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Identification of arachidonic acid metabolism-related diagnostic markers in heart failure based on bioinformatics analysis and machine learning

Saiqing Chen, Chunxia Zhang, Yueting Yu • Frontiers in Cardiovascular Medicine (2025)

BackgroundHeart failure (HF) represents the terminal phase of multiple cardiovascular conditions and is associated with significant morbidity and mortality rates. Arachidonic acid (AA), an essential fatty acid, plays a crucial role in modul...

DOAJ Open Access (DOAJ) DOI: 10.3389/fcvm.2025.1625064

Inferring Markovian quantum master equations of few-body observables in interacting spin chains

Francesco Carnazza, Federico Carollo, Dominik Zietlow, Sabine Andergassen et al. • New Journal of Physics (2022)

Full information about a many-body quantum system is usually out-of-reach due to the exponential growth—with the size of the system—of the number of parameters needed to encode its state. Nonetheless, in order to understand the complex phen...

DOAJ Open Access (DOAJ) DOI: 10.1088/1367-2630/ac7df6

Automated, economical, and environmentally-friendly asphalt mix design based on machine learning and multi-objective grey wolf optimization

Jian Liu, Fangyu Liu, Linbing Wang • Journal of Traffic and Transportation Engineering (English ed. Online) (2024)

The increasing impact of the greenhouse effect on ecosystems is prompting transportation agencies to seek methods for reducing CO2 emissions during pavement construction and maintenance. Additionally, the laboratory mix design process, whic...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jtte.2023.10.002

Machine learning-derived prediction of in-hospital mortality in patients with severe acute respiratory infection: analysis of claims data from the German-wide Helios hospital network

Johannes Leiner, Vincent Pellissier, Sebastian König, Sven Hohenstein et al. • Respiratory Research (2022)

Abstract Background Severe acute respiratory infections (SARI) are the most common infectious causes of death. Previous work regarding mortality prediction models for SARI using machine learning (ML) algorithms that can be useful for both i...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12931-022-02180-w

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

Jehad Al Dallal, Bader Alkhazi • IEEE Access (2024)

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...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3484007

Evaluation of the Applications of using Global free Digital Elevation Models and GNSS-RTK data for Agricultural purposes in Egypt using Machine Learning

Ashraf abdallah, Bara' Al-MISTAREHI, Amir SHTAYAT • JES: Journal of Engineering Sciences (2025)

Agriculture is a vital component of Egypt's economy; therefore, using Digital Elevation Models (DEMs) in agricultural planning in Egypt has significant benefits regarding water management, site appropriateness assessment, flood risk mitigat...

DOAJ Open Access (DOAJ) DOI: 10.21608/jesaun.2024.326709.1374

LearningEMS: A Unified Framework and Open-Source Benchmark for Learning-Based Energy Management of Electric Vehicles

Yong Wang, Hongwen He, Yuankai Wu, Pei Wang et al. • Engineering (2025)

An effective energy management strategy (EMS) is essential to optimize the energy efficiency of electric vehicles (EVs). With the advent of advanced machine learning techniques, the focus on developing sophisticated EMS for EVs is increasin...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.eng.2024.10.021

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

Felix Menne, Felix Dörr, Julia Schräder, Johannes Tröger et al. • BMC Psychiatry (2024)

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...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12888-024-06253-6

Integrating task-state electroencephalography and motor function for intelligent assessment of recovery status from prolonged disorders of consciousness

Longhao Zhang, Hongzhen Cui, Xiaoyue Zhu, Guilong Zhang et al. • BMC Neurology (2026)

Abstract Background Accurately assessing recovery in patients with prolonged disorders of consciousness (PDoC) is essential for evaluating the therapeutic efficacy and optimizing clinical care. However, substantial individual variability an...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12883-026-05183-y

Artificial intelligence model to predict pregnancy and multiple pregnancy risk following in vitro fertilization-embryo transfer (IVF-ET)

Jen-Yu Wen, Chung-Fen Liu, Ming-Ting Chung, Yung-Chieh Tsai • Taiwanese Journal of Obstetrics & Gynecology (2022)

Objective: To decrease multiple pregnancy risk and sustain optimal pregnancy chance by choosing suitable number of embryos during transfer, this study aims to construct artificial intelligence models to predict the pregnancy outcome and mul...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.tjog.2021.11.038

Selection of target-binding proteins from the information of weakly enriched phage display libraries by deep sequencing and machine learning

Tomoyuki Ito, Thuy Duong Nguyen, Yutaka Saito, Yoichi Kurumida et al. • mAbs (2023)

Despite the advances in surface-display systems for directed evolution, variants with high affinity are not always enriched due to undesirable biases that increase target-unrelated variants during biopanning. Here, our goal was to design a ...

DOAJ Open Access (DOAJ) DOI: 10.1080/19420862.2023.2168470

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

Fatemeh Bahador, Azam Sabahi, Samaneh Jalali, Fatemeh Ameri • پیاورد سلامت (2023)

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...

DOAJ Open Access (DOAJ)

РОЛЬ ИСКУССТВЕННОГО ИНТЕЛЛЕКТА В АВТОМАТИЗАЦИИ НАУЧНЫХ ИССЛЕДОВАНИЙ: ОТ АНАЛИЗА ЛИТЕРАТУРЫ ДО ГЕНЕРАЦИИ ГИПОТЕЗ

Анастас К.В. • Cifra: Компьютерные науки и информатика (2026)

Современная научная деятельность характеризуется экспоненциальным ростом объема публикаций и данных, что создает значительные трудности в систематизации, анализе и интерпретации информации. В этих условиях технологии искусственного интеллек...

DOAJ Open Access (DOAJ) DOI: 10.60797/COMP.2026.9.1

Predicting Choroidal Nevus Transformation to Melanoma Using Machine Learning

Prashant D. Tailor, MD, Piotr K. Kopinski, MD, PhD, Haley S. D’Souza, MD, David A. Leske, MS et al. • Ophthalmology Science (2025)

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...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.xops.2024.100584

Hyperspectral imaging for the detection of plant pathogens in seeds: recent developments and challenges

Luciellen da Costa Ferreira, Ian Carlos Bispo Carvalho, Lúcio André de Castro Jorge, Alice Maria Quezado-Duval et al. • Frontiers in Plant Science (2024)

Food security, a critical concern amid global population growth, faces challenges in sustainable agricultural production due to significant yield losses caused by plant diseases, with a multitude of them caused by seedborne plant pathogen. ...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpls.2024.1387925

Leveraging AI to Estimate Caribou Lichen in UAV Orthomosaics from Ground Photo Datasets

Galen Richardson, Sylvain G. Leblanc, Julie Lovitt, Krishan Rajaratnam et al. • Drones (2021)

Relating ground photographs to UAV orthomosaics is a key linkage required for accurate multi-scaled lichen mapping. Conventional methods of multi-scaled lichen mapping, such as random forest models and convolutional neural networks, heavily...

DOAJ Open Access (DOAJ) DOI: 10.3390/drones5030099