Academic Articles & Research Papers

Risk factor assessments of temporomandibular disorders via machine learning

Abstract This study aimed to use artificial intelligence to determine whether biological and psychosocial factors, such as stress, socioeconomic status, and working conditions, were major risk factors for temporomandibular disorders (TMDs)....

Artificial Intelligence for Efficient Thermal Comfort Systems: Requirements, Current Applications and Future Directions

In buildings, one or a combination of systems (e.g., central HVAC system, ceiling fan, desk fan, personal heater, and foot warmer) are often responsible for providing thermal comfort to the occupants. While thermal comfort has been shown to...

Artificial Intelligence in Education: A Review

The purpose of this study was to assess the impact of Artificial Intelligence (AI) on education. Premised on a narrative and framework for assessing AI identified from a preliminary analysis, the scope of the study was limited to the applic...

Machine learning-based prediction models for recurrent stroke after an index stroke: a scoping review protocol.

Gender bias in artificial intelligence

Artificial intelligence is increasingly influencing the opinions and behavior of people in everyday life. However, the over-representation of men in the design of these technologies could quietly undo decades of advances in gender equality....

Learning the Path to Ion Separation: A Proof-of-Concept for Machine Learning-Assisted Inverse Design (MLAID) of Nanofiltration Membranes.

Development of a novel RNA modification-based risk model to predict prognosis and immunotherapy response in melanoma using machine learning.

Paddy Yield Prediction in Tamilnadu Delta Region Using MLR-LSTM Model

Crop yield forecasting has been well studied in recent decades and is significant in protecting food security. Crop growth is a complex phenomenon that depends on various factors. Machine learning and deep learning trends have emerged as im...

Comparative architectural evaluation of CNN models with alternative classifiers for UAV-based detection of damaged green zones

Unmanned aerial vehicle imagery provides a practical and high-resolution data source for monitoring the spatial condition of urban and peri-urban green zones. However, the reliable detection of damaged, stressed, or declining vegetation are...

What is Artificial Intelligence?

Artificial intelligence (AI) is the ability of a machine or computer system to simulate and perform tasks that would normally require human intelligence, such as logical reasoning, learning, and problem solving. Artificial intelligence is b...

Probabilistic machine learning and artificial intelligence

Artificial intelligence and echocardiography

Echocardiography plays a crucial role in the diagnosis and management of cardiovascular disease. However, interpretation remains largely reliant on the subjective expertise of the operator. As a result inter-operator variability and experie...

External Validation of a Machine Learning Model for Delirium Risk.

Integrative Approaches to Soybean Resilience, Productivity, and Utility: A Review of Genomics, Computational Modeling, and Economic Viability

Soybean is a vital crop globally and a key source of food, feed, and biofuel. With advancements in high-throughput technologies, soybeans have become a key target for genetic improvement. This comprehensive review explores advances in multi...

On the practical aspects of machine learning based active power loss forecasting in transmission networks

Abstract The cost for covering active power losses makes a significant item in transmission system operators (TSO) annual budgets, and still it received limited attention in the existing literature. The focus of accurate power loss forecast...

A Primer on Generative Artificial Intelligence

Many educators and professionals in different industries may need to become more familiar with the basic concepts of artificial intelligence (AI) and generative artificial intelligence (Gen-AI). Therefore, this paper aims to introduce some ...

Artificial intelligence in recommender systems

Abstract Recommender systems provide personalized service support to users by learning their previous behaviors and predicting their current preferences for particular products. Artificial intelligence (AI), particularly computational intel...

Cobdock: an accurate and practical machine learning-based consensus blind docking method

Abstract Probing the surface of proteins to predict the binding site and binding affinity for a given small molecule is a critical but challenging task in drug discovery. Blind docking addresses this issue by performing docking on binding r...

An Ensemble Machine Learning Model for Early Prediction of Vancomycin-Induced Acute Kidney Injury in ICU Patients

Introduction: Acute Kidney Injury (AKI) is a severe complication of vancomycin treatment due to its nephrotoxic effects. However, research on predicting AKI in this high-risk group remains limited. This study presents a stacking ensemble ma...

AI-assisted neurocognitive assessment protocol for older adults with psychiatric disorders

IntroductionEvaluating neurocognitive functions and diagnosing psychiatric disorders in older adults is challenging due to the complexity of symptoms and individual differences. An innovative approach that combines the accuracy of artificia...