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Predictive accuracy of machine learning models for conservative treatment failure in thoracolumbar burst fractures.
BMC musculoskeletal disorders
Nov 18, 2024
BACKGROUND: The management of patients with thoracolumbar burst fractures remains a topic of debate, with conservative treatment being successful in most cases but not all. This study aimed to assess the utility of machine learning models (MLMs) in p...
Artificial intelligence-based personalized survival prediction using clinical and radiomics features in patients with advanced non-small cell lung cancer.
BMC cancer
Nov 18, 2024
BACKGROUND: Multiple first-line treatment options have been developed for advanced non-small cell lung cancer (NSCLC) in each subgroup determined by predictive biomarkers, specifically driver oncogene and programmed cell death ligand-1 (PD-L1) status...
A novel prediction model for the prognosis of non-small cell lung cancer with clinical routine laboratory indicators: a machine learning approach.
BMC medical informatics and decision making
Nov 18, 2024
BACKGROUND: Lung cancer is characterized by high morbidity and mortality due to the lack of practical early diagnostic and prognostic tools. The present study uses machine learning algorithms to construct a clinical predictive model for non-small cel...
Prediction of esophageal fistula in radiotherapy/chemoradiotherapy for patients with advanced esophageal cancer by a clinical-deep learning radiomics model : Prediction of esophageal fistula in radiotherapy/chemoradiotherapy patients.
BMC medical imaging
Nov 18, 2024
BACKGROUND: Esophageal fistula (EF), a rare and potentially fatal complication, can be better managed with predictive models for personalized treatment plans in esophageal cancers. We aim to develop a clinical-deep learning radiomics model for effect...
Predictive risk models for COVID-19 patients using the multi-thresholding meta-algorithm.
Scientific reports
Nov 18, 2024
This study aims to develop a Machine Learning model to assess the risks faced by COVID-19 patients in a hospital setting, focusing specifically on predicting the complications leading to Intensive Care Unit (ICU) admission or mortality, which are min...
Exploring the Perspectives of Older Adults on a Digital Brain Health Platform Using Natural Language Processing: Cohort Study.
JMIR formative research
Nov 18, 2024
BACKGROUND: Although digital technology represents a growing field aiming to revolutionize early Alzheimer disease risk prediction and monitoring, the perspectives of older adults on an integrated digital brain health platform have not been investiga...
Comparative efficacy of anteroposterior and lateral X-ray based deep learning in the detection of osteoporotic vertebral compression fracture.
Scientific reports
Nov 18, 2024
Magnetic resonance imaging remains the gold standard for diagnosing osteoporotic vertebral compression fractures (OVCF), but the use of X-ray imaging, particularly anteroposterior (AP) and lateral views, is prevalent due to its accessibility and cost...
An arterial spin labeling-based radiomics signature and machine learning for the prediction and detection of various stages of kidney damage due to diabetes.
Frontiers in endocrinology
Nov 18, 2024
OBJECTIVE: The aim of this study was to assess the predictive capabilities of a radiomics signature obtained from arterial spin labeling (ASL) imaging in forecasting and detecting stages of kidney damage in patients with diabetes mellitus (DM), as we...
Perceptions and experiences of Korean American older adults with companion robots through long-term use: a comparative analysis of robot retention vs. return.
Frontiers in public health
Nov 18, 2024
To date, limited research has been conducted on technology use among socially marginalized groups, such as older immigrants who may have limited digital literacy. This pilot study aims to explore Korean American older adults' perceptions and experien...
Machine learning identifies immune-based biomarkers that predict efficacy of anti-angiogenesis-based therapies in advanced lung cancer.
International immunopharmacology
Nov 17, 2024
BACKGROUND: The anti-angiogenic drugs showed remarkable efficacy in the treatment of lung cancer. Nonetheless, the potential roles of the intra-tumoral immune cell abundances and peripheral blood immunological features in prognosis prediction of pati...
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