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Leveraging Cloud Technology for Personalized Multiple Sclerosis Care: A Comprehensive Data Management and Visualization Approach

Jose Manuel PINILLOS RUBIO, Minerva VIGUERA MORENO • Applied Medical Informatics (2024)

This project develops a cloud-based solution for securely managing clinical data and patient-reported outcomes (PROMs) for multiple sclerosis (MS) patients. Utilizing REDCap for data collection, we incorporated clinical outcomes and PROMs f...

DOAJ Open Access (DOAJ)

Synergistic multi-altimeter for estimating water level in the coastal zone of Beibu Gulf using SEL, ALES + and BFAST algorithms

Jiaoling Qin, Jiaoling Qin, Sunzhe Li, Sunzhe Li et al. • Frontiers in Marine Science (2023)

Accurately monitoring and predicting the large-scale dynamic changes of water levels in coastal zones is essential for its protection, restoration and sustainable development. However, there has been a challenge for achieving this goal usin...

DOAJ Open Access (DOAJ) DOI: 10.3389/fmars.2022.1113387

Machine learning and the physical sciences

Giuseppe Carleo, J. I. Cirac, Kyle Stuart Cranmer, Laurent Daudet et al. • Reviews of Modern Physics (2019)

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...

OPENALEX Open Access DOI: https://doi.org/10.1103/revmodphys.91.045002

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

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

A machine learning approach predicts future risk to suicidal ideation from social media data

Arunima Roy, Katerina Nikolitch, Rachel McGinn, Safiya Jinah et al. • npj Digital Medicine (2020)

Abstract Machine learning analysis of social media data represents a promising way to capture longitudinal environmental influences contributing to individual risk for suicidal thoughts and behaviors. Our objective was to generate an algori...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41746-020-0287-6

Artificial intelligence in glaucoma

Chengjie Zheng, Thomas V. Johnson, Aakriti Garg Shukla, Michael Vincent Boland • Current Opinion in Ophthalmology (2018)

PURPOSE OF REVIEW: The use of computers has become increasingly relevant to medical decision-making, and artificial intelligence methods have recently demonstrated significant advances in medicine. We therefore provide an overview of curren...

OPENALEX DOI: https://doi.org/10.1097/icu.0000000000000552

Preoperative and Prognostic Prediction of Microvascular Invasion in Hepatocellular Carcinoma: A Review Based on Artificial Intelligence

Yu Jiang Master of Engineering, Kang Wang Master of Medicine, Yu-Ran Wang Master of Engineering, Yan-Jun Xiang Master of Medicine et al. • Technology in Cancer Research & Treatment (2023)

Microvascular invasion of hepatocellular carcinoma is an important factor affecting tumor recurrence after liver resection and liver transplantation. There are many ways to classify microvascular invasion, however, an international consensu...

DOAJ Open Access (DOAJ) DOI: 10.1177/15330338231212726

Timor Leste in ASEAN: Implications for ASEAN-Led Economic Multilateralism in the Digital Field

Evgeny A. Kanaev • Vestnik RUDN. International Relations (2026)

The paper explores the main implications of East Timor’s accession to the Association of Southeast Asian Nations (ASEAN) in October 2025 for ASEAN-led economic projects and initiatives in the digital field. The research aims to identify the...

DOAJ Open Access (DOAJ) DOI: 10.22363/2313-0660-2026-26-3-476-488

Impact of AI-quantified fluid dynamics on visual outcomes over 5 years in patients with treatment-naïve nAMD from the FRB! registry

Philipp Fuchs, Ursula Schmidt-Erfurth, Leonard M. Coulibaly, Hrvoje Bogunovic et al. • Scientific Reports (2025)

Abstract To investigate the impact of retinal fluid dynamics on visual outcomes in patients with treatment-naïve neovascular age-related macular degeneration (nAMD) treated in the real world over 5 years using approved AI-based fluid monito...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-025-17417-z

Artificial intelligence in medical education

Ken Masters • Medical Teacher (2019)

Artificial intelligence (AI) is a growing phenomenon, and will soon facilitate wide-scale changes in many professions, including medical education. In order for medical educators to be properly prepared for AI, they will need to have at lea...

OPENALEX DOI: https://doi.org/10.1080/0142159x.2019.1595557

Early math interest and the development of math skills.

Paige H. Fisher, Jennifer Dobbs‐Oates, Greta L. Doctoroff, David Harvey Arnold • Journal of Educational Psychology (2012)

Prior models suggest that math attitudes and ability might strengthen each other over time in a reciprocal fashion (Ma, 1997). The current study investigated the relationship between math interest and skill both concurrently and over time i...

OPENALEX DOI: https://doi.org/10.1037/a0027756