AIMC Topic: Machine Learning

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Risk formulation mechanism among top global energy companies under large shocks.

PloS one
Taking top global energy companies as the epitome, this paper investigates the risk formulation mechanism of the international energy market under the impact of large shocks. We first use the machine learning method in (Liu and Pun, 2022) to calculat...

Artificial Intelligence and Machine Learning for Stone Management.

The Urologic clinics of North America
Stone disease management is continuously evolving through the introduction of novel tools and technologies. Artificial intelligence and machine learning (ML) promise a new technological frontier for the enhancement of urolithiasis diagnosis, treatmen...

MRI-based radiomics model for the preoperative prediction of classification in children with venous malformations.

Clinical radiology
AIM: This study aimed to explore the efficacy of MRI-based radiomics models, employing various machine learning techniques, in the preoperative prediction of the digital subtraction angiography (DSA) classification of venous malformations (VMs).

On the Difficulty to Rescore Hits from Ultralarge Docking Screens.

Journal of chemical information and modeling
Docking-based virtual screening tools customized to mine ultralarge chemical spaces are consistently reported to yield both higher hit rates and more potent ligands than that achieved by conventional docking of smaller million-sized compound librarie...

The Gut Microbiota in Young Adults with High-Functioning Autism Spectrum Disorder and Its Performance as Diagnostic Biomarkers.

Nutrients
Diagnosing ASD in adults presents unique challenges, and there are currently no specific biomarkers for this condition. Most existing studies on the gut microbiota in ASD are conducted in children; however, the composition of the gut microbiota in c...

Association of sarcopenia with all-cause and cause-specific mortality in cancer patients: development and validation of a 3-year and 5-year survival prediction model.

BMC cancer
BACKGROUND: Sarcopenia is a clinicopathological condition characterized by a decrease in muscle strength and muscle mass, playing a crucial role in the prognosis of cancer. Therefore, this study aims to investigate the association between sarcopenia ...

The value of radiomics features of white matter hyperintensities in diagnosing cognitive frailty: a study based on T2-FLAIR imaging.

BMC medical imaging
BACKGROUND: White matter hyperintensities (WMHs) are closely associated with cognitive frailty (CF). This study aims to explore the potential diagnostic value of WMHs for CF based on radiomics approaches, thereby providing a novel methodology for the...

Transcriptome combined with Mendelian randomization to identify key genes related to polyamine metabolism in childhood obesity and elucidate their molecular regulatory mechanisms.

Scientific reports
Currently, research has found a close correlation between childhood obesity (CO) and elevated levels of polyamines in the bloodstream. Thus, the identification of key genes associated with polyamines metabolism in CO could offer fresh insights for cl...

Interpretable prediction of drug synergy for breast cancer by random forest with features from Boolean modeling of signaling pathways.

Scientific reports
Breast cancer is a complex and challenging disease to treat, and despite progress in combating it, drug resistance remains a significant hindrance. Drug combinations have shown promising results in improving therapeutic outcomes, and many machine lea...

Apnea detection using wrist actigraphy in patients with heterogeneous sleep disorders.

Scientific reports
Obstructive sleep apnea (OSA) and related hypoxia are well-established cardiovascular and neurocognitive risk factors. Current multi-sensor diagnostic approaches are intrusive and prone to misdiagnosis when simplified. This study introduces an enhanc...