awesome-visual-analytics-healthcare

Awesome Visual Analytics in Healthcare

A community-curated list of awesome resources for visual analytics in healthcare. This list will be of interest to wide audience, including, students, academics, practitioners and healthcare professionals.

AMIA Visual Analytics Working Group maintains this list, although we do not endorse any resource in particular. We welcome suggestions as GitHub Pull Requests or Discussion posts or via this Airtable form (no login required).

Related Awesome lists:

Books
Checklists & Guidelines
Collections
Conferences
Courses
Publications
Tools

Books

Effective Data Visualization: The Right Chart for the Right Data by Stephanie Evergreen (not specific to healthcare)
Fundamentals of Data Visualization by Claus O. Wilke (not specific to healthcare but freely accessible under the Creative Commons License)
Storytelling with Data: A Data Visualization Guide for Business Professionals by Cole Nussbaumer Knaflic (not specific to healthcare)
Tableau for Healthcare by Daniel Benevento, Katherine Rowell, Janet Steeger
The Functional Art: An Introduction to Information Graphics and Visualization by Alberto Cairo (not specific to healthcare)
The Visual Display of Quantitative Information by Edward R. Tufte (not specific to healthcare)
Visualize This: The FlowingData Guide to Design, Visualization, and Statistics by Nathan Yau (not specific to healthcare)
Visualizing Health and Healthcare Data by Lindsay Betzendahl, Cambria Brown & Katherine Rowell

Checklists & Guidelines

Guides & Principles

Data Visualization Design - UC Berkeley Library guide on data visualization design principles, including chart selection, color, and accessibility (not specific to healthcare).
Designing Effective Data Visualizations (guide page) - Johns Hopkins University Libraries guide on designing effective data visualizations, with companion PDF handout (not specific to healthcare).
Data Visualization Guide - Yale University Library research guide covering data visualization principles, tools, and resources.
Development of a usability checklist for public health dashboards to identify violations of usability principles by Bahareh Ansari & Erika G Martin from University at Albany on JAMIA - A usability checklist for public health dashboards with 86 items covering 11 areas of considerations.
The Development of Heuristics for Evaluation of Dashboard Visualizations by Dawn Dowding & Jacqueline A. Merrill from University of Manchester & Columbia University on Appl Clin Inform - A checklist of usability heuristics for evaluating information visualization systems that can contribute to assuring high quality in electronic data systems developed for health care.
Visual Mapping – The Elements of Information Visualization by the Interaction Design Foundation - introductory article on the visual encoding building blocks of information visualization (not specific to healthcare).

Misleading Visualizations & Common Pitfalls

How to Spot Visualization Lies by Nathan Yau on FlowingData - a field guide to identifying common deceptive chart patterns.
Misleading Graph (Wikipedia) - reference article cataloging common misleading-graph techniques (truncated axes, distorted scales, etc.).
Replacement of the Aortic Root with a Pulmonary Autograft in Children and Young Adults with Aortic-Valve Disease on New England Journal of Medicine - frequently cited as an “extra-dimension” 3D chart pitfall in healthcare visualization (not specific to healthcare best practices, but a healthcare-domain example of misleading design).
Why the National Review’s global temperature graph is so misleading on The Washington Post - canonical example of a scaled / compressed y-axis distorting interpretation.

Bad-Chart Galleries

Karl Broman – The Top Ten Worst Graphs - a curated gallery of poorly designed graphs from the scientific literature with critiques.
Junk Charts by Kaiser Fung - long-running blog critiquing real-world charts and proposing improved redesigns.
r/dataisugly - community-curated subreddit collecting bad data visualizations from the wild.
viz.wtf - a curated gallery of egregiously bad data visualizations.

Collections

Healthcare-Specific

EHR STAR by Qiru Wang - a collection of literature and datasets included in the state-of-the-art (STAR) report, EHR STAR: The State-of-the-art in Interactive EHR and PopHR Visualization
GenoCAT by Gehlenborg Lab - a database of genomic visualization tools
Visualization Design Studio led by Adriana Arcia more info on this page.
- A list of Online Visualization Resources by Adriana Arcia

Examples & Demos (Why Visualization Matters)

100 Data Viz Project - 100 different visualizations of the same dataset, illustrating how chart choice changes the story.
Anscombe’s Quartet - four datasets with near-identical summary statistics but very different visual distributions; classic demonstration of why summary stats alone are insufficient.
One Dataset Visualized 25 Ways by Nathan Yau on FlowingData - shows how the same data can be communicated very differently across 25 chart forms.
Same Stats, Different Graphs: Generating Datasets with Varied Appearance and Identical Statistics through Simulated Annealing by Justin Matejka & George Fitzmaurice (Autodesk Research) - the “DataSaurus dozen” extension of Anscombe’s quartet, demonstrating that statistically identical datasets can look radically different.

