Dr. Verónica Espinoza - Health Research

Health Research

Interactive medical presentations, scientific research, dynamic visualizations, and biomedical applications.

By Dr. Verónica Espinoza

In this section, I share a compilation of materials specially prepared and developed for my conferences, classes, training sessions, and personal projects. It includes interactive medical presentations, scientific research, dynamic visualizations, biomedical applications and other resources. More content will be added soon.

Thematic content

1.-Biomedical applications

A portfolio of clinical intelligence applications I have developed:

Lupus Landscape © - Real-time literature v1.0
Bone Sarcoidosis © - Clinical Intelligence-v1.0
PubMed-Graph App © - Mapping Scientific Collaborations v1.1.
PubMed Semantic Explorer © - Identify key connections in biomedical research v1.1
AlergoFDAexplorer© - Excipients · Hypersensitivity Warnings · v1.0 (coming soon)
Clinical Trials Monitor© Real-Time Data v1.0 (coming soon)
FDA Drug Explorer © Regulatory · Clinical · Pharmacological data. v1.0 (coming soon)

2.-Interactive presentations

A collection of dynamic presentations focused on key medical topics:

- Open Access Research on Lupus Treatments (2024-2025): An Interactive Exploration.
- Artificial Intelligence in Context: History, Models, and Applications in Rheumatology

Open Access Articles on Rheumatoid Arthritis (2024-2025)
Sjögren Treatment Strategies: A Comprehensive Overview of Current and Emerging Therapies (2020-2025)
Polymyalgia Rheumatica: Advances in Contemporary and Novel Therapies (2020–2025).

3.-Dynamic Visualizations

A series of interactive visualizations covering diverse medical topics:

Artificial Intelligence and Neuroscience: interactive dashboard containing articles on "Neuroscience and Artificial Intelligence", as well as an interactive semantic map created from the abstracts of these articles.
ChatGPT in Medicine: A semantic map based on 2,448 articles.

More dynamic visualizations will be added soon..

All the sections presented below are original research materials prepared by Dr. Veronica Espinoza

These are open‑access educational resources. If you use these materials, proper credit must be given.

Biomedical Applications

This section hosts my portfolio of clinical intelligence applications, designed to transform vast open-access research into intuitive visual landscapes. Each tool leverages dynamic visualizations to streamline the exploration of global medical resources, providing specialists with an integrated environment for comprehensive data analysis and review.

Developed by Dr. Verónica Espinoza.

Release date: April 13, 2026

Lupus LandScape is a web application that automatically searches for the most recent scientific articles on systemic lupus erythematosus (SLE) using open-access databases.

It queries OpenAlex and retrieves English-language, open-access, non-retracted articles, returning the 150 most recent results for each of the 4 clinical categories: Diagnosis, Treatment, Lupus Nephritis and Biomarkers & Outcomes.

This tool features Journal and Word Clouds for visual trend analysis, along with detailed Article Tables that include citations and full-text links. Users can easily organize data using integrated filters and export results to Excel for offline analysis.

It is free, works in the browser with no installation required.

Developed by Dr. Verónica Espinoza.

Release date: April 8, 2026

Bone Sarcoidosis is a web application that automatically searches for the most recent scientific articles on bone sarcoidosis using open-access databases.

It queries OpenAlex and retrieves English-language, open-access, non-retracted articles published between 2020 and the current year, organized into 4 clinical categories: General, Diagnosis, Treatment and Specific manifestations

It is free, works in the browser with no installation required.

Developed by Dr. Verónica Espinoza.

Version 1.0 release date: April 18, 2025

Version 1.1 release date: April 20, 2026

Description: This application integrates in real-time with the PubMed database via the official NCBI E-utilities API. It allows users to search for an author, retrieve their publications, and visualize co-authorship networks, word clouds from titles, and publication trends over time.

Additionally, users can download the results as a CSV file, export the co-authorship network as a GEXF file for advanced analysis in tools like Gephi or NodeXL, sort articles by relevance or publication date, filter by year range (Entire career, Last 2, 5, 10 years, or Since 2000), adjust the minimum number of collaborations required to appear in the network, and delete individual articles to remove homonyms or irrelevant publications.

t is free, works in the browser with no installation required.

Citation

Espinoza-González, V. (2025). PubMed-Graph App: Mapping Scientific Collaborations (v 1.0). Zenodo. https://doi.org/10.5281/zenodo.15238965

Developed by Dr. Verónica Espinoza.

Version 1.0 release date: January 10, 2025

Version 1.1 release date: April 10, 2026

Description: This application integrates in real-time with the PubMed database via the official NCBI E-utilities API. It allows users to search for a topic, retrieve publications, and visualize word co-occurrence networks, word clouds from titles, and top journals.

