AIMC Topic: Retrospective Studies
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A Machine Learning Trauma Triage Model for Critical Care Transport.
JAMA network open
Jun 2, 2025
IMPORTANCE: Under austere prehospital conditions, rapid classification of injured patients for intervention or transport is essential for providing lifesaving care. Discerning which patients need care most urgently further allows for optimal allocati...
Accuracy of Artificial Intelligence for Gatekeeping in Referrals to Specialized Care.
JAMA network open
Jun 2, 2025
IMPORTANCE: Integrating artificial intelligence (AI) technologies into gatekeeping holds significant potential, as it efficiently handles repetitive tasks and can process large amounts of information quickly.
Unsupervised learning-based quantitative analysis of CT intratumoral subregions predicts risk stratification of bladder cancer patients.
BMC medicine
Jun 2, 2025
BACKGROUND: Preoperative diagnosis of muscle invasion and American Joint Committee on Cancer (AJCC) stage plays a crucial role in guiding treatment strategies for bladder cancer (BCa). Utilizing quantitative analysis of tumor subregions via CT imagin...
Machine-learning model for predicting left atrial thrombus in patients with paroxysmal atrial fibrillation.
BMC cardiovascular disorders
Jun 2, 2025
OBJECTIVE: Left atrial thrombus (LAT) poses a significant risk for stroke and other thromboembolic complication in patients with atrial fibrillation (AF). This study aimed to evaluate the incidence and predictors of LAT in patients with paroxysmal AF...
Closing the AI generalisation gap by adjusting for dermatology condition distribution differences across clinical settings.
EBioMedicine
Jun 2, 2025
BACKGROUND: Generalisation of artificial intelligence (AI) models to a new setting is challenging. In this study, we seek to understand the robustness of a dermatology (AI) model and whether it generalises from telemedicine cases to a new setting inc...
A Deep Learning-Based Artificial Intelligence Model Assisting Thyroid Nodule Diagnosis and Management: Pilot Results for Evaluating Thyroid Malignancy in Pediatric Cohorts.
Thyroid : official journal of the American Thyroid Association
Jun 2, 2025
Artificial intelligence (AI) models have shown promise in predicting malignant thyroid nodules in adults; however, research on deep learning (DL) for pediatric cases is limited. We evaluated the applicability of a DL-based model for assessing thyroi...
NeoPred: dual-phase CT AI forecasts pathologic response to neoadjuvant chemo-immunotherapy in NSCLC.
Journal for immunotherapy of cancer
May 31, 2025
BACKGROUND: Accurate preoperative prediction of major pathological response or pathological complete response after neoadjuvant chemo-immunotherapy remains a critical unmet need in resectable non-small-cell lung cancer (NSCLC). Conventional size-base...
Deep learning reconstruction for T2-weighted and contrast-enhanced T1-weighted magnetic resonance enterography imaging in patients with Crohn's disease: Assessment of image quality and clinical utility.
Clinical imaging
May 30, 2025
PURPOSE: To investigate the image quality of deep learning-reconstructed T2-weighted half-Fourier single-shot turbo spin echo (DL T2 HASTE) and contrast-enhanced T1-weighted volumetric interpolated breath-hold examination (DL T1 VIBE) of magnetic res...
Multi-spatial-attention U-Net: a novel framework for automated gallbladder segmentation on CT images.
BMC medical imaging
May 30, 2025
OBJECTIVE: This study aimed to construct a novel model, Multi-Spatial Attention U-Net (MSAU-Net) by incorporating our proposed Multi-Spatial Attention (MSA) block into the U-Net for the automated segmentation of the gallbladder on CT images.
Radiomics-based differentiation of upper urinary tract urothelial and renal cell carcinoma in preoperative computed tomography datasets.
BMC medical imaging
May 30, 2025
BACKGROUND: To investigate a non-invasive radiomics-based machine learning algorithm to differentiate upper urinary tract urothelial carcinoma (UTUC) from renal cell carcinoma (RCC) prior to surgical intervention.
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