General Data-Viz Blogs & Resource Sites

blog.datawrapper.de - Datawrapper’s blog with practical articles on chart design, color, and storytelling.
FlowingData by Nathan Yau - long-running blog on data visualization design, tutorials, and projects.
Perceptual Edge by Stephen Few - articles and resources on quantitative information presentation.
Towards Data Science - Medium publication with many data-visualization tutorials and case studies (not specific to healthcare).
Visualising Data by Andy Kirk - resources, references, and commentary on data visualization practice.

Conferences

ACM CHI - the ACM CHI Conference on Human Factors in Computing Systems, the premier international conference on Human-Computer Interaction, hosted annually by ACM SIGCHI.
IEEE VIS - the premier forum for advances in visualization and visual analytics, hosting the IEEE Transactions on Visualization and Computer Graphics (TVCG) conference track annually.
VAHC Workshop - Visual Analytics in Healthcare Workshop is an annual academic event hosted alternatively at AMIA (on even years) and IEEE VIS (on odd years). The workshop is dedicated to the study of visual analytics in healthcare. The workshop is a forum for researchers and practitioners to present and discuss their work, and to identify research challenges and opportunities in the field.

Courses

Data Analytics and Visualization in Health Care from Rochester Institute of Technology on edX
Data Visualization Specialization from Johns Hopkins University on Coursera - covers foundational principles, specialized techniques, and practical applications for creating impactful visualizations (not specific to healthcare).

Publications

Featured in AMIA Year in Review

2024

TrajVis: a visual clinical decision support system to translate artificial intelligence trajectory models in the precision management of chronic kidney disease by Zuotian Li, et al, J Am Med Inform Assoc. 2024 Nov 1;31(11):2474-2485. doi: 10.1093/jamia/ocae158. PMID: 38916922; PMCID: PMC11491615.
Hybrid visualization-based framework for depressive state detection and characterization of atypical patients by Leon Kopitar, et al, J Biomed Inform. 2023 Nov;147:104535. doi: 10.1016/j.jbi.2023.104535. Epub 2023 Nov 4. PMID: 37926393.
Analysing disease trajectories in a cohort of 71,849 Patients: A visual analytics and statistical approach by Jon Kerexeta-Sarriegi, et al, Int J Med Inform. 2024 Aug;188:105466. doi: 10.1016/j.ijmedinf.2024.105466. Epub 2024 May 1. PMID: 38761458.
Design of an interface to communicate artificial intelligence-based prognosis for patients with advanced solid tumors: a user-centered approach by Catherine J Staes, et al, J Am Med Inform Assoc. 2023 Dec 22;31(1):174-187. doi: 10.1093/jamia/ocad201. PMID: 37847666; PMCID: PMC10746322.
Inpatient nurses’ preferences and decisions with risk information visualization by Alvin D Jeffery, et al, J Am Med Inform Assoc. 2023 Dec 22;31(1):61-69. doi: 10.1093/jamia/ocad209. PMID: 37903375; PMCID: PMC10746300.
HealthPrism: A Visual Analytics System for Exploring Children’s Physical and Mental Health Profiles with Multimodal Data by Zhihan Jiang, et al, IEEE Trans Vis Comput Graph. 2023 Oct 24;PP. doi: 10.1109/TVCG.2023.3326943. Epub ahead of print. PMID: 37874717.

2023

Integrating statistical and visual analytic methods for bot identification of health-related survey data by Annie T. Chen, …, Yan Zhang from University of Washington and UT Austin. Journal of Biomedical Informatics, July 2023

2022

Loon: Using Exemplars to Visualize Large-Scale Microscopy Data by Devin Lange, …, Alexander Lex from University of Utah on IEEE Transactions on Visualization and Computer Graphics - a visualization tool for analyzing drug screening data based on quantitative phase microscopy imaging for patient-specific cancer drug selection. GitHub Repo
VBridge: Connecting the Dots Between Features and Data to Explain Healthcare Models by Furui Cheng, …, Kalyan Veeramachaneni from Hong Kong University and MIT on IEEE Transactions on Visualization and Computer Graphics - VBridge incorporates ML explanations into clinicians’ decision-making workflow. GitHub Repo (MIT License)
A flexible framework for visualizing and exploring patient misdiagnosis over time by Wathsala Widanagamaachchi, …, Mkoto Jones from University of Utah on JBI - Framework for exploring the cohorts diagnoses over time

2020

Visual analogies, not graphs, increase patients’ comprehension of changes in their health status by Meghan Reading Turchio, …, Ruth Masterson Creber from Cornell, Columbia, others on JAMIA - Patient comprehension of their self-reported outcomes

