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Development and validation of a predictive model for diabetic peripheral neuropathy with type 2 diabetes mellitus in Xinjiang, China

Asiguli Adili, Maihesumu Aikemu, Karanvir Singh Rana, Yihan Wei et al. • Scientific Reports (2025)

Abstract This study aims to identify risk factors associated with diabetic peripheral neuropathy (DPN) in patients with type 2 diabetesmellitus (T2DM) and to develop a predictive model to support clinical decision-making. A total of 1,001 p...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-19922-7

Machine Learning in Healthcare Communication

Sarkar Siddique, James C. L. Chow • Encyclopedia (2021)

Machine learning (ML) is a study of computer algorithms for automation through experience. ML is a subset of artificial intelligence (AI) that develops computer systems, which are able to perform tasks generally having need of human intelli...

OPENALEX cc-by DOI: https://doi.org/10.3390/encyclopedia1010021

Real time identification of phishing attacks through machine learning enhanced browser extensions

Monika Dandotiya, Nikhil Kumar Goyal, Ajay Khunteta, Babita Tiwari • Scientific Reports (2026)

Abstract Phishing attack continues to rank among the deadliest online threats. They create phony websites in an attempt to obtain personal data. This study offers a framework for a browser extension that uses machine learning to examine URL...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-026-35655-7

Prediction of emergency department revisits among child and youth mental health outpatients using deep learning techniques

Simran Saggu, Hirad Daneshvar, Reza Samavi, Paulo Pires et al. • BMC Medical Informatics and Decision Making (2024)

Abstract Background The proportion of Canadian youth seeking mental health support from an emergency department (ED) has risen in recent years. As EDs typically address urgent mental health crises, revisiting an ED may represent unmet menta...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12911-024-02450-1

Exploiting the features of deep residual network with SVM classifier for human posture recognition.

Irfan Kareem, Syed Farooq Ali, Muhammad Bilal, Muhammad Shehzad Hanif • PLoS ONE (2024)

Over the last decade, there have been a lot of advances in the area of human posture recognition. Among multiple approaches proposed to solve this problem, those based on deep learning have shown promising results. Taking another step in th...

DOAJ Open Access (DOAJ) DOI: 10.1371/journal.pone.0314959

Efficient covid19 disease diagnosis based on cough signal processing and supervised machine learning

Khaled Bensid, Abdelhai Lati, Azeddine Benlamoudi, Brahim Elkhalil Ghouar et al. • Diagnostyka (2022)

The spread of the coronavirus has claimed the lives of millions around the world, which led to the emergence of an economic and health crisis at the global level, which prompted many researchers to submit proposals for early diagnosis of th...

DOAJ Open Access (DOAJ) DOI: 10.29354/diag/156751

Very Deep Convolutional Neural Networks for Complex Land Cover Mapping Using Multispectral Remote Sensing Imagery

Masoud Mahdianpari, Bahram Salehi, Mohammad Rezaee, Fariba Mohammadimanesh et al. • Remote Sensing (2018)

Despite recent advances of deep Convolutional Neural Networks (CNNs) in various computer vision tasks, their potential for classification of multispectral remote sensing images has not been thoroughly explored. In particular, the applicatio...

DOAJ Open Access (DOAJ) DOI: 10.3390/rs10071119

GAUSSIAN PROCESSES FOR MACHINE LEARNING

Matthias Seeger • International Journal of Neural Systems (2004)

Gaussian processes (GPs) are natural generalisations of multivariate Gaussian random variables to infinite (countably or continuous) index sets. GPs have been applied in a large number of fields to a diverse range of ends, and very many dee...

OPENALEX Open Access DOI: https://doi.org/10.1142/s0129065704001899

Deciphering Exhaled Aerosol Fingerprints for Early Diagnosis and Personalized Therapeutics of Obstructive Respiratory Diseases in Small Airways

Xiuhua April Si, Jinxiang Xi • Journal of Nanotheranostics (2021)

Respiratory diseases often show no apparent symptoms at their early stages and are usually diagnosed when permanent damages have been made to the lungs. A major site of lung pathogenesis is the small airways, which make it highly challengin...

