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

Sadettin Y. Ugurlu, David McDonald, Huangshu Lei, Alan M. Jones et al. • Journal of Cheminformatics (2024)

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...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13321-023-00793-x

Patient information needs for transparent and trustworthy cardiovascular artificial intelligence: A qualitative study.

Austin M Stroud, Sarah A Minteer, Xuan Zhu, Jennifer L Ridgeway et al. • PLOS Digital Health (2025)

As health systems incorporate artificial intelligence (AI) into various aspects of patient care, there is growing interest in understanding how to ensure transparent and trustworthy implementation. However, little attention has been given t...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pdig.0000826

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

Faezeh Aghamirzaei, Ahmad Ali Abin, Farzaneh Futuhi • Archives of Academic Emergency Medicine (2025)

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...

DOAJ Open Access (DOAJ) DOI: 10.22037/aaemj.v13i1.2560

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

Diego D. Díaz-Guerra, Marena de la C. Hernández-Lugo, Yunier Broche-Pérez, Carlos Ramos-Galarza et al. • Frontiers in Psychiatry (2025)

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...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpsyt.2024.1516065

Raman Spectroscopy Pre-Trained Encoder: A Self-Supervised Learning Approach for Data-Efficient Domain-Independent Spectroscopy Analysis

Abhiraam Eranti, Yogesh Tewari, Rafael Palacios, Amar Gupta • IEEE Access (2026)

Deep-learning methods have boosted the analytical power of Raman spectroscopy, yet they still require large, task-specific, labeled datasets and often fail to transfer across application domains. The study explores pre-trained encoders as a...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2026.3672109

Prediction of irinotecan toxicity in metastatic colorectal cancer patients based on machine learning models with pharmacokinetic parameters

Esther Oyaga-Iriarte, Asier Insausti, Onintza Sayar, Azucena Aldaz • Journal of Pharmacological Sciences (2019)

Irinotecan (CPT-11) is a drug used against a wide variety of tumors, which can cause severe toxicity, possibly leading to the delay or suspension of the cycle, with the consequent impact on the prognosis of survival. The main goal of this w...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jphs.2019.03.004

Emotional intelligence or artificial intelligence– an employee perspective

Catherine Prentice, Sérgio Dominique‐Ferreira, Xuequn Wang • Journal of Hospitality Marketing & Management (2019)

Emotional intelligence as personal intelligence and artificial intelligence as a machine intelligence have been popular in the relevant literature over the last two decades. The current study integrates these two concepts and explores how e...

OPENALEX Open Access DOI: https://doi.org/10.1080/19368623.2019.1647124

Artificial intelligence in medicine

AN Ramesh, C. Kambhampati, J. Quinn Monson, Philip J. Drew • Annals of The Royal College of Surgeons of England (2004)

INTRODUCTION: Artificial intelligence is a branch of computer science capable of analysing complex medical data. Their potential to exploit meaningful relationship with in a data set can be used in the diagnosis, treatment and predicting ou...

OPENALEX Open Access DOI: https://doi.org/10.1308/147870804290 PMC: 1964229

Tachyon: Enhancing stacked models using Bayesian optimization for intrusion detection using different sampling approaches

T. Anitha Kumari, Sanket Mishra • Egyptian Informatics Journal (2024)

The integration of sensors in the monitoring of essential bodily measurements, air quality, and energy consumption in buildings demonstrates the importance of the Internet of Things (IoT) in everyday life. These security breaches are caused...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.eij.2024.100520

Convergence of Artificial Intelligence and Wearables in Strength Training and Performance Monitoring: A Scoping Review

Eleftherios Fyntikakis, Spyridon Plakias, Themistoklis Tsatalas, Minas A. Mina et al. • Applied Sciences (2026)

Background: Strength training (ST) is essential for enhancing athletic performance and reducing injury risk, yet traditional monitoring relies heavily on subjective assessment, limiting objective and individualized evaluation. Objective: Th...

DOAJ Open Access (DOAJ) DOI: 10.3390/app16073565

Micro‐/Nanohierarchical Surfaces for Enhanced Pool Boiling in Large‐Area Silicon Multichips

Youngseob Lee, Kiwan Kim, Yunseo Kim, Daeyoung Kong et al. • Small Structures (2025)

With the rising demand for data centers, the need for an efficient thermal management approach becomes increasingly critical. This study examines the enhancement in pool boiling heat transfer on a customized multichip module, designed to mi...

DOAJ Open Access (DOAJ) DOI: 10.1002/sstr.202400512

Perspectives of Administrators and Teachers on Factors Affecting STEM Professional Development Management in Primary Schools in the Mekong Delta

Thi Mai Huong Vu, Van Ngoan Trinh, Tuan Khanh Vo • Tạp chí Khoa học Đại học Đồng Tháp (2026)

This study examined administrators’ and teachers’ perceptions of the factors affecting the management of professional development for primary school teachers’ STEM teaching competencies in the Mekong Delta, Vietnam. The paper reports the qu...

DOAJ Open Access (DOAJ) DOI: 10.52714/dthu.ajes.36.2023

Association between myosteatosis and impaired glucose metabolism: A deep learning whole‐body magnetic resonance imaging population phenotyping approach

Matthias Jung, Hanna Rieder, Marco Reisert, Susanne Rospleszcz et al. • Journal of Cachexia, Sarcopenia and Muscle (2024)

Abstract Background There is increasing evidence that myosteatosis, which is currently not assessed in clinical routine, plays an important role in risk estimation in individuals with impaired glucose metabolism, as it is associated with th...

DOAJ Open Access (DOAJ) DOI: 10.1002/jcsm.13527

Enhancing Online Security: A Novel Machine Learning Framework for Robust Detection of Known and Unknown Malicious URLs

Shiyun Li, Omar Dib • Journal of Theoretical and Applied Electronic Commerce Research (2024)

The rapid expansion of the internet has led to a corresponding surge in malicious online activities, posing significant threats to users and organizations. Cybercriminals exploit malicious uniform resource locators (URLs) to disseminate har...

DOAJ Open Access (DOAJ) DOI: 10.3390/jtaer19040141

Extracting behavioral patterns of people in crowdfunding projects using artificial intelligence and identify key investors

Musa Hajiani, Ehsan Eshtehardian, Mojtaba Azizi • بهبود مدیریت (2025)

Crowdfunding as a new method has an important contribution to projects, especially for small and medium-sized businesses. Despite the many years of activity of crowdfunding platforms in Iran, the scale of projects and the volume of capital ...

DOAJ Open Access (DOAJ) DOI: 10.22034/jmi.2025.463212.3109

Managing artificial intelligence

Paul R. Krausman • Journal of Wildlife Management (2023)

By the time you finish reading this editorial about artificial intelligence (AI), it will be outdated; the AI field is growing beyond the imagination of many. One cannot even look at the news without finding something about AI: duplication ...

OPENALEX other-oa DOI: https://doi.org/10.1002/jwmg.22492