2019

A federated EHR network data completeness tracking system by Hossein Estiri,…, Shawn N. Murphy from Massachusetts General Hospital on J Am Med Inform Assoc - DQe-c is an open source tool for evaluating completeness in EHR data repositories
A smartwatch-based framework for real-time and online assessment and mobility monitoring by Matin Kheirkhahan, …, Sanjay Ranka from University of Florida on J Biomed Inform

2018

A visual analytics approach for pattern-recognition in patient-generated data by Daniel Feller, …, Lena Mamykina from Columbia University on JAMIA - Authors developed Glucolyzer to help dieticians interpret glucose and meal data
Eye-Tracking Study to Enhance Usability of Molecular Diagnostics Reports in Cancer Precision Medicine by Vishakha Sharma, …, Subha Madhavan from Georgetown University on JCO Precision Oncology.

Academic Informatics

Data-Driven Healthcare: Challenges and Opportunities for Interactive Visualization by David Gotz & David Borland from University of North Carolina at Chapel Hill on IEEE Computer Graphics and Applications

Human-Computer Interaction / Human-centered Design

Consumer Health Informatics

Clinical Decision Support

Best practices for data visualization: creating and evaluating a report for an evidence-based fall prevention program by Srijesa Khasnabish, Zoe Burns, Madeline Couch, Mary Mullin, Randall Newmark, Patricia C Dykes from Brigham and Women’s Hospital on J Am Med Inform Assoc. 2020;27(2):308-314. doi: 10.1093/jamia/ocz190 - Iterative design and evaluation of a fall-prevention dashboard report; identifies best practices for clinician-facing data displays (high data-ink ratio, conservative color use, clear performance-vs-goal communication).

Visual Analytics System

Review Paper

EHR STAR: The State-of-the-art in Interactive EHR and PopHR Visualization by Qiru Wang & Robert Laramee from University of Nottingham on Computer Graphics Forum
Evaluating visual analytics for health informatics applications: a systematic review from the American Medical Informatics Association Visual Analytics Working Group Task Force on Evaluation by Danny Wu, …, David Gotz from AMIA Visual Analytics Working Group on JAMIA
Principles of Effective Data Visualization by Stephen R. Midway from Louisiana State University on Patterns (N Y). 2020;1(9):100141. doi: 10.1016/j.patter.2020.100141. PMID: 33336199 - Ten foundational principles for creating effective scientific data visualizations, covering geometry selection, color use, uncertainty representation, and communication strategies (not specific to healthcare).
Tasks, Techniques, and Tools for Genomic Data Visualization by Sabrina Nusrat, Theresa Harbig, and Nils Gehlenborg from Harvard University on Computer Graphics Forum

Tools

Chart Catalogs & Pickers

Data Viz Project - a catalog of chart types with filters by data shape, function, and family, useful for picking the right chart.
Data Visualisation Catalogue by Severino Ribecca - a catalog of visualization methods organized by the task they support.
From Data to Viz - a decision-tree explorer that recommends suitable chart types based on the structure of your data, with code examples.

Healthcare & Visual Analytics Platforms

CadenceEVA - a visual analytics platform for event sequence analysis.
PyHealth - a Python library for healthcare predictive tasks.
SandDance - a web-based application that enables you to more easily explore, identify, and communicate insights about tabular data.

General-Purpose Platforms

Observable - a collaborative notebook platform for building reactive data visualizations in JavaScript, widely used for prototyping bespoke charts.
Plotly Dash - an open-source Python framework for building analytical web applications and interactive dashboards.
Tableau - a widely used commercial BI and data visualization platform; see also the “Tableau for Healthcare” book listed under Books.

Color & Accessibility

Coblis – Color Blindness Simulator - upload an image and preview how it appears under different forms of color vision deficiency.
Color Oracle - free desktop color-blindness simulator (macOS / Windows / Linux) that applies a full-screen filter for designers.
Colorblind palette comparison by David Nichols - an interactive tool to preview and compare categorical color palettes under different types of color vision deficiency.
Datawrapper - A detailed guide to colors in data vis style guides - an extensive reference on building organizational color palettes for data visualization.
Datawrapper - How to pick more beautiful colors for your data visualizations - practical guidance on choosing accessible and aesthetically effective colors for charts.

AI-Assisted & Agent-based

AI-driven design generators and coding agents that can be used to prototype or implement healthcare data visualizations from natural-language prompts.

Claude Code by Anthropic - a command-line coding agent that can read, modify, and run code in your repository, suitable for building or extending visualization apps.
Gemini CLI by Google - an open-source command-line agent powered by Gemini models, for terminal-based coding and automation workflows.
Google Gemini - Google’s multimodal AI assistant for chat-based coding help, image/data understanding, and quick visualization sketches.
Google Stitch - Google Labs experiment that turns natural-language prompts into UI designs, useful for rapidly prototyping dashboard layouts.

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