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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

Machine Learning and Law

Harry Surden • Colorado Law Scholarly Commons (University of Colorado Colorado Springs) (2014)

This Article explores the application of machine learning techniques within the practice of law. Broadly speaking “machine learning” refers to computer algorithms that have the ability to “learn” or improve in performance over time on some ...

OPENALEX Open Access

Enhancing host-pathogen phenotyping dynamics: early detection of tomato bacterial diseases using hyperspectral point measurement and predictive modeling

Mafalda Reis Pereira, Mafalda Reis Pereira, Filipe Neves dos Santos, Fernando Tavares et al. • Frontiers in Plant Science (2023)

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...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpls.2023.1242201

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

Taxonomy-based data representation for data mining: an example of the magnitude of risk associated with H. pylori infection

Inese Polaka, Danute Razuka-Ebela, Jin Young Park, Marcis Leja • BioData Mining (2021)

Abstract Background The amount of available and potentially significant data describing study subjects is ever growing with the introduction and integration of different registries and data banks. The single specific attribute of these data...

DOAJ Open Access (DOAJ) DOI: 10.1186/s13040-021-00271-w

Multi-Resolution and Multi-Temporal Satellite Remote Sensing Analysis to Understand Human-Induced Changes in the Landscape for the Protection of Cultural Heritage: The Case Study of the MapDam Project, Syria

Nicodemo Abate, Diego Ronchi, Sara Elettra Zaia, Gabriele Ciccone et al. • Land (2025)

This study presents a multi-resolution and multi-temporal remote sensing approach to assess human-induced changes in cultural landscapes, with a focus on the archaeological site of Amrit (Syria) within the MapDam project. By integrating sat...

DOAJ Open Access (DOAJ) DOI: 10.3390/land14112233

Python Machine Learning

Sebastian Raschka (2015)

Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analyticsAbout This BookLeverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualizationLearn effect...

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The Moral Psychology of Artificial Intelligence

Jean‐François Bonnefon, Iyad Rahwan, Azim Shariff • Annual Review of Psychology (2023)

Moral psychology was shaped around three categories of agents and patients: humans, other animals, and supernatural beings. Rapid progress in artificial intelligence has introduced a fourth category for our moral psychology to deal with: in...

OPENALEX cc-by DOI: https://doi.org/10.1146/annurev-psych-030123-113559

Neurosurgery and artificial intelligence

Mohammad Mofatteh • AIMS neuroscience (2021)

Neurosurgeons receive extensive and lengthy training to equip themselves with various technical skills, and neurosurgery require a great deal of pre-, intra- and postoperative clinical data collection, decision making, care and recovery. Th...

OPENALEX cc-by DOI: https://doi.org/10.3934/neuroscience.2021025 PMC: 8611194

Artificial intelligence model to predict pregnancy and multiple pregnancy risk following in vitro fertilization-embryo transfer (IVF-ET)

Jen-Yu Wen, Chung-Fen Liu, Ming-Ting Chung, Yung-Chieh Tsai • Taiwanese Journal of Obstetrics & Gynecology (2022)

Objective: To decrease multiple pregnancy risk and sustain optimal pregnancy chance by choosing suitable number of embryos during transfer, this study aims to construct artificial intelligence models to predict the pregnancy outcome and mul...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.tjog.2021.11.038

Predicting Choroidal Nevus Transformation to Melanoma Using Machine Learning

Prashant D. Tailor, MD, Piotr K. Kopinski, MD, PhD, Haley S. D’Souza, MD, David A. Leske, MS et al. • Ophthalmology Science (2025)

Purpose: To develop and validate machine learning (ML) models to predict choroidal nevus transformation to melanoma based on multimodal imaging at initial presentation. Design: Retrospective multicenter study. Participants: Patients diagnos...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.xops.2024.100584

PERMEPSY: a multicentre, randomized, double-blind proof-of-concept trial of personalized metacognitive training for adults with psychosis — a study protocol

Maria Lamarca, Maria Lamarca, Maria Lamarca, Maria Lamarca et al. • Frontiers in Psychiatry (2026)

BackgroundWhile psychological interventions are effective at improving symptoms of psychosis, accessible, cost- and time-efficient treatments remain limited. Personalized medicine has emerged as a promising approach, tailoring interventions...

DOAJ Open Access (DOAJ) DOI: 10.3389/fpsyt.2026.1711659

Artificial intelligence in orthopaedic surgery

Anthony B. Lisacek-Kiosoglous, Amber S. Powling, Andreas Fontalis, Ayman Gabr et al. • Bone and Joint Research (2023)

The use of artificial intelligence (AI) is rapidly growing across many domains, of which the medical field is no exception. AI is an umbrella term defining the practical application of algorithms to generate useful output, without the need ...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1302/2046-3758.127.bjr-2023-0111.r1 PMC: 10329876

Teens, Tech, and Talk: Adolescents’ Use of and Emotional Reactions to Snapchat’s My AI Chatbot

Gaëlle Vanhoffelen, Laura Vandenbosch, Lara Schreurs • Behavioral Sciences (2025)

Due to technological advancements such as generative artificial intelligence (AI) and large language models, chatbots enable increasingly human-like, real-time conversations through text (e.g., OpenAI’s ChatGPT) and voice (e.g., Amazon’s Al...

DOAJ Open Access (DOAJ) DOI: 10.3390/bs15081037

The Integration of Cone Beam Computed Tomography, Artificial Intelligence, Augmented Reality, and Virtual Reality in Dental Diagnostics, Surgical Planning, and Education: A Narrative Review

Aida Meto, Gerta Halilaj • Applied Sciences (2025)

(1) Background: Advancements in dental imaging technologies have significantly transformed diagnostic and surgical practices. The integration of cone beam computed tomography (CBCT), artificial intelligence (AI), augmented reality (AR), and...

DOAJ Open Access (DOAJ) DOI: 10.3390/app15116308

Artificial Intelligence Adoption and Employee Productivity in Vietnam’s Technology Sector: Evidence From Telecommunications and IT Firms

Nguyen Trung Kien, Quang Hung Do, Nguyen Tung Duong • SAGE Open (2026)

This study investigates the impact of artificial intelligence (AI) adoption on employee productivity within Vietnam’s technology sector, with a particular focus on telecommunications and information technology firms. Using survey data colle...

DOAJ Open Access (DOAJ) DOI: 10.1177/21582440261488067