utilizing Artificial Intelligence (AI) as a self-health-management material has shown promise. Here we developed a functional and AI-enabled smartphone e-Or...
Enhanced Plaque Stabilization Effects of Alirocumab　- Insights From Artificial Intelligence-Aided Optical Coherence Tomography Analysis of the Alirocumab for Thin-Cap Fibroatheroma in Patients With Coronary Artery Disease Estimated by Optical Coherence Tomography (ALTAIR) Study.
Circulation journal : official journal of the Japanese Circulation Society
Sep 21, 2024
BACKGROUND: Proprotein convertase subtilisin/kexin type 9 inhibitors stabilize vulnerable plaque, reducing cardiovascular events. However, manual optical coherence tomography (OCT) analysis of drug efficacy is challenging because of signal attenuatio...
Comparative evaluation of machine learning models in predicting overall survival for nasopharyngeal carcinoma using F-FDG PET-CT parameters.
Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico
Sep 20, 2024
PURPOSE: The objective of this study is to assess the prognostic efficacy of F-fluorodeoxyglucose (F-FDG) positron emission tomography/computed tomography (PET-CT) parameters in nasopharyngeal carcinoma (NPC) and identify the best machine learning (M...
AI-based lumbar central canal stenosis classification on sagittal MR images is comparable to experienced radiologists using axial images.
European radiology
Sep 20, 2024
OBJECTIVES: The assessment of lumbar central canal stenosis (LCCS) is crucial for diagnosing and planning treatment for patients with low back pain and neurogenic pain. However, manual assessment methods are time-consuming, variable, and require axia...
AI-Safe-C score: Assessing liver-related event risks in patients without cirrhosis after successful direct-acting antiviral treatment.
Journal of hepatology
Sep 20, 2024
BACKGROUND & AIMS: Direct-acting antivirals (DAAs) have considerably improved chronic hepatitis C (HCV) treatment; however, follow-up after sustained virological response (SVR) typically neglects the risk of liver-related events (LREs). This study in...
Exploring Deep Learning Applications using Ultrasound Single View Cines in Acute Gallbladder Pathologies: Preliminary Results.
Academic radiology
Sep 20, 2024
RATIONALE AND OBJECTIVES: In this preliminary study, we aimed to develop a deep learning model using ultrasound single view cines that distinguishes between imaging of normal gallbladder, non-urgent cholelithiasis, and acute calculous cholecystitis r...
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