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Body movements as biomarkers: Machine Learning-based prediction of HPA axis reactivity to stress.
Psychoneuroendocrinology
Jun 26, 2025
Body movements and posture provide valuable insights into stress responses, yet their relationship with endocrine biomarkers of the stress response remains underexplored. This study investigates whether movement patterns during the Trier Social Stres...
Predicting brain metastases in EGFR-positive lung adenocarcinoma patients using pre-treatment CT lung imaging data.
European journal of radiology
Jun 26, 2025
OBJECTIVES: This study aims to establish a dual-feature fusion model integrating radiomic features with deep learning features, utilizing single-modality pre-treatment lung CT image data to achieve early warning of brain metastasis (BM) risk within 2...
Deep transfer learning radiomics combined with explainable machine learning for preoperative thymoma risk prediction based on CT.
European journal of radiology
Jun 26, 2025
OBJECTIVE: To develop and validate a computerized tomography (CT)‑based deep transfer learning radiomics model combined with explainable machine learning for preoperative risk prediction of thymoma.
Design and optimization of an automatic deep learning-based cerebral reperfusion scoring (TICI) using thrombus localization.
Journal of neuroradiology = Journal de neuroradiologie
Jun 26, 2025
BACKGROUND: The Thrombolysis in Cerebral Infarction (TICI) scale is widely used to assess angiographic outcomes of mechanical thrombectomy despite significant variability. Our objective was to create and optimize an artificial intelligence (AI)-based...
The Cost-Effectiveness of an Artificial Intelligence-Based Population-Wide Screening Program for Primary Open-Angle Glaucoma in The Netherlands.
Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
Jun 26, 2025
OBJECTIVES: Population-wide screening for primary open-angle glaucoma (glaucoma) is typically not cost-effective because of low prevalence and high costs. We evaluated the cost-effectiveness of repeated artificial intelligence (AI)-based glaucoma scr...
Using Machine Learning to Match Clients and Therapy Providers: Evaluating Clinical Quality and Cost of Care.
Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
Jun 26, 2025
OBJECTIVES: Matching clients in need of mental healthcare with providers who will deliver high quality treatment presents a substantial challenge. Machine learning models hold potential for predicting the best pairings from a multitude of data points...
Developing interpretable machine learning models to predict length of stay and disposition decision for adult patients in emergency departments.
BMJ health & care informatics
Jun 26, 2025
OBJECTIVE: Machine learning (ML) models have emerged as tools to predict length of stay (LOS) and disposition decision (DD) in emergency departments (EDs) to combat overcrowding. However, site-specific ML models are not transferable to different site...
Predictive modeling for early detection of refractory esophageal stricture following esophageal atresia surgery: insight from a machine learning study.
Pediatric surgery international
Jun 26, 2025
BACKGROUND: Refractory esophageal stricture (RES) presents a challenging complication after esophageal atresia (EA) repair. Earlier identification of patients with RES could help clinical decision-making. However, there are currently limited articles...
Prognostic predictions in psychosis: exploring the complementary role of machine learning models.
BMJ mental health
Jun 26, 2025
BACKGROUND: Predicting outcomes in schizophrenia spectrum disorders is challenging due to the variability of individual trajectories. While machine learning (ML) shows promise in outcome prediction, it has not yet been integrated into clinical practi...
Exploring semantic grounding in the posterior parietal cortex.
Brain structure & function
Jun 26, 2025
This study examines the evolving perspective on semantic processing, which has shifted from the traditional view of an isolated semantic memory system to one that recognizes the involvement of dynamic, distributed neural networks. Recent evidence sup...
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