AIMC Topic: Adult
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Deep learning for tibial plateau fracture detection and classification.
The Knee
Mar 1, 2025
BACKGROUND: Deep learning (DL) has been shown to be successful in interpreting radiographs and aiding in fracture detection and classification. However, no study has aimed to develop a computer vision model for tibia plateau fractures using the Schat...
Predicting 30-day mortality in hemophagocytic lymphohistiocytosis: clinical features, biochemical parameters, and machine learning insights.
Annals of hematology
Mar 1, 2025
This study aims to evaluate the clinical characteristics and biochemical parameters of hemophagocytic lymphohistiocytosis (HLH) patients to predict 30-day mortality. Parameters analyzed include lymphocyte count (L), platelet count (PLT), total protei...
An interpretable machine learning approach for detecting psoriatic arthritis in a UK primary care psoriasis cohort using electronic health records from the Clinical Practice Research Datalink.
Annals of the rheumatic diseases
Mar 1, 2025
OBJECTIVES: Develop an interpretable machine learning model to detect patients with newly diagnosed psoriatic arthritis (PsA) in a cohort of psoriasis patients and identify important clinical indicators of PsA in primary care.
Artificial intelligence-driven 3D MRI of lumbosacral nerve root anomalies: accuracy, incidence, and clinical utility.
Neuroradiology
Mar 1, 2025
PURPOSE: Lumbosacral nerve root anomalies are relatively rare but can be a risk factor for intraoperative nerve injury. However, it is often difficult to evaluate them with preoperative imaging. We developed a software that automatically generates th...
Automated Detection of Keratorefractive Laser Surgeries on Optical Coherence Tomography Using Deep Learning.
Journal of refractive surgery (Thorofare, N.J. : 1995)
Mar 1, 2025
PURPOSE: To report a deep learning neural network on anterior segment optical coherence tomography (AS-OCT) for automated detection of different keratorefractive laser surgeries-including laser in situ keratomileusis with femtosecond microkeratome (f...
Evaluation by dental professionals of an artificial intelligence-based application to measure alveolar bone loss.
BMC oral health
Mar 1, 2025
BACKGROUND: Several commercial programs incorporate artificial intelligence in diagnosis, but very few dental professionals have been surveyed regarding its acceptability and usability. Furthermore, few have explored how these advances might be incor...
Predicting responsiveness to fixed-dose methylene blue in adult patients with septic shock using interpretable machine learning: a retrospective study.
Scientific reports
Mar 1, 2025
This study aimed to develop an interpretable machine learning model to predict methylene blue (MB) responsiveness in adult patients with refractory septic shock and to identify key factors influencing MB responsiveness using the SHapley Additive exPl...
Machine-learning models for the prediction of ideal surgical outcomes in patients with adult spinal deformity.
The bone & joint journal
Mar 1, 2025
AIMS: Adult spinal deformity (ASD) surgery can reduce pain and disability. However, the actual surgical efficacy of ASD in doing so is far from desirable, with frequent complications and limited improvement in quality of life. The accurate prediction...
Artificial intelligence-assisted precise preoperative prediction of lateral cervical lymph nodes metastasis in papillary thyroid carcinoma via a clinical-CT radiomic combined model.
International journal of surgery (London, England)
Mar 1, 2025
OBJECTIVES: This study aimed to develop an artificial intelligence-assisted model for the preoperative prediction of lateral cervical lymph node metastasis (LCLNM) in papillary thyroid carcinoma (PTC) using computed tomography (CT) radiomics, providi...
Comprehensive evaluation of pipelines for classification of psychiatric disorders using multi-site resting-state fMRI datasets.
Neural networks : the official journal of the International Neural Network Society
Feb 28, 2025
Objective classification biomarkers that are developed using resting-state functional magnetic resonance imaging (rs-fMRI) data are expected to contribute to more effective treatment for psychiatric disorders. Unfortunately, no widely accepted biomar...
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