AIMC Topic: Aged
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Developing a machine learning-based predictive model for levothyroxine dosage estimation in hypothyroid patients: a retrospective study.
Frontiers in endocrinology
Mar 14, 2025
Hypothyroidism, a common endocrine disorder, has a high incidence in women and increases with age. Levothyroxine (LT4) is the standard therapy; however, achieving clinical and biochemical euthyroidism is challenging. Therefore, developing an accurate...
An explainable web application based on machine learning for predicting fragility fracture in people living with HIV: data from Beijing Ditan Hospital, China.
Frontiers in cellular and infection microbiology
Mar 14, 2025
PURPOSE: This study aimed to develop and validate a novel web-based calculator using machine learning algorithms to predict fragility fracture risk in People living with HIV (PLWH), who face increased morbidity and mortality from such fractures.
Automatic Detection of Cognitive Impairment in Patients With White Matter Hyperintensity Using Deep Learning and Radiomics.
American journal of Alzheimer's disease and other dementias
Mar 14, 2025
White matter hyperintensity (WMH) is associated with cognitive impairment. In this study, 79 patients with WMH from hospital 1 were randomly divided into a training set (62 patients) and an internal validation set (17 patients). In addition, 29 WMH p...
Deep learning for the prediction of acute kidney injury after coronary angiography and intervention in patients with chronic kidney disease: a model development and validation study.
Renal failure
Mar 13, 2025
BACKGROUND: Patients with chronic kidney disease (CKD) are considered the primary population at risk for post-contrast acute kidney injury (PC-AKI), yet there are few predictive tools specifically designed for this vulnerable population.
Risk of bias assessment of post-stroke mortality machine learning predictive models: Systematic review.
Journal of stroke and cerebrovascular diseases : the official journal of National Stroke Association
Mar 13, 2025
BACKGROUND: Stroke is a major cause of mortality and permanent disability worldwide. Precise prediction of post-stroke mortality is essential for guiding treatment decisions and rehabilitation planning. The ability of Machine learning models to proce...
DCE-MRI based deep learning analysis of intratumoral subregion for predicting Ki-67 expression level in breast cancer.
Magnetic resonance imaging
Mar 13, 2025
OBJECTIVE: To evaluate whether deep learning (DL) analysis of intratumor subregion based on dynamic contrast-enhanced MRI (DCE-MRI) can help predict Ki-67 expression level in breast cancer.
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.
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...
Biological age prediction and NAFLD risk assessment: a machine learning model based on a multicenter population in Nanchang, Jiangxi, China.
BMC gastroenterology
Mar 13, 2025
BACKGROUND: The objective was to develop a biological age prediction model (NC-BA) for the Chinese population to enrich the relevant studies in this population. And to investigate the association between accelerated age and NAFLD.
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