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Integrating AI in medical education: a comprehensive study of medical students' attitudes, concerns, and behavioral intentions.
BMC medical education
Apr 23, 2025
BACKGROUND: To analyze medical students' perceptions, trust, and attitudes toward artificial intelligence (AI) in medical education, and explore their willingness to integrate AI in learning and teaching practices.
Torg-Pavlov ratio qualification to diagnose developmental cervical spinal stenosis based on HRViT neural network.
BMC musculoskeletal disorders
Apr 23, 2025
BACKGROUND: Developing computer-assisted methods to measure the Torg-Pavlov ratio (TPR), defined as the ratio of the sagittal diameter of the cervical spinal canal to the sagittal diameter of the corresponding vertebral body on lateral radiographs, c...
Vascular-related biological stress, DNA methylation, allostatic load and domain-specific cognition: an integrated machine learning and causal inference approach.
BMC neurology
Apr 23, 2025
BACKGROUND: Vascular disease in aging populations spans a wide range of disorders including strokes, circulation disorders and hypertension. As individuals age, vascular disorders co-occur and hence exert combined effects. In the present study we int...
Development and validation of a machine learning risk prediction model for asthma attacks in adults in primary care.
NPJ primary care respiratory medicine
Apr 23, 2025
Primary care consultations provide an opportunity for patients and clinicians to assess asthma attack risk. Using a data-driven risk prediction tool with routinely collected health records may be an efficient way to aid promotion of effective self-ma...
Expectations of Intensive Care Physicians Regarding an AI-Based Decision Support System for Weaning From Continuous Renal Replacement Therapy: Predevelopment Survey Study.
JMIR medical informatics
Apr 23, 2025
BACKGROUND: Critically ill patients in intensive care units (ICUs) require continuous monitoring, generating vast amounts of data. Clinical decision support systems (CDSS) leveraging artificial intelligence (AI) technologies have shown promise in imp...
Association of acute kidney injury with 1-year mortality in granulomatosis with polyangiitis patients: a cohort study using mediation analyses and machine learning.
Rheumatology international
Apr 23, 2025
To investigate the correlation between acute kidney injury (AKI) and 1-year mortality in patients with granulomatosis with polyangiitis (GPA). Clinical data for GPA patients were extracted from the MIMIC-IV (version 3.0) database. Logistic and Cox re...
Constructing a neural network model based on tumor-infiltrating lymphocytes (TILs) to predict the survival of hepatocellular carcinoma patients.
PeerJ
Apr 23, 2025
BACKGROUND: Hepatocellular carcinoma (HCC) is the most common primary liver cancer worldwide, and early pathological diagnosis is crucial for formulating treatment plans. Despite the widespread attention to pathology in the treatment of HCC patients,...
The establishment of machine learning prognostic prediction models for pineal region tumors based on SEER-A multicenter real-world study.
European journal of surgical oncology : the journal of the European Society of Surgical Oncology and the British Association of Surgical Oncology
Apr 22, 2025
BACKGROUND: Pineal region tumors (PRT) are rare intracranial neoplasms with diverse pathological types and growth characteristics, leading to varied clinical manifestations. This study aims to develop machine learning (ML) models for survival predict...
Radiomics-based analysis of choroid plexus abnormalities in neuromyelitis optica spectrum disorders and multiple sclerosis and their clinical implications.
Multiple sclerosis and related disorders
Apr 22, 2025
BACKGROUND: The choroid plexus (CP) is closely linked to inflammation in multiple sclerosis (MS). While the CP volume is enlarged in MS compared with healthy controls (HC), no such changes are observed in neuromyelitis optica spectrum disorder (NMOSD...
Predicting responsiveness to a dialectical behaviour therapy skills training app for recurrent binge eating: A machine learning approach.
Behaviour research and therapy
Apr 22, 2025
OBJECTIVE: Smartphone applications (apps) show promise as an effective and scalable intervention modality for disordered eating, yet responsiveness varies considerably. The ability to predict user responses to app-based interventions is currently lim...
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