DOAJ Open Access (DOAJ) DOI: 10.3390/jnt2030007

Exploring Traffic Patterns Through Network Programmability: Introducing SDNFLow, a Comprehensive OpenFlow-Based Statistics Dataset for Attack Detection

Jorge Buzzio-Garcia, Jaime Vergara, Santiago Rios-Guiral, Christian Garzon et al. • IEEE Access (2024)

In the contemporary cybersecurity landscape, robust attack detection mechanisms are important for organizations. However, the current state of research in Software-Defined Networking (SDN) suffers from a notable lack of recent SDN-OpenFlow-...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3378271

Precision water quality indices forecasting through an optimized hybrid SMW-LSSVM-R model enhanced by SATLDE and uncertainty analysis

Heming Jia, Marjan Kordani, Iman Ahmadianfar, Arvin Samadi Koucheksaraee et al. • Engineering Applications of Computational Fluid Mechanics (2026)

Precise forecasting of water quality indices (WQI) is essential for safeguarding ecosystems, human health, and sustainable water resource management. This study presents an innovative approach for evaluating river Water Quality Indices usin...

DOAJ Open Access (DOAJ) DOI: 10.1080/19942060.2025.2602582

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

DATA MINING AND MACHINE LEARNING IN ASTRONOMY

Nicholas M. Ball, Robert J. Brunner • International Journal of Modern Physics D (2010)

We review the current state of data mining and machine learning in astronomy. Data Mining can have a somewhat mixed connotation from the point of view of a researcher in this field. If used correctly, it can be a powerful approach, holding ...

OPENALEX Open Access DOI: https://doi.org/10.1142/s0218271810017160

Efficacy of ChatGPT in Cantonese Sentiment Analysis: Comparative Study

Ziru Fu, Yu Cheng Hsu, Christian S Chan, Chaak Ming Lau et al. • Journal of Medical Internet Research (2024)

BackgroundSentiment analysis is a significant yet difficult task in natural language processing. The linguistic peculiarities of Cantonese, including its high similarity with Standard Chinese, its grammatical and lexical uniqueness, and its...

DOAJ Open Access (DOAJ) DOI: 10.2196/51069

A diagnostic model based on clinical indicators and radiomics features for superior labral anterior and posterior lesions in the shoulder joint

Hongyu Wang, Lin Wang, Lei Shi, Fei Wang et al. • Journal of Orthopaedic Surgery (2026)

Background Superior labrum anterior and posterior (SLAP) lesions are a common cause of shoulder pain and instability. Accurate diagnosis remains challenging in clinical practice. This study aims to develop and evaluate radiomics models and ...

DOAJ Open Access (DOAJ) DOI: 10.1177/10225536261418429

Machine learning in pain research

Jörn Lötsch, Alfred Ultsch • Pain (2017)

1. Introduction Pain and pain chronification are incompletely understood and unresolved medical problems that continue to have a high prevalence.14 It has been accepted that pain is a complex phenomenon.2,32,72 Contemporary methods of compu...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1097/j.pain.0000000000001118 PMC: 5895117

Identification of immune-associated biomarkers of diabetes nephropathy tubulointerstitial injury based on machine learning: a bioinformatics multi-chip integrated analysis

Lin Wang, Jiaming Su, Zhongjie Liu, Shaowei Ding et al. • BioData Mining (2024)

Abstract Background Diabetic nephropathy (DN) is a major microvascular complication of diabetes and has become the leading cause of end-stage renal disease worldwide. A considerable number of DN patients have experienced irreversible end-st...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13040-024-00369-x

Deep Learning-Based Visual Complexity Analysis of Electroencephalography Time-Frequency Images: Can It Localize the Epileptogenic Zone in the Brain?

Navaneethakrishna Makaram, Sarvagya Gupta, Matthew Pesce, Jeffrey Bolton et al. • Algorithms (2023)

In drug-resistant epilepsy, a visual inspection of intracranial electroencephalography (iEEG) signals is often needed to localize the epileptogenic zone (EZ) and guide neurosurgery. The visual assessment of iEEG time-frequency (TF) images i...

DOAJ Open Access (DOAJ) DOI: 10.3390/a16120567