AI, automation and algorithms are proliferating across many sectors of the global economy, including in regulated industries ...
Last month, the Sedona Conference Working Group 13 Annual Meeting and the ASU Arkfeld Conference on eDiscovery, Law, and ...
MRI-detected sacroiliac bone marrow edema is a key diagnostic marker for axial spondyloarthritis (axSpA), but its value in ...
The goal of this article is to address the most common questions practitioners are asking today about gen AI in e-discovery.
Data governance frameworks were built for a world where humans created most data, but AI has changed that equation.
In computer science, the research area of algorithms investigates formal procedures for solving computational problems, emphasizing correctness, efficiency, and resource optimization. It encompasses ...
As the world races to build artificial superintelligence, one maverick bioengineer is testing how much unprogrammed intelligence may already be lurking in our simplest algorithms to determine whether ...
Abstract: E-health sensors and wearables play an important role in the detection and classification of many chronic diseases. A chronic disease requires active monitoring and its severity increases ...
Cancer machine learning research is often limited by overparameterization and overfitting, which arise because cancer ‘omic’ variables significantly outnumber patient samples. Traditional feature ...
ABSTRACT: This paper presents a comprehensive machine learning approach for credit score classification, addressing key challenges in financial risk assessment. We propose an optimized CatBoost-based ...
Algorithms are involved in decisions ranging from trivial to significant, but people often express distrust toward them. Research suggests that educational efforts to explain how algorithms work may ...
Abstract: As online news grows exponentially, hotspot classification is becoming increasingly important. Although traditional machine learning-based text classification methods, such as plain Bayes, ...
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