The line between human and artificial intelligence is growing ever more blurry. Since 2021, AI has deciphered ancient texts ...

AI is pushing Canada’s justice system toward a crisis of trust The post When Evidence Can Be Deepfaked, How Do Courts Decide What’s Real? first appeared on The Walrus.

Existing algorithms can partially reconstruct the shape of a single tree from a clean point-cloud dataset acquired by laser-scanning technologies. Doing the same with forest data has proven far more ...

Google Discover is largely a mystery to publishers and the search marketing community even though Google has published ...

Abstract: Because of their transparency, interpretability, and efficiency in classification tasks, decision tree algorithms are the foundation of many Business Intelligence (BI) and Analytics ...

Background Patients with severe aortic stenosis (AS) are at high risk of mortality, regardless of symptom status. Despite this, aortic valve replacement rates remain low for patients with severe AS ...

Abstract: This research aims to study, design, and develop a brain tumor classification system using artificial intelligence, specifically decision tree algorithms. The system's primary objective is ...

There is indeed a vast literature on the design and analysis of decision tree algorithms that aim at optimizing these parameters. This paper contributes to this important line of research: we propose ...

ABSTRACT: From the perspective of student consumption behavior, a data-driven framework for screening student loan eligibility was developed using K-means clustering analysis and decision tree models.

Introduction: Accurate identification of forest tree species is essential for sustainable forest management, biodiversity assessment, and environmental monitoring. Urban forests, in particular, ...

Recently, many machine learning techniques have been presented to detect brain lesions or determine brain lesion types using microwave data. However, there are limited studies analyzing the location ...

Computer vision systems combined with machine learning techniques have demonstrated success as alternatives to empirical methods for classification and selection. This study aimed to classify tomatoes ...