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Using fuzzy and machine learning iterative optimized models to generate the flood susceptibility maps: case study of Prahova River basin, Romania

Romulus Costache, Hazem Ghassan Abdo, Arun Pratap Mishra, Subodh Chandra Pal et al. • Geomatics, Natural Hazards & Risk (2023)

AbstractIn this work, the vulnerability to flooding in the Prahova River basin was calculated and analyzed using advanced methods and techniques. Thus, 2 hybrid models represented by Iterative Classifier Optimizer – Multiclass Alternating D...

DOAJ Open Access (DOAJ) DOI: 10.1080/19475705.2023.2281241

Key factors and serial mediation analysis of anxiety and depression among university students: a cross-sectional study

Tan Jiang, Shijia Zhang, Shijia Zhang, Deyou Jiang • Frontiers in Psychiatry (2026)

BackgroundAnxiety and depressive symptoms are prevalent among university students; however, their risk factors are unlikely to operate in isolation. Instead, they may be organized in a multilevel structure that progressively approaches emot...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpsyt.2026.1809332

CViewer: a Java-based statistical framework for integration of shotgun metagenomics with other omics datasets

Orges Koci, Richard K. Russell, M. Guftar Shaikh, Christine Edwards et al. • Microbiome (2024)

Abstract Background Shotgun metagenomics for microbial community survey recovers enormous amount of information for microbial genomes that include their abundances, taxonomic, and phylogenetic information, as well as their genomic makeup, t...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40168-024-01834-9

Burnout Risk Profiles in Psychology Students: An Exploratory Study with Machine Learning

M. Graça Pereira, Martim Santos, Renata Magalhães, Cláudia Rodrigues et al. • Behavioral Sciences (2025)

University students are at increased risk of developing burnout and psychological distress from high academic workloads and performance expectations. The purpose of this study is to analyze the relationship between psychological and lifesty...

DOAJ Open Access (DOAJ) DOI: 10.3390/bs15040505

Generative-Adversarial-Network-Based Image Reconstruction for the Capacitively Coupled Electrical Impedance Tomography of Stroke

Mikhail Ivanenko, Damian Wanta, Waldemar T. Smolik, Przemysław Wróblewski et al. • Life (2024)

This study investigated the potential of machine-learning-based stroke image reconstruction in capacitively coupled electrical impedance tomography. The quality of brain images reconstructed using the adversarial neural network (cGAN) was e...

DOAJ Open Access (DOAJ) DOI: 10.3390/life14030419

A novel machine learning-based model for predicting the transition fatigue lifetime in piston aluminum alloys

Mahmood Matin, Mohammad Azadi • International Journal of Lightweight Materials and Manufacture (2024)

The estimation of transition fatigue lifetimes for piston aluminum alloys was carried out using unsupervised machine learning (ML) with the K-means algorithm. For this purpose, an experimental dataset representing standard ISO specimens wit...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.ijlmm.2024.04.004

Machine learning and applications in microbiology

Stephen J. Goodswen, Joel Barratt, Paul J Kennedy, Alexa Kaufer et al. • FEMS Microbiology Reviews (2021)

To understand the intricacies of microorganisms at the molecular level requires making sense of copious volumes of data such that it may now be humanly impossible to detect insightful data patterns without an artificial intelligence applica...

OPENALEX cc-by-nc DOI: https://doi.org/10.1093/femsre/fuab015 PMC: 8498514

Machine Learning in Enzyme Engineering

Stanislav Mazurenko, Zbyněk Prokop, Jiřı́ Damborský • ACS Catalysis (2019)

Abstract Enzyme engineering plays a central role in developing efficient biocatalysts for biotechnology, biomedicine, and life sciences. Apart from classical rational design and directed evolution approaches, machine learning methods have b...

OPENALEX other-oa DOI: https://doi.org/10.1021/acscatal.9b04321

Automated shape-based clustering of 3D immunoglobulin protein structures in chronic lymphocytic leukemia

Eleftheria Polychronidou, Ilias Kalamaras, Andreas Agathangelidis, Lesley-Ann Sutton et al. • BMC Bioinformatics (2018)

Abstract Background Although the etiology of chronic lymphocytic leukemia (CLL), the most common type of adult leukemia, is still unclear, strong evidence implicates antigen involvement in disease ontogeny and evolution. Primary and 3D stru...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12859-018-2381-1

Perspectives in machine learning for wildlife conservation

Devis Tuia, Benjamin Kellenberger, Sara Beery, Blair R. Costelloe et al. • Nature Communications (2022)

Inexpensive and accessible sensors are accelerating data acquisition in animal ecology. These technologies hold great potential for large-scale ecological understanding, but are limited by current processing approaches which inefficiently d...

OPENALEX cc-by DOI: https://doi.org/10.1038/s41467-022-27980-y PMC: 8828720

Calibrated Machine Learning with Temporal Leakage Controls for Rare-Event Forecasting of Port Activity Anomalies: Evidence from Selected African Countries and Indonesia

Tomasz Rokicki, Piotr Bórawski, Aneta Bełdycka-Bórawska, Bogdan Klepacki • Applied Sciences (2026)

Port activity anomalies are rare but may signal operational constraints relevant to supply chains. The aim of the study was to develop and empirically evaluate a calibrated machine learning framework for forecasting rare, algorithmically de...

DOAJ Open Access (DOAJ) DOI: 10.3390/app16189017

Predicting Urban Quality of Life Using Machine Learning on Street Images and Personal Information with Statistical Feature Selection: A Comparative Study of Bangkok and London

Ployrada Suvarnakuta, Intouch Prakaisak, Pittipol Kantavat, Boonserm Kijsirikul et al. • Engineered Science (2025)

This study proposes a machine learning framework for predicting perceived urban quality of life (QoL) by integrating visual features from street-level imagery with personal attributes, including demographic, socioeconomic, and travel behavi...

DOAJ Open Access (DOAJ) DOI: 10.30919/es1972

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