AIMC Topic: Retrospective Studies
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Impact of Photon-counting Detector Computed Tomography on a Quantitative Interstitial Lung Disease Machine Learning Model.
Journal of thoracic imaging
May 1, 2025
PURPOSE: Compare the impact of photon-counting detector computed tomography (PCD-CT) to conventional CT on an interstitial lung disease (ILD) quantitative machine learning (QML) model.
Predicting Gene Comutation of EGFR and TP53 by Radiomics and Deep Learning in Patients With Lung Adenocarcinomas.
Journal of thoracic imaging
May 1, 2025
PURPOSE: This study was designed to construct progressive binary classification models based on radiomics and deep learning to predict the presence of epidermal growth factor receptor ( EGFR ) and TP53 mutations and to assess the models' capacities t...
Gender Authorship Among Urology Artificial Intelligence Publications: A 10-Year Retrospective Analysis.
Urology
Apr 30, 2025
We aim to characterize gender authorship in urology-related artificial intelligence (AI) research. A retrospective review was performed using MEDLINE, Embase, and Web of Science (Clarivate) databases (2014-2024). First and senior author gender was es...
Machine learning-based prediction of postoperative pancreatic fistula after laparoscopic pancreaticoduodenectomy.
BMC surgery
Apr 30, 2025
BACKGROUND: Clinically relevant postoperative pancreatic fistula (CR-POPF) following laparoscopic pancreaticoduodenectomy (LPD) is a critical complication that significantly worsens patient outcomes. However, the heterogeneity of its risk factors and...
Clinical assessment of the criticality index - dynamic, a machine learning prediction model of future care needs in pediatric inpatients.
PloS one
Apr 30, 2025
OBJECTIVE: To assess patient characteristics and care factors that are associated with correct and incorrect predictions of future care locations (ICU vs. non-ICU) by the Criticality Index-Dynamic (CI-D), with the goal of enhancing the CI-D.
A machine learning tool for prediction of vertebral compression fracture following stereotactic body radiation therapy for spinal metastases.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Apr 29, 2025
BACKGROUND AND PURPOSE: The most common adverse event following spine stereotactic body radiotherapy (SBRT) is vertebral compression fracture (VCF). There is interest in the development of patient-specific tools that can predict those at high risk of...
Clinical Validation of a Noninvasive Multi-Omics Method for Multicancer Early Detection in Retrospective and Prospective Cohorts.
The Journal of molecular diagnostics : JMD
Apr 29, 2025
Recent studies highlight the promise of blood-based multicancer early detection (MCED) tests for identifying asymptomatic patients with cancer. However, most focus on a single cancer hallmark, thus limiting effectiveness because of cancer's heterogen...
B lymphocyte subset-based stratification in primary Sjögren's syndrome: implications for lymphoma risk and personalized treatment.
Clinical rheumatology
Apr 29, 2025
OBJECTIVE: This study aimed to perform a detailed stratification analysis of B lymphocyte subsets in patients with primary Sjögren's syndrome (pSS) and to investigate their associations with lymphoma risk, clinical phenotypes, and disease activity.
Development and validation of a novel chronic pancreatitis pathological grade based on artificial intelligence.
Pancreatology : official journal of the International Association of Pancreatology (IAP) ... [et al.]
Apr 29, 2025
BACKGROUND: Effective chronic pancreatitis (CP) treatment requires accurate severity evaluation, but no histopathology grading system exists. This study aimed to develop and validate a novel CP pathological grade (Histopathology-derived CPpG) using q...
Intelligent predictive risk assessment and management of sarcopenia in chronic disease patients using machine learning and a web-based tool.
European journal of medical research
Apr 29, 2025
BACKGROUND: Individuals with chronic diseases are at higher risk of sarcopenia, and precise prediction is essential for its prevention. This study aims to develop a risk scoring model using longitudinal data to predict the probability of sarcopenia i...
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