AIMC Topic: Retrospective Studies
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Diagnostic performances of hysteroscopy in post-remission surveillance of patients treated conservatively for endometrial cancer and atypical hyperplasia: a cohort study.
European journal of obstetrics, gynecology, and reproductive biology
Jun 4, 2025
OBJECTIVE: Hysteroscopy is commonly used for diagnosing benign endometrial conditions, but its diagnostic performance in malignancies post-treatment surveillance has not been evaluated. This study evaluated the correlation between hysteroscopic appea...
Impact of AI-Generated ADC Maps on Computer-Aided Diagnosis of Prostate Cancer: A Feasibility Study.
Academic radiology
Jun 4, 2025
RATIONALE AND OBJECTIVES: To evaluate the impact of AI-generated apparent diffusion coefficient (ADC) maps on diagnostic performance of a 3D U-Net AI model for prostate cancer (PCa) detection and segmentation at biparametric MRI (bpMRI).
Predicting mortality risk following major lower extremity amputation using machine learning.
Journal of vascular surgery
Jun 4, 2025
OBJECTIVE: Major lower extremity amputation for advanced vascular disease involves significant perioperative risks. Although outcome prediction tools could aid in clinical decision-making, they remain limited. To address this, we developed machine le...
Associations between all-cause and ischemic heart disease mortality and long-term ambient ultrafine particles exposure: a comparison of statistical and machine learning exposure models.
Environment international
Jun 4, 2025
BACKGROUND: Evidence about the health effects of ultrafine particles (UFPs) remains limited, especially due to challenges in estimating exposure in epidemiological studies.
UNIK (Urologic Non-Neoplastic Investigation of Kidneys): a machine learning approach to decode benign lesion.
World journal of urology
Jun 4, 2025
PURPOSE: Predicting the likelihood of benign neoplasia in patients with suspected renal cell carcinoma (RCC) is a cornerstone of presurgical planning. We sought to create and validate U.N.I.K., a machine learning (ML) model capable of predicting beni...
Machine learning models for predicting severe acute kidney injury in patients with sepsis-induced myocardial injury.
Scientific reports
Jun 4, 2025
Severe acute kidney injury (sAKI) is a prevalent and serious complication among patients with sepsis-induced myocardial injury (SIMI). Prompt and early prediction of sAKI has an important role in timely intervention, ultimately improving the patients...
Development of a machine learning-based model to predict urethral recurrence following radical cystectomy: a multicentre retrospective study and updated meta-analysis.
Scientific reports
Jun 4, 2025
Urethral recurrence (UR) following radical cystectomy for bladder cancer represents an aggressive disease failure with typically poor survival outcomes. Our study aimed to assess the predictive risk factors for UR, to develop and validate an easy-to-...
Developing a CT radiomics-based model for assessing split renal function using machine learning.
Japanese journal of radiology
Jun 3, 2025
PURPOSE: This study aims to investigate whether non-contrast computed tomography radiomics can effectively reflect split renal function and to develop a radiomics model for its assessment.
Uncovering nonlinear patterns in time-sensitive prehospital breathing emergencies: an exploratory machine learning study.
BMC medical informatics and decision making
Jun 3, 2025
BACKGROUND: Timely prehospital care is crucial for patients presenting with high-risk time-sensitive (HRTS) conditions. However, the interplay between response time and demographic factors in patients with breathing problems remains insufficiently un...
Machine Learning-Assisted Prediction of Persistent Incomplete Occlusion in Intracranial Aneurysms From Angiographic Parametric Imaging-Derived Features.
Academic radiology
Jun 2, 2025
RATIONALE AND OBJECTIVES: To develop machine-learning (ML) models incorporating angiographic parametric imaging (API)-derived parameters in predicting persistent incomplete occlusion of intracranial aneurysms (IAs) after flow diverter (FD) treatment.
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