AIMC Topic: Retrospective Studies
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AI-assisted 3D versus conventional 2D preoperative planning in total hip arthroplasty for Crowe type II-IV high hip dislocation: a two-year retrospective study.
Journal of orthopaedic surgery and research
Aug 20, 2025
BACKGROUND: With the growing complexity of total hip arthroplasty (THA) for high hip dislocation (HHD), artificial intelligence (AI)-assisted three-dimensional (3D) preoperative planning has emerged as a promising tool to enhance surgical accuracy. T...
Machine learning-assisted radiogenomic analysis for miR-15a expression prediction in renal cell carcinoma.
BMC cancer
Aug 20, 2025
BACKGROUND: Renal cell carcinoma (RCC) is a prevalent malignancy with highly variable outcomes. MicroRNA-15a (miR-15a) has emerged as a promising prognostic biomarker in RCC, linked to angiogenesis, apoptosis, and proliferation. Radiogenomics integra...
A development of machine learning models to preoperatively predict insufficient clinical improvement after total knee arthroplasty.
Journal of orthopaedic surgery and research
Aug 20, 2025
BACKGROUND: Identifying patients unlikely to achieve meaningful improvement following total knee arthroplasty (TKA) supports more effective shared decision-making (SDM). This study aimed to develop and validate machine learning (ML) models that preop...
Machine learning-based prediction model for post-stroke cerebral-cardiac syndrome: a risk stratification study.
Scientific reports
Aug 20, 2025
Cerebral-cardiac syndrome (CCS) is a severe cardiac complication following acute ischemic stroke, often associated with adverse outcomes. This study developed and validated a machine learning (ML) model to predict CCS using clinical, laboratory, and ...
The prediction models for the optimal timing of surgical intervention for necrotizing enterocolitis: nomogram vs. five machine learning models.
Pediatric surgery international
Aug 20, 2025
BACKGROUND: Necrotizing enterocolitis (NEC) is one of the most common diseases that pose serious threats to the life of newborns. In clinical practice, NEC is typically treated by surgical intervention, but it is still difficult to identify the timin...
Predicting post-liver transplantation mortality: a retrospective cohort study on risk factor identification and prognostic nomogram construction.
European journal of medical research
Aug 20, 2025
BACKGROUND: To identify risk factors for post-transplant mortality and develop a machine learning-integrated prognostic tool to optimise clinical decision-making in liver transplantation (LT) recipients.
Effect of discontinuing antipsychotic medications on the risk of hospitalization in long-term care: a machine learning-based analysis.
BMC medicine
Aug 20, 2025
BACKGROUND: Antipsychotic medications are frequently prescribed to older residents of long-term care facilities (LTCFs) despite their limited efficacy and considerable safety risks. While discontinuation of these drugs might help reduce their associa...
Predicting in-hospital mortality in ICU patients with lymphoma using machine learning models.
PloS one
Aug 20, 2025
BACKGROUND: Lymphoma is a severe condition with high mortality rates, often requiring ICU admission. Traditional risk stratification tools like SOFA and APACHE scores struggle to capture complex clinical interactions. Machine learning (ML) models off...
Improving risk stratification of PI-RADS 3 + 1 lesions of the peripheral zone: expert lexicon of terms, multi-reader performance and contribution of artificial intelligence.
Cancer imaging : the official publication of the International Cancer Imaging Society
Aug 19, 2025
BACKGROUND: According to PI-RADS v2.1, peripheral PI-RADS 3 lesions are upgraded to PI-RADS 4 if dynamic contrast-enhanced MRI is positive (3+1 lesions), however those lesions are radiologically challenging. We aimed to define criteria by expert cons...
Multimodal imaging deep learning model for predicting extraprostatic extension in prostate cancer using MpMRI and 18 F-PSMA-PET/CT.
Cancer imaging : the official publication of the International Cancer Imaging Society
Aug 19, 2025
OBJECTIVE: This study aimed to construct a multimodal imaging deep learning (DL) model integrating mpMRI and F-PSMA-PET/CT for the prediction of extraprostatic extension (EPE) in prostate cancer, and to assess its effectiveness in enhancing the diagn...
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