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Accelerated Prediction of Terahertz Performance Metrics in GaN IMPATT Sources via Artificial Neural Networks

Santu Mondal, Sneha Ray, Aritra Acharyya, Rudra Sankar Dhar et al. • IEEE Access (2025)

This work investigates the application of artificial neural network (ANN)-based regression models to predict the static and dynamic characteristics of GaN impact avalanche transit time (IMPATT) sources in the terahertz (THz) frequency regim...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2025.3567410

Empirical Asset Pricing via Machine Learning

Shihao Gu, Bryan Kelly, Dacheng Xiu • Review of Financial Studies (2020)

Abstract We perform a comparative analysis of machine learning methods for the canonical problem of empirical asset pricing: measuring asset risk premiums. We demonstrate large economic gains to investors using machine learning forecasts, i...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1093/rfs/hhaa009

lab2clean: a novel algorithm for automated cleaning of retrospective clinical laboratory results data for secondary uses

Ahmed Medhat Zayed, Arne Janssens, Pavlos Mamouris, Nicolas Delvaux • BMC Medical Informatics and Decision Making (2024)

Abstract Background The integrity of clinical research and machine learning models in healthcare heavily relies on the quality of underlying clinical laboratory data. However, the preprocessing of this data to ensure its reliability and acc...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12911-024-02652-7

Elements of Machine Learning

Pat Langley B (1995)

Elements of Machine Learning by Pat Langley Preface 1. An overview of machine learning 1.1 The science of machine learning 1.2 Nature of the environment 1.3 Nature of representation and performance 1.4 Nature of the learning component 1.5 F...

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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

Global patterns of gully occurrence and their sensitivity to environmental changes

Yixian Chen, Sofie De Geeter, Jean Poesen, Francis Matthews et al. • International Soil and Water Conservation Research (2026)

Gully formation is a significant driver of soil erosion and land degradation worldwide and often leads to important downstream impacts. Nonetheless, our understanding of the global patterns and the factors controlling this process remains l...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.iswcr.2025.09.004

Assessing climate and land use impacts on surface water yield using remote sensing and machine learning

Amanuel Kumsa Bojer, Muluneh Woldetsadik Abshare, Fitsum Mesfin, Ayad M. Fadhil Al-Quraishi • Scientific Reports (2025)

Abstract Climate and land use changes are critical factors affecting watershed water yields, with significant implications for water resources at both local and regional levels. This study examined the combined effects of temporal and spati...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-03493-8

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

suzy elnokoudy • المجلة العلمية للدراسات والبحوث المالية والتجارية (2025)

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...

DOAJ Open Access (DOAJ) DOI: 10.21608/cfdj.2024.326666.2065

Enhancing Explainable Artificial Intelligence: Using Adaptive Feature Weight Genetic Explanation (AFWGE) with Pearson Correlation to Identify Crucial Feature Groups

Ebtisam AlJalaud, Manar Hosny • Mathematics (2024)

The ‘black box’ nature of machine learning (ML) approaches makes it challenging to understand how most artificial intelligence (AI) models make decisions. Explainable AI (XAI) aims to provide analytical techniques to understand the behavior...

DOAJ Open Access (DOAJ) DOI: 10.3390/math12233727

A Study on the Effectiveness of Deep Learning-Based Anomaly Detection Methods for Breast Ultrasonography

Changhee Yun, Bomi Eom, Sungjun Park, Chanho Kim et al. • Sensors (2023)

In the medical field, it is delicate to anticipate good performance in using deep learning due to the lack of large-scale training data and class imbalance. In particular, ultrasound, which is a key breast cancer diagnosis method, is delica...

DOAJ Open Access (DOAJ) DOI: 10.3390/s23052864

Artificial intelligence and employment

Alexandre Georgieff, Raphaela Hyee • OECD social employment and migration working papers (2021)

Recent years have seen impressive advances in artificial intelligence (AI) and this has stoked renewed concern about the impact of technological progress on the labour market, including on worker displacement. This paper looks at the possib...

OPENALEX DOI: https://doi.org/10.1787/c2c1d276-en

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

Nodir Rakhimov, Jura Kuvandikov, Ma'ruf Tojiyev, Dilmurod Khasanov et al. • Frontiers in Artificial Intelligence (2026)

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...

DOAJ Open Access (DOAJ) DOI: 10.3389/frai.2026.1910842

Silhouette-driven contrastive learning with hierarchical neighborhood structure for unsupervised clothes change person re-identification

Mingkun Li, Peng Xu • CAAI Artificial Intelligence Research (2026)

This paper addresses a highly challenging yet critical task: unsupervised person re-identification (Re-ID) under clothing changes. Unfortunately, existing unsupervised person Re-ID methods are mainly designed for short-term scenarios that r...

DOAJ Open Access (DOAJ) DOI: 10.26599/AIR.2025.9150050

Is cardiovascular risk profiling from UK Biobank retinal images using explicit deep learning estimates of traditional risk factors equivalent to actual risk measurements? A prospective cohort study design

Kohji Nishida, Ryo Kawasaki, Yiming Qian, Liangzhi Li et al. • BMJ Open (2024)

Objective Despite extensive exploration of potential biomarkers of cardiovascular diseases (CVDs) derived from retinal images, it remains unclear how retinal images contribute to CVD risk profiling and how the results can inform lifestyle m...

DOAJ Open Access (DOAJ) DOI: 10.1136/bmjopen-2023-078609

AI-heat transfer analysis of casson fluid in uniformly heated enclosure with semi heated baffle

Khalil Ur Rehman, Wasfi Shatanawi, Lok Yian Yian • International Journal of Thermofluids (2025)

The heat transfer in Casson fluid with natural convection claims various applications namely thermal regulation in biological systems, solar collectors, polymer processing, and geothermal applications to mention just a few. Owing to such mo...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.ijft.2025.101148