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Explainable machine learning for predicting clinical outcomes in HIV/TB co-infection: a comparative retrospective study

Qingfeng Sun, Kai Zhang, Yuanlong Xu, Mengmei Luo et al. • BMC Infectious Diseases (2025)

Abstract Background HIV/TB co-infection presents substantial public-health challenges, showing greater treatment-failure and mortality rates than tuberculosis alone. Recent advances in machine learning (ML) provide a robust means of identif...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12879-025-11998-w

Integrated Bioinformatics Analysis and Experimental Verification of Immune Cell Infiltration and the Related Core Genes in Ulcerative Colitis

Zhao D, Qin D, Yin L, Yang Q • Pharmacogenomics and Personalized Medicine (2023)

Danya Zhao,1 Danping Qin,2 Liming Yin,3 Qiang Yang4 1The First School of Clinical Medicine of Zhejiang Chinese Medical University, Hangzhou, People’s Republic of China; 2Department of Gastroenterology, The First Affiliated Hospital of Zheji...

DOAJ Open Access (DOAJ)

The association of Coronavirus Disease-19 mortality and prior bacille Calmette-Guerin vaccination: a robust ecological analysis using unsupervised machine learning

Nathan A. Brooks, Ankur Puri, Sanya Garg, Swapnika Nag et al. • Scientific Reports (2021)

Abstract Population-level data have suggested that bacille Calmette-Guerin (BCG) vaccination may lessen the severity of Coronavirus Disease-19 (COVID-19) prompting clinical trials in this area. Some reports have demonstrated conflicting res...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-020-80787-z

Machine Learning Model Coupled with Graphical User Interface for Predicting Mechanical Properties of Flax Fiber

T. Nageshkumar, Prateek Shrivastava, L. Ammayapan, Manisha Jagadale et al. • Journal of Natural Fibers (2025)

Machine learning model coupled with graphical user interface was developed to predict mechanical properties of flax fiber. The experiment was conducted using test setup which applies constant rate of loading (CRL). Flax fiber was tested und...

DOAJ Open Access (DOAJ) DOI: 10.1080/15440478.2025.2502662

Spatial analysis of smart tourism contrasts A comparison between tourist attractions in Cairo and Dubai

Walaa Mohamed Najeb • Al-Mağallah Al-ʿilmiyyaẗ Li Kulliyyaẗ Al-Adāb - Ǧāmiʿaẗ Asyūṭ (2026)

Technology has undergone rapid advancements, significantly impacting various sectors, with the tourism industry emerging as one of the most benefited. This research examines several key aspects, including: An overview of Cairo and Dubai as ...

DOAJ Open Access (DOAJ) DOI: 10.21608/aakj.2025.429364.2248

Machine learning for neuroimaging with scikit-learn

Alexandre Abraham, Fabián Pedregosa, Michael Eickenberg, Philippe Gervais et al. • Frontiers in Neuroinformatics (2014)

Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series....

OPENALEX cc-by DOI: https://doi.org/10.3389/fninf.2014.00014 PMC: 3930868

Understanding Machine Learning

Shai Shalev‐Shwartz, Shai Ben-David • Cambridge University Press eBooks (2014)

Machine learning is one of the fastest growing areas of computer science, with far-reaching applications. The aim of this textbook is to introduce machine learning, and the algorithmic paradigms it offers, in a principled way. The book prov...

OPENALEX DOI: https://doi.org/10.1017/cbo9781107298019

Bayesian Reasoning and Machine Learning

David Barber • Cambridge University Press eBooks (2012)

Machine learning methods extract value from vast data sets quickly and with modest resources. They are established tools in a wide range of industrial applications, including search engines, DNA sequencing, stock market analysis, and robot ...

OPENALEX DOI: https://doi.org/10.1017/cbo9780511804779

Machine Learning: An Applied Econometric Approach

Sendhil Mullainathan, Jann Spiess • The Journal of Economic Perspectives (2017)

Machines are increasingly doing “intelligent” things. Face recognition algorithms use a large dataset of photos labeled as having a face or not to estimate a function that predicts the presence y of a face from pixels x. This similarity to ...

OPENALEX DOI: https://doi.org/10.1257/jep.31.2.87

Machine learning methods in chemoinformatics

John B. O. Mitchell • Wiley Interdisciplinary Reviews Computational Molecular Science (2014)

Machine learning algorithms are generally developed in computer science or adjacent disciplines and find their way into chemical modeling by a process of diffusion. Though particular machine learning methods are popular in chemoinformatics ...

OPENALEX cc-by DOI: https://doi.org/10.1002/wcms.1183 PMC: 4180928

Machine learning for precision medicine

Sarah J. MacEachern, Nils D. Forkert • Genome (2020)

Precision medicine is an emerging approach to clinical research and patient care that focuses on understanding and treating disease by integrating multi-modal or multi-omics data from an individual to make patient-tailored decisions. With t...

OPENALEX Open Access DOI: https://doi.org/10.1139/gen-2020-0131

Machine learning for combustion

Lei Zhou, Yuntong Song, Weiqi Ji, Haiqiao Wei • Energy and AI (2021)

Combustion science is an interdisciplinary study that involves nonlinear physical and chemical phenomena in time and length scales, including complex chemical reactions and fluid flows. Combustion widely supplies energy for powering vehicle...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.egyai.2021.100128

Machine Learning

Mohssen M. Z. E. Mohammed, Muhammad Badruddin Khan, Eihab B. M. Bashier • CRC Press eBooks (2016)

Machine learning, one of the top emerging sciences, has an extremely broad range of applications. However, many books on the subject provide only a theoretical approach, making it difficult for a newcomer to grasp the subject material. This...

OPENALEX DOI: https://doi.org/10.1201/9781315371658