AIMC Topic: Machine Learning
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Comprehensive predictive modeling in subarachnoid hemorrhage: integrating radiomics and clinical variables.
Neurosurgical review
Jun 24, 2025
Subarachnoid hemorrhage (SAH) is a severe condition with high morbidity and long-term neurological consequences. Radiomics, by extracting quantitative features from Computed Tomograhpy (CT) scans, may reveal imaging biomarkers predictive of outcomes....
Machine learning model for the prediction of postoperative acute kidney injury (AKI) in neonates undergoing digestive surgery.
Pediatric surgery international
Jun 24, 2025
OBJECTIVE: The aim of our study is to determine the main predictors of postoperative AKI in neonates using machine learning models compared with the logistic regression model.
Learning from small datasets-review of workshop 6 of the 10th International BCI Meeting 2023.
Journal of neural engineering
Jun 24, 2025
In a brain-computer interface (BCI), a primary objective is to reduce calibration time by recording as few as possible novel data points to (re-)train decoder models.Minimizing the calibration can be crucial for enhancing the usability of a BCI appli...
Synergistic application of artificial intelligence and response surface methodology for predicting and enhancing in vitro tuber production of potato (Solanum tuberosum).
PloS one
Jun 24, 2025
In vitro regeneration of potato tubers is highly significant in modern agriculture as it offers efficient propagation, genetic enhancement, and pathogen-free seed production. This study aimed to optimize in vitro tuberization by manipulating key vari...
MVT-Net: A novel cervical tumour segmentation using multi-view feature transfer learning.
PloS one
Jun 24, 2025
Cervical cancer is one of the most aggressive malignant tumours of the reproductive system, posing a significant global threat to women's health. Accurately segmenting cervical tumours in MR images remains a challenging task due to the complex charac...
Exploring the association between volatile organic compound exposure and chronic kidney disease: evidence from explainable machine learning methods.
Renal failure
Jun 23, 2025
BACKGROUND: Chronic Kidney Disease (CKD) affects approximately 697.5 million people worldwide. Volatile organic compounds (VOCs) are emerging as potential risk factors, but their complex relationships with CKD may be underestimated by traditional lin...
The early prediction of neonatal necrotizing enterocolitis in high-risk newborns based on two medical center clinical databases.
The journal of maternal-fetal & neonatal medicine : the official journal of the European Association of Perinatal Medicine, the Federation of Asia and Oceania Perinatal Societies, the International Society of Perinatal Obstetricians
Jun 23, 2025
: Early identification and timely preventive interventions play an essential role for improving the prognosis of newborns with necrotizing enterocolitis (NEC). Thus, establishing a novel and simple prediction model is of great clinical significance. ...
Sleep disturbances and PTSD: identifying baseline predictors of insomnia response in an intensive treatment programme.
European journal of psychotraumatology
Jun 23, 2025
This study examined whether baseline demographic and clinical variables could predict clinically significant reductions in insomnia symptoms among veterans receiving a 2-week Cognitive Processing Therapy (CPT)-based intensive PTSD treatment programm...
Influence of microplastics on antibiotic resistance genes across diverse environments: A comprehensive meta and machine-learning analysis.
Journal of hazardous materials
Jun 23, 2025
The coexistence of microplastics (MPs) and antibiotic resistance genes (ARGs) in various environments presents significant ecological risks. However, the influence of MPs properties and environmental conditions shaping ARG dynamics remain unclear. Th...
MLWNNR: LncRNA-Disease Association Prediction with Multi-Kernel Learning-Driven Weighted Nuclear Norm Regularization.
Interdisciplinary sciences, computational life sciences
Jun 23, 2025
Emerging evidence highlights long non-coding RNAs (lncRNAs) as pivotal regulators demonstrating significant linkages with diverse human pathologies through expression dynamics and regulatory cascades. This research endeavors to establish an algorithm...
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