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Similar failures of consideration arise in human and machine planning.
Cognition
Mar 13, 2025
Humans are remarkably efficient at decision making, even in "open-ended" problems where the set of possible actions is too large for exhaustive evaluation. Our success relies, in part, on processes for calling to mind the right candidate actions. Whe...
Machine Learning-Based localization of the epileptogenic zone using High-Frequency oscillations from SEEG: A Real-World approach.
Journal of clinical neuroscience : official journal of the Neurosurgical Society of Australasia
Mar 13, 2025
INTRODUCTION: Localizing the epileptogenic zone (EZ) using Stereo EEG (SEEG) is often challenging through manual analysis. Even methods based on signal analysis have limitations in identifying the EZ, particularly in patients with neocortical epileps...
Machine learning prediction of right ventricular volume and ejection fraction from two-dimensional echocardiography in patients with pulmonary regurgitation.
The international journal of cardiovascular imaging
Mar 13, 2025
Right ventricular (RV) end-diastolic volume (RVEDV) and ejection fraction (RVEF) by cardiac MRI (cMRI) guide management in chronic pulmonary regurgitation (PR). Two-dimensional echocardiography suboptimally correlate with RV volumes. This study teste...
Adult
Male
Stroke Volume
Echocardiography
Retrospective Studies
Female
Reproducibility of Results
Young Adult
Ventricular Dysfunction, Right
Image Interpretation, Computer-Assisted
Humans
Severity of Illness Index
Ventricular Function, Right
Machine Learning
Adolescent
Pulmonary Valve Insufficiency
Prognosis
Chronic Disease
Predictive Value of Tests
Posttraumatic Arthritis After Anterior Cruciate Ligament Injury: Machine Learning Comparison Between Surgery and Nonoperative Management.
The American journal of sports medicine
Mar 13, 2025
BACKGROUND: Nonoperative and operative management techniques after anterior cruciate ligament (ACL) injury are both appropriate treatment options for selected patients. However, the subsequent development of posttraumatic knee osteoarthritis (PTOA) r...
Prediction of Chemotherapy Response in Locally Advanced Breast Cancer Patients at Pre-Treatment Using CT Textural Features and Machine Learning: Comparison of Feature Selection Methods.
Tomography (Ann Arbor, Mich.)
Mar 13, 2025
RATIONALE: Neoadjuvant chemotherapy (NAC) is a key element of treatment for locally advanced breast cancer (LABC). Predicting the response of NAC for patients with LABC before initiating treatment would be valuable to customize therapies and ensure t...
Development and evaluation of a deep learning framework for pelvic and sacral tumor segmentation from multi-sequence MRI: a retrospective study.
Cancer imaging : the official publication of the International Cancer Imaging Society
Mar 13, 2025
BACKGROUND: Accurate segmentation of pelvic and sacral tumors (PSTs) in multi-sequence magnetic resonance imaging (MRI) is essential for effective treatment and surgical planning.
Machine learning based model for the early detection of Gestational Diabetes Mellitus.
BMC medical informatics and decision making
Mar 13, 2025
BACKGROUND: Gestational Diabetes Mellitus (GDM) is one of the most common medical complications during pregnancy. In the Gulf region, the prevalence of GDM is higher than in other parts of the world. Thus, there is a need for the early detection of G...
Machine learning-derived diagnostic model of epithelial ovarian cancer based on gut microbiome signatures.
Journal of translational medicine
Mar 13, 2025
BACKGROUND: Prior studies have elucidated that alterations in gut microbiota are associated with a spectrum of tumors and metabolic disorders. However, the diagnostic value of gut microbiota in epithelial ovarian cancer remains insufficiently investi...
Integration of artificial intelligence in radiology education: a requirements survey and recommendations from faculty radiologists, residents, and medical students.
BMC medical education
Mar 13, 2025
BACKGROUND: To investigate the perspectives and expectations of faculty radiologists, residents, and medical students regarding the integration of artificial intelligence (AI) in radiology education, a survey was conducted to collect their opinions a...
Integration of intratumoral and peritumoral CT radiomic features with machine learning algorithms for predicting induction therapy response in locally advanced non-small cell lung cancer.
BMC cancer
Mar 13, 2025
OBJECTIVES: To extract intratumoral, peritumoral, and integrated intratumoral-peritumoral CT radiomic features, develop multi-source radiomic models using various machine learning algorithms to identify the optimal model, and integrate clinical facto...
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