Users can download the results as a CSV file, export the semantic network as a GEXF file for advanced analysis in tools like Gephi or NodeXL, sort articles by relevance or publication date, adjust the number of nodes displayed in the network, filter by year range (1, 2, 3, or 5 years), and refine searches using interactive sliders for node size and network density.

It is free, works in the browser with no installation required.

Interactive Presentations

This section features a collection of dynamic presentations focused on key medical topics. It combines interactive visualizations, semantic maps, and tables with curated open-access research articles on relevant medical subjects, providing a comprehensive resource for clinical consultation and academic review.

Open Access Articles on Rheumatoid Arthritis (2024-2025)

Dr. Verónica Espinoza

read

Artificial Intelligence in Context: History, Models, and Applications in Rheumatology

Dr. Verónica Espinoza

read

Open Access Research on Lupus Treatments (2024-2025): An Interactive Exploration

Dr. Verónica Espinoza

read

Sjögren Treatment Strategies:

A Comprehensive Overview of Current and Emerging Therapies (2020-2025)

Dr. Verónica Espinoza

read

Polymyalgia Rheumatica

Advances in Contemporary and Novel Therapies (2020–2025)

Dr. Verónica Espinoza

read

Dynamic Visualizations

This section features a series of dynamic visualizations I have developed covering diverse medical topics. These range from dynamic dashboards for clinical consultation to interactive semantic maps designed for exploring complex concepts and thematic clusters.

A) Artificial Intelligence and Neuroscience

1.1 Dashboard with open-access articles on Neuroscience and Artificial Intelligence

The dashboard includes the article title, Authors, Journal, Year and Link, allowing you to access any article of interest. I have also added filters to help you explore according to your interests.

1.2 Semantic Map on Neuroscience and Artificial Intelligence

The following visualization is based on the abstracts of the articles from the previous dashboard. Each node represents a concept, and the size of the nodes corresponds to the frequency with which that concept appears throughout the text. The edges represent co-occurrences between nodes, that is, the number of times those nodes appear close to each other in the analyzed text. The colors indicate themes grouped by thematic similarities, providing an overview of the ongoing work in this area.

Some relevant themes and concepts observed in this semantic map are:

Neuroimaging and Computational Methods:
“image”, “neuroimage”, “segmentation”, “algorithm”, “MRI”, showing a strong focus on AI for brain image analysis.
Clinical Diagnosis and Neurological Disorders:
“diagnosis”, “clinical”, “neurological”, “disease”, “neurodegenerative”, reflecting applications of AI in medical decision-making and early detection.
Neurointervention and Psychiatry:
“neuromodulation”, “brain stimulation”, “psychiatry”, “pain”, emphasizing AI’s role in treatment optimization.
Explainability and Cognitive Insights:
“explainable”, “cognitive”, “human”, highlighting interest in interpretable models for clinical use.
Oncology and Tumor Analysis:
“oncology”, “tumor”, “spinal cord”, pointing to emerging AI applications in neuro-oncology.

▶ To interact with the network, click on the nodes of interest or use the zoom function to explore it in greater detail.

B) ChatGPT in Medicine

The following visualization is based on the titles of 2,448 open-access PubMed articles on ChatGPT and Medicine published between 2022 and 2025. The tool used was NocodeFunctions tool. Each node represents a concept, and its size corresponds to the frequency with which that concept appears in the text. The edges represent co-occurrences between nodes, meaning the number of times those concepts appear close to each other. The colors indicate thematic clusters, offering an overview of the main topics in this area.

Some relevant themes and concepts observed in this semantic map are:

Generative AI and Large Language Models: “chatgpt”, “generative”, “google gemini”, “llm”, and “transformer”, highlighting a massive shift toward using pre-trained models for medical tasks.
Medical Education and Academic Research: “medical education”, “student”, “scientific”, “abstract”, and “peer review”, showing how AI is being integrated into student learning and the automation of research workflows.
Clinical Performance and Validation: “performance”, “accuracy”, “comparison”, “evaluation”, and “systematic review”, reflecting a strong focus on testing the reliability of AI against clinical standards.
Specialized Diagnostics and Examination: “diagnostic”, “radiology”, “orthopedic”, “surgical”, and “medical licensing examination”, pointing to AI’s role in passing professional exams and assisting in surgical/radiological fields.
Ethics and Data Governance: “ethical”, “guideline”, “privacy”, “quality”, and “standard”, highlighting the ongoing efforts to regulate AI use and ensure data integrity in medicine.

➡️Explore this network interactively here.