AIMC Topic: Machine Learning

Clear Filters Showing 6601 to 6610 of 34417 articles

Unraveling asymmetrical spillover effects originating from China's green finance markets: Insights from asymmetric TVP-VAR and interpretable machine learning.

Journal of environmental management
This study combines an asymmetric TVP-VAR model with interpretable machine learning algorithms to confirm the presence of asymmetries in spillover effects within China's green finance market and to identify the macroeconomic drivers behind these effe...

Does smart city construction promote urban green development? Evidence from a double machine learning model.

Journal of environmental management
The issue of whether smart city construction (SCC) can promote urban green development (UGD) is controversial. To address this problem, first, a UGD evaluation index system with four dimensions, namely, green production, green living, green growth, a...

Improving the Performance of Electrotactile Brain-Computer Interface Using Machine Learning Methods on Multi-Channel Features of Somatosensory Event-Related Potentials.

Sensors (Basel, Switzerland)
Traditional tactile brain-computer interfaces (BCIs), particularly those based on steady-state somatosensory-evoked potentials, face challenges such as lower accuracy, reduced bit rates, and the need for spatially distant stimulation points. In contr...

Habitat Suitability Modelling for the Red Dwarf Honeybee (Apis florea (Linnaeus)) and Its Distribution Prediction Using Machine Learning and Cloud Computing.

Neotropical entomology
Apis florea bees were recently identified in Egypt, marking the second occurrence of this species on the African continent. The objective of this study was to track the distribution of A. florea in Egypt and evaluate its potential for invasive behavi...

Advancing miRNA cancer research through artificial intelligence: from biomarker discovery to therapeutic targeting.

Medical oncology (Northwood, London, England)
MicroRNAs (miRNAs), a class of small non-coding RNAs, play a vital role in regulating gene expression at the post-transcriptional level. Their discovery has profoundly impacted therapeutic strategies, particularly in cancer treatment, where RNA thera...

Machine learning for predicting post-operative outcomes in meningiomas: a systematic review and meta-analysis.

Acta neurochirurgica
PURPOSE: Meningiomas are the most common primary brain tumour and account for over one-third of cases. Traditionally, estimations of morbidity and mortality following surgical resection have depended on subjective assessments of various factors, incl...

Machine Learning-Based Prediction Model for ICU Mortality After Continuous Renal Replacement Therapy Initiation in Children.

Critical care explorations
BACKGROUND: Continuous renal replacement therapy (CRRT) is the favored renal replacement therapy in critically ill patients. Predicting clinical outcomes for CRRT patients is difficult due to population heterogeneity, varying clinical practices, and ...

Prediction of talent selection in elite male youth soccer across 7 seasons: A machine-learning approach.

Journal of sports sciences
This study aimed to investigate the relative importance of parameters from several domains associated to both selecting or de-selecting players with regards to the next age group within a professional German youth soccer academy across a 7-year perio...

Low-Cost Approaches in Neuroscience to Teach Machine Learning Using a Cockroach Model.

eNeuro
In an effort to increase access to neuroscience education in underserved communities, we created an educational program that utilizes a simple task to measure place preference of the cockroach () and the open-source free software, SLEAP Estimates Ani...

Machine Learning-Based Model for Prediction of Post-Stroke Cognitive Impairment in Acute Ischemic Stroke: A Cross-Sectional Study.

Neurology India
BACKGROUND AND OBJECTIVE: Early identification of post-stroke cognitive impairment (PSCI) is an important challenge for clinicians. In this study, we aimed to build a machine learning-based prediction model for PSCI and uncover potential risk factors...