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Visual Analytic Tools and Techniques in Population Health and Health Services Research: Scoping Review

We further reviewed the conference proceedings from Visual Analytics in Health Care, which is held one year apart in collaboration with the American Medical Information Association and IEEE VIS conferences.

Jawad Ahmed Chishtie, Jean-Sebastien Marchand, Luke A Turcotte, Iwona Anna Bielska, Jessica Babineau, Monica Cepoiu-Martin, Michael Irvine, Sarah Munce, Sally Abudiab, Marko Bjelica, Saima Hossain, Muhammad Imran, Tara Jeji, Susan Jaglal

J Med Internet Res 2020;22(12):e17892

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IBM Watson Analytics: Automating Visualization, Descriptive, and Predictive Statistics

Clinicians and other health care workers would benefit from tools that could produce descriptive, predictive, and visual analytics more rapidly and easily than tools currently available in most analytical software packages and with little training required

Robert E Hoyt, Dallas H Snider, Carla J Thompson, Sarita Mantravadi

JMIR Public