Academic Articles & Research Papers

Discovering subtypes with imaging signatures in the Motoric Cognitive Risk Syndrome Consortium using weakly supervised clustering

ABSTRACT INTRODUCTION Understanding the heterogeneity of brain structure in individuals with the Motoric Cognitive Risk Syndrome (MCR) may improve the current risk assessments of dementia. METHODS We used data from six cohorts from the MCR ...

Machine Learning for Sociology

Machine learning is a field at the intersection of statistics and computer science that uses algorithms to extract information and knowledge from data. Its applications increasingly find their way into economics, political science, and soci...

Exploring the Impact of Alternatives of Object-Oriented Cohesion Measures on Machine Learning-Based Predictions of Inheritance Reusability

The cohesion of an object-oriented class refers to the relatedness of its methods and attributes. Constructors, destructors, and access methods are special types of methods featuring unique characteristics that can artificially affect class...

The voice of depression: speech features as biomarkers for major depressive disorder

Abstract Background Psychiatry faces a challenge due to the lack of objective biomarkers, as current assessments are based on subjective evaluations. Automated speech analysis shows promise in detecting symptom severity in depressed patient...

Investigating the Role of Artificial Intelligence in Management of Diabetes in Iran: A Systematic Review

Background and Aim: Diabetes is one of the most common metabolic diseases in Iran and the fifth leading cause of death all over the world. Its spread around the world has created new methods in biomedical research, including artificial inte...

Predicting Choroidal Nevus Transformation to Melanoma Using Machine Learning

Purpose: To develop and validate machine learning (ML) models to predict choroidal nevus transformation to melanoma based on multimodal imaging at initial presentation. Design: Retrospective multicenter study. Participants: Patients diagnos...

Artificial intelligence in orthopaedic surgery

The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need ...

Artificial Empathy and Imprecise Communication in a Multi-Agent System

This paper introduces a novel artificial intelligence model that integrates artificial empathy into the decision-making processes of collaborative agent systems. The existing models of collaborative behaviors, especially in swarm applicatio...

Vestibular-Visual Reweighting in Persistent Postural-Perceptual Dizziness: A Multilevel Resting-State fMRI Study

Persistent postural-perceptual dizziness (PPPD) is a disabling functional vestibular disorder characterized by chronic dizziness and visually and motion-induced unsteadiness that markedly impairs daily activities, yet it lacks objective neu...

Decreasing the Burden of West Nile Virus Disease: The Need for More Prevention Measures.

Artificial Intelligence Voluntary Disclosures and Their Effect on Firms’ Financial Performance: Evidence from Egypt Firms on the EGX30 Index

The present paper, thus, investigates the link between AI-disclosure in annual reports and firm performance in the Egyptian financial industry. It explains how the number of appertained AI-words in the corporate disclosures would correspond...

From “usefulness” to “dependence”: the dynamic evolution mechanism of generative AI use behaviors

BackgroundAs generative artificial intelligence (GenAI) rapidly permeates Chinese higher education, university students’ AI use behaviors have come to be characterized by “high frequency, wide penetration, and rapid iteration.” Yet, a syste...

Artificial intelligence and firm-level productivity

Artificial Intelligence (AI) is often regarded as the next general-purpose technology with a rapid, penetrating, and far-reaching use over a broad number of industrial sectors. The main feature of new general-purpose technology is to enable...

Assessing carbon and economic loss from oak decline in Iran’s Zagros forests using Sentinel-2 and machine learning

Over recent decades, the decline of oak trees, which has emerged as the most significant challenge to the Zagros forests (ZFs), poses serious threats to carbon storage (CS) and economic valuation, jeopardizing the ecological and economic su...

Application of artificial intelligence in gastroenterology

Artificial intelligence (AI) using deep-learning (DL) has emerged as a breakthrough computer technology. By the era of big data, the accumulation of an enormous number of digital images and medical records drove the need for the utilization...

Smart IoT device for in field Black Sigatoka Disease recognition and mapping

Recently banana plantations have been affected by the Black Sigatoka Disease (BSD), producing streaks, lesions and yellow and brown spots on the leaves until the appearance of entire dead parts. The disease causes reductions in yield making...

A Scalo Gram-Based CNN Ensemble Method With Density-Aware SMOTE Oversampling for Improving Bearing Fault Diagnosis

Machine learning (ML) based bearing fault detection is an emerging application of Artificial Intelligence (AI) that has proven its utility in effectively classifying various faults for timely measures. There are myriad studies dedicated to ...

Unsupervised machine learning identifies distinct ALS molecular subtypes in post-mortem motor cortex and blood expression data

Abstract Amyotrophic lateral sclerosis (ALS) displays considerable clinical and genetic heterogeneity. Machine learning approaches have previously been utilised for patient stratification in ALS as they can disentangle complex disease lands...

Discussion on Artificial Intelligence Safety and Ethical Issues

As artificial intelligence (AI) is increasingly integrated into society, people are relying on it more and more, and higher requirements are put forward for the safety and ethical standards of AI. This article explores the development of ar...

The co-curation of collective memory: artificial intelligence, Holocaust survivor testimony and the contribution of museum educators

Holocaust survivor testimony is increasingly being preserved using emerging technologies in preparation for a post-survivor era. A key approach to this process is exemplified by the Dimensions in Testimony platform developed by the Universi...