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Validation of an artificial intelligence-based prognostic biomarker in patients with oligometastatic Castration-Sensitive prostate cancer.
Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology
Nov 6, 2024
BACKGROUND: There is a need for clinically actionable prognostic and predictive tools to guide the management of oligometastatic castration-sensitive prostate cancer (omCSPC).
Feature Selection and Machine Learning Approaches in Prediction of Current E-Cigarette Use Among U.S. Adults in 2022.
International journal of environmental research and public health
Nov 6, 2024
Feature selection is essentially the process of picking informative and relevant features from a larger collection of features. Few studies have focused on predictors for current e-cigarette use among U.S. adults using feature selection and machine l...
Machine learning models in evaluating the malignancy risk of ovarian tumors: a comparative study.
Journal of ovarian research
Nov 6, 2024
OBJECTIVES: The study aimed to compare the diagnostic efficacy of the machine learning models with expert subjective assessment (SA) in assessing the malignancy risk of ovarian tumors using transvaginal ultrasound (TVUS).
Predictive modeling of preoperative acute heart failure in older adults with hypertension: a dual perspective of SHAP values and interaction analysis.
BMC medical informatics and decision making
Nov 6, 2024
BACKGROUND: In older adults with hypertension, hip fractures accompanied by preoperative acute heart failure significantly elevate surgical risks and adverse outcomes, necessitating timely identification and management to improve patient outcomes.
Computed tomography enterography radiomics and machine learning for identification of Crohn's disease.
BMC medical imaging
Nov 6, 2024
BACKGROUND: Crohn's disease is a severe chronic and relapsing inflammatory bowel disease. Although contrast-enhanced computed tomography enterography is commonly used to evaluate crohn's disease, its imaging findings are often nonspecific and can ove...
Random survival forest algorithm for risk stratification and survival prediction in gastric neuroendocrine neoplasms.
Scientific reports
Nov 6, 2024
This study aimed to construct and assess a machine-learning algorithm designed to forecast survival rates and risk stratification for patients with gastric neuroendocrine neoplasms (gNENs) after diagnosis. Data on patients with gNENs were extracted a...
Artificial intelligence-assisted magnetic resonance imaging technology in the differential diagnosis and prognosis prediction of endometrial cancer.
Scientific reports
Nov 6, 2024
It aimed to analyze the value of deep learning algorithm combined with magnetic resonance imaging (MRI) in the risk diagnosis and prognosis of endometrial cancer (EC). Based on the deep learning convolutional neural network (CNN) architecture residua...
Predictive modeling of COVID-19 mortality risk in chronic kidney disease patients using multiple machine learning algorithms.
Scientific reports
Nov 6, 2024
The coronavirus disease 2019 (COVID-19) has a significant impact on the global population, particularly on individuals with chronic kidney disease (CKD). COVID-19 patients with CKD will face a considerably higher risk of mortality than the general po...
Machine learning model for age-related macular degeneration based on heavy metals: The National Health and Nutrition Examination Survey 2005 to 2008.
Scientific reports
Nov 6, 2024
Age-related macular degeneration (AMD) is the leading cause of blindness in older people in developed countries. It has been suggested that heavy metal exposure may be associated with the development of AMD, but most studies have focused on the effec...
Automatic delineation of cervical cancer target volumes in small samples based on multi-decoder and semi-supervised learning and clinical application.
Scientific reports
Nov 6, 2024
Radiotherapy has been demonstrated to be one of the most significant treatments for cervical cancer, during which accurate and efficient delineation of target volumes is critical. To alleviate the data demand of deep learning and promote the establis...
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