To prevent data imbalance, a common problem in environmental modeling where non-flooded areas vastly outnumber flooded points ...
Monoclonal antibody (mAb) manufacturing must continually improve to keep up with increasing demands. To do this, biomanufacturers can deploy machine learning tools to augment traditional process ...
This paper represents the first attempt to examine investor behaviour for green stocks through the lens of return co-movement ...
Machine learning predicted ASD using sex-specific prenatal/perinatal factors: pregestational BMI, socioeconomic status, maternal age, and more.
In an era where insurance fraud drains billions from the global economy annually, a groundbreaking study by researchers ...
Marine oil spills are among the most severe environmental hazards, threatening aquatic ecosystems, coastal economies, and biodiversity. Traditional detection methods, based on manual observation, ship ...
Machine learning models using initial neuropsychological and neuropsychiatric clinical data accurately distinguished AD from bvFTD.
With the rapid advancements in computer technology and bioinformatics, the prediction of protein-ligand binding sites has ...
Awurum, N.P. (2025) Next-Generation Cyber Defense: AI-Powered Predictive Analytics for National Security and Threat Resilience. Open Access Library Journal, 12, 1-17. doi: 10.4236/oalib.1114210 .
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