The British journal of social psychology
Jan 1, 2025
The burgeoning progress of cutting-edge technology paradoxically evokes nostalgia. How does this emotion influence responses to innovative technology, such as Artificial Intelligence (AI)? We hypothesized that two pathways operate concurrently. First...
The general aggression model (GAM) suggests that cyber-aggression stems from individual characteristics and situational contexts. Previous studies have focused on limited factors using linear models, leading to oversimplified predictions. This study ...
OBJECTIVES: The purpose of this study was to propose a machine learning model and assess its ability to classify temporomandibular joint (TMJ) disc displacements on MR T1-weighted and proton density-weighted images.
Journal of the American Medical Informatics Association : JAMIA
Jan 1, 2025
OBJECTIVES: Successful implementation of machine learning-augmented clinical decision support systems (ML-CDSS) in perioperative care requires the prioritization of patient-centric approaches to ensure alignment with societal expectations. We assesse...
Journal of cataract and refractive surgery
Jan 1, 2025
PURPOSE: To design formulas for predicting postoperative vaults in vertical implantable collamer lens (ICL) implantation and to achieve more precise predictions using machine learning models.
OBJECTIVES: This study aimed to clarify the performance of MRI-based deep learning classification models in diagnosing temporomandibular joint osteoarthritis (TMJ-OA) and to compare the developed diagnostic assistance with human observers.
Journal of the American Medical Informatics Association : JAMIA
Jan 1, 2025
BACKGROUND: Acute hepatic porphyria (AHP) is a group of rare but treatable conditions associated with diagnostic delays of 15 years on average. The advent of electronic health records (EHR) data and machine learning (ML) may improve the timely recogn...
BACKGROUND AND HYPOTHESIS: Schizophrenia (SZ) is a prevalent mental disorder that imposes significant health burdens. Diagnostic accuracy remains challenging due to clinical subjectivity. To address this issue, we explore magnetic resonance imaging (...
The study aimed to compare the morphometric and morphologic analyses of the bone structures of temporomandibular joint and masticatory muscles on Cone beam computed tomography (CBCT) in 62 healthy subjects and 33 subjects with temporomandibular dysfu...
We investigated the impact of donor characteristics on outcomes in allogeneic hematopoietic cell transplantation (HCT) recipients using a novel machine learning approach, the Nonparametric Failure Time Bayesian Additive Regression Trees (NFT BART). N...
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