AIMC Topic: Retrospective Studies
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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
Radiographic Image Interpretation, Computer-Assisted
Reproducibility of Results
Humans
Aortic Valve Stenosis
Multidetector Computed Tomography
Aged
Aortic Valve
Retrospective Studies
Computed Tomography Angiography
Predictive Value of Tests
Aged, 80 and over
Transcatheter Aortic Valve Replacement
Female
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.
Evaluating the prognostic significance of artificial intelligence-delineated gross tumor volume and prostate volume measurements for prostate radiotherapy.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Mar 22, 2025
BACKGROUND AND PURPOSE: Artificial intelligence (AI) may extract prognostic information from MRI for localized prostate cancer. We evaluate whether AI-derived prostate and gross tumor volume (GTV) are associated with toxicity and oncologic outcomes a...
Learning from the machine: is diabetes in adults predicted by lifestyle variables? A retrospective predictive modelling study of NHANES 2007-2018.
BMJ open
Mar 22, 2025
OBJECTIVES: This study aimed to compare the performance of five machine learning algorithms to predict diabetes mellitus based on lifestyle factors (diet and physical activity).
Machine learning-based model for predicting all-cause mortality in severe pneumonia.
BMJ open respiratory research
Mar 22, 2025
BACKGROUND: Severe pneumonia has a poor prognosis and high mortality. Current severity scores such as Acute Physiology and Chronic Health Evaluation (APACHE-II) and Sequential Organ Failure Assessment (SOFA), have limited ability to help clinicians i...
Machine learning-based radiomics using MRI to differentiate early-stage Duchenne and Becker muscular dystrophy in children.
BMC musculoskeletal disorders
Mar 22, 2025
OBJECTIVES: Duchenne muscular dystrophy (DMD) and Becker muscular dystrophy (BMD) present similar symptoms in the early stage, complicating their differentiation. This study aims to develop a classification model using radiomic features from MRI T2-w...
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