AIMC Topic: Retrospective Studies
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Eye movement detection using electrooculography and machine learning in cardiac arrest patients.
Resuscitation
Mar 24, 2025
AIM: To train a machine learning algorithm to identify eye movement from electrooculography (EOG) in cardiac arrest (CA) patients. Neuroprognostication of comatose post-CA patients is challenging, requiring novel biomarkers to guide decision making. ...
Development and validation of a machine learning model to predict hemostatic intervention in patients with acute upper gastrointestinal bleeding.
BMC medical informatics and decision making
Mar 24, 2025
BACKGROUND: Acute upper gastrointestinal bleeding (UGIB) is common in clinical practice and has a wide range of severity. Along with medical therapy, endoscopic intervention is the mainstay treatment for hemostasis in high-risk rebleeding lesions. Pr...
Understanding EMS response times: a machine learning-based analysis.
BMC medical informatics and decision making
Mar 24, 2025
BACKGROUND: Emergency Medical Services (EMS) response times are critical for optimizing patient outcomes, particularly in time-sensitive emergencies. This study explores the multifaceted determinants of EMS response times, leveraging machine learning...
Intelligent detection and grading diagnosis of fresh rib fractures based on deep learning.
BMC medical imaging
Mar 24, 2025
BACKGROUND: Accurate detection and grading of fresh rib fractures are crucial for patient management but remain challenging due to the complexity of rib structures on CT images.
Machine learning prediction of premature death from multimorbidity among people with inflammatory bowel disease: a population-based retrospective cohort study.
CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne
Mar 24, 2025
BACKGROUND: Multimorbidity, the co-occurrence of 2 or more chronic conditions, is important in patients with inflammatory bowel disease (IBD) given its association with complex care plans, poor health outcomes, and excess mortality. Our objectives we...
Technical implications of a novel deep learning system in the segmentation and evaluation of computed tomography angiography before transcatheter aortic valve replacement.
Therapeutic advances in cardiovascular disease
Mar 24, 2025
OBJECTIVE: The goal of this study was to compare the computed tomography angiography scans of the segmentation results from the Cvpilot, 3mensio, and Volume Viewer systems to explore the practicability of the Cvpilot system in the automatic segmentat...
Deep Learning
Aortography
Aortic Valve Stenosis
Aortic Valve
Predictive Value of Tests
Radiographic Image Interpretation, Computer-Assisted
Humans
Multidetector Computed Tomography
Reproducibility of Results
Retrospective Studies
Computed Tomography Angiography
Aged
Female
Transcatheter Aortic Valve Replacement
Aged, 80 and over
Male
Machine learning models for prediction of NPVR ≥80% with HIFU ablation for uterine fibroids.
International journal of hyperthermia : the official journal of European Society for Hyperthermic Oncology, North American Hyperthermia Group
Mar 23, 2025
BACKGROUND: Currently high-intensity focused ultrasound (HIFU) is widely used to treat uterine fibroids (UFs). The aim of this study is to develop a machine learning model that can accurately predict the efficacy of HIFU ablation for UFs, assisting t...
Evaluation and comparison of machine learning algorithms for predicting discharge against medical advice in injured inpatients.
Surgery
Mar 23, 2025
BACKGROUND: Whether the application of machine learning algorithms offers an advantage over logistic regression in forecasting discharge against medical advice occurrences needs to be evaluated.
Integration of AI lesion classification, age, and BI-RADS assessment to reduce benign biopsies on breast ultrasound.
European radiology
Mar 22, 2025
OBJECTIVES: To develop and test AI-integrated biopsy avoidance strategies to improve the specificity of screening breast ultrasound (US).
New approach to specific Alzheimer's disease diagnosis based on plasma biomarkers in a cognitive disorder cohort.
European journal of clinical investigation
Mar 22, 2025
BACKGROUND: The validation of a combination of plasma biomarkers and demographic variables is required to establish reliable cut-offs for Alzheimer's disease diagnosis (AD).
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