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Ensembles machine learning for short duration rainfall intensity forecasting

Susilowati, Aprizal, Dyah Indriana Kusumastuti • Discover Artificial Intelligence (2026)

Abstract This study introduces an ensemble machine learning (EML) framework to enhance short-duration rainfall-intensity prediction under limited-data conditions. By integrating multiple base learners within a stacking architecture, the pro...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44163-026-01772-5

Machine learning with persistent homology and chemical word embeddings improves prediction accuracy and interpretability in metal-organic frameworks

Aditi S. Krishnapriyan, Joseph Montoya, Maciej Haranczyk, Jens Hummelshøj et al. • Scientific Reports (2021)

Abstract Machine learning has emerged as a powerful approach in materials discovery. Its major challenge is selecting features that create interpretable representations of materials, useful across multiple prediction tasks. We introduce an ...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-021-88027-8

Artificial Intelligence in Routine IVF Practice

Grzegorz Mrugacz, Aleksandra Mospinek, Małgorzata Jagielska, Dariusz Miszczak et al. • Biology (2025)

Background: Artificial Intelligence (AI) has emerged as a transformative tool in in vitro fertilization (IVF) as it has done in other sectors. In IVF, AI offers advancements in embryo selection, treatment personalization, and outcome predic...

DOAJ Open Access (DOAJ) DOI: 10.3390/biology15010042

Advanced Swine Management: Infrared Imaging for Precise Localization of Reproductive Organs in Livestock Monitoring

Iyad Almadani, Brandon Ramos, Mohammed Abuhussein, Aaron L. Robinson • Digital (2024)

Traditional methods for predicting sow reproductive cycles are not only costly but also demand a larger workforce, exposing workers to respiratory toxins, repetitive stress injuries, and chronic pain. This occupational hazard can even lead ...

DOAJ Open Access (DOAJ) DOI: 10.3390/digital4020022

Applied research note: Predicting carcass portion weights for purebred turkey (Meleagris gallopavo) lines using a 2D imaging system

Shai Barbut, Emily M. Leishman, Ryley J. Vanderhout, Benjamin J. Wood et al. • Journal of Applied Poultry Research (2025)

Summary: Improving carcass portion yields (e.g., breast meat) is a major goal of modern turkey breeding and traditionally requires manual collection of portion weights. This can be a labor-intensive process considering the large amount of d...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.japr.2024.100506

From Data to Decisions: AI in Varicose Veins—Predicting, Diagnosing, and Guiding Effective Management

Lakshmi Sree Pugalenthi, Chris Garapati, Srivarshini Maddukuri, Fnu Kanwal et al. • Journal of Vascular Diseases (2025)

Background: Varicose veins (VVs) of the lower limbs, characterized by palpable, dilated, and tortuous veins, affect 2–73% of the global population. Artificial intelligence (AI) offers significant potential to enhance healthcare efficiency a...

DOAJ Open Access (DOAJ) DOI: 10.3390/jvd4020019

Potential of machine learning approaches for predicting mechanical properties of spruce wood in the transverse direction

Shuoye Chen, Rei Shiina, Kazushi Nakai, Tatsuya Awano et al. • Journal of Wood Science (2023)

Abstract To predict the mechanical properties of wood in the transverse direction, this study used machine learning to extract the anatomical features of wood from cross-sectional stereograms. Specimens with different orientations of the ra...

DOAJ Open Access (DOAJ) DOI: 10.1186/s10086-023-02096-z

Evaluating the ergonomic deficiencies in computer workstations and investigating their correlation with reported musculoskeletal disorders and visual symptoms among computer users in Bangladeshi university

Md Golam Kibria, Md Shohel Parvez, Palash Saha, Subrata Talapatra • Heliyon (2023)

Background: Nowadays, computer users are facing musculoskeletal disorders (MSDs) and visual symptoms. Prolonged sitting in inappropriate, awkward, and static postures on the computer workstation may cause musculoskeletal disorders (MSDs). S...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.heliyon.2023.e22179

Building neural networks

David M. Skapura (1995)

Foundations. Motivation. Neural-Network Fundamentals. Single Neuron Computations. Network Computations. Network Simulation. Foundations Summary. Suggested Readings. Bibliography. Paradigms. The Backpropagation Network. The Counterpropagatio...

OPENALEX

Predicting air quality index using artificial neural network: a case study of the Coimbatore region

P. Jagadesh, J. Harshini, D. Arul, Solomon Oyebisi et al. • Discover Civil Engineering (2026)

Abstract This study predicts the Air Quality Index (AQI) in the Coimbatore region using Artificial Neural Networks (ANN) to enhance air quality management and environmental science. The researchers measured six input variables over a two-ye...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44290-026-00423-z

Digital Local Return Services and Purchase Intention in Cross-Border E-Commerce: A Risk–Trust Perspective

Xianfa Shi, Miao Su, Keun-sik Park • Journal of Theoretical and Applied Electronic Commerce Research (2026)

Cross-border e-commerce offers consumers broader product access, yet uncertainty surrounding returns continues to suppress online purchase decisions. This study conceptualizes digital local return services as a digital assurance mechanism i...

DOAJ Open Access (DOAJ) DOI: 10.3390/jtaer21060165

Predictive model for 5-year mortality after breast cancer surgery in Taiwan residents

Su-Hsin Huang, Joon-Khim Loh, Jinn-Tsong Tsai, Ming-Feng Houg et al. • Chinese Journal of Cancer (2017)

Abstract Background Few studies of breast cancer surgery outcomes have used longitudinal data for more than 2 years. This study aimed to validate the use of the artificial neural network (ANN) model to predict the 5-year mortality of breast...

DOAJ Open Access (DOAJ) DOI: 10.1186/s40880-017-0192-9

On Calibration of Modern Neural Networks

Chuan Guo, Geoff Pleiss, Yu Sun, Kilian Q. Weinberger • arXiv (Cornell University) (2017)

Confidence calibration -- the problem of predicting probability estimates representative of the true correctness likelihood -- is important for classification models in many applications. We discover that modern neural networks, unlike thos...

OPENALEX Open Access DOI: https://doi.org/10.48550/arxiv.1706.04599

Spatial analysis and risk mapping of Fasciola hepatica infection in dairy cattle at the Peruvian central highlands

Daniel Alexis Zárate-Rendón, David Godoy Padilla, Samuel Pizarro Carcausto, Alberto del Águila et al. • Parasite Epidemiology and Control (2023)

This study aimed to develop maps for Fasciola hepatica infection occurrence in dairy cattle in the districts of Matahuasi and Baños in the Peruvian central highlands. For this, a model based on the correlation between environmental variable...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.parepi.2023.e00329

Application of Artificial Neural Networks for Predicting Relative Permeability in Talang Akar Formation

Fathaddin Muhammad Taufiq, Sari Alvita Kumala, Sutansyah Daddy, Ulfah Baiq Maulinda et al. • E3S Web of Conferences (2024)

Relative permeability is a substantial parameter for estimating multi-phase fluid flow in porous rocks. It is a complex physical property that is influenced by the behavior and interactions between the fluid and rock phases. Relative permea...

DOAJ Open Access (DOAJ) DOI: 10.1051/e3sconf/202450003019