Academic Articles & Research Papers
Search and discover peer-reviewed scholarly literature, open-access articles, and research citations across DOAJ, PubMed Central, and OpenAlex.
An Introduction to Machine Learning
https://doi.org/10.1007/978-3-319-63913-0
Machine learning for microbiologists
https://doi.org/10.1038/s41579-023-00984-1
PMC: 11980903
Calibrated Machine Learning with Temporal Leakage Controls for Rare-Event Forecasting of Port Activity Anomalies: Evidence from Selected African Countries and Indonesia
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...
10.3390/app16189017
Hybrid machine learning and 3D numerical modeling-based multi-objective optimization of geosynthetic-reinforced pile-supported embankments
Efficient and reliable design of Geosynthetic Reinforced Pile-Supported (GRPS) embankments on soft ground remains challenging due to the complex nonlinear soil–structure interaction and the high computational cost of repeated numerical anal...
10.3389/fbuil.2026.1829950
PCPAm - A dataset of histopathological images of penile cancer for classification tasksZenodo
Penile cancer has an incidence strongly linked to sociocultural factors, being more common in underdeveloped countries like Brazil, where it represents approximately 2% of cancers affecting men. This dataset was created to address the scarc...
10.1016/j.dib.2025.111823
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
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...
10.30919/es1972
Enhancing host-pathogen phenotyping dynamics: early detection of tomato bacterial diseases using hyperspectral point measurement and predictive modeling
Early diagnosis of plant diseases is needed to promote sustainable plant protection strategies. Applied predictive modeling over hyperspectral spectroscopy (HS) data can be an effective, fast, cost-effective approach for improving plant dis...
10.3389/fpls.2023.1242201
lab2clean: a novel algorithm for automated cleaning of retrospective clinical laboratory results data for secondary uses
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...
10.1186/s12911-024-02652-7
Surface circulation properties in the eastern Mediterranean emphasized using machine learning methods
The eastern Mediterranean surface circulation is highly energetic and composed of structures interacting stochastically. However, some main features are still debated, and the behavior of some fine-scale dynamics and their role in shaping t...
10.5194/os-18-1491-2022
Design and Pilot Feasibility of a Low-Cost Wearable for Mexican Sign Language in Inclusive Higher Education
A substantial number of students with hearing impairments are enrolled in higher education, motivating the development of inclusive assistive technologies that reduce communication barriers. This study developed and evaluated a prototype el...
10.3390/technologies14030189
Machine Learning–Based Wear Prediction of Recycled Magnesium Matrix Composites Reinforced With Ceramic Fibers
ABSTRACT This study deals with an integrated experimental‐machine learning framework for wear estimation in functionally graded composites made from recycled magnesium machining chips, using low‐cost ceramic fibers as reinforcement with the...
10.1002/eng2.70686
Machine learning in catalysis
https://doi.org/10.1038/s41929-018-0056-y
Machine Learning : A Probabilistic Perspective
Today's Web-enabled deluge of electronic data calls for automated methods of data analysis. Machine learning provides these, developing methods that can automatically detect patterns in data and then use the uncovered patterns to predict fu...
Machine learning in materials science
Abstract Traditional methods of discovering new materials, such as the empirical trial and error method and the density functional theory (DFT)‐based method, are unable to keep pace with the development of materials science today due to the...
https://doi.org/10.1002/inf2.12028
Machine Learning
In machine learning, a computer first learns to perform a task by studying a training set of examples. The computer then performs the same task with data it hasn't encountered before. This article presents a brief overview of machine-learni...
https://doi.org/10.1109/ms.2016.114
Elements of Machine Learning
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...
Machine learning phases of matter
https://doi.org/10.1038/nphys4035
Machine learning and the physical sciences
In October 2018 an APS Physics Next Workshop on Machine Learning was held in Riverhead, NY. This article reviews and summarizes the proceedings of this very broad, emerging field.This needs to be a placard in the left-hand column, with a cu...
https://doi.org/10.1103/revmodphys.91.045002
Pattern Recognition and Machine Learning
(2007). Pattern Recognition and Machine Learning. Technometrics: Vol. 49, No. 3, pp. 366-366....
https://doi.org/10.1198/tech.2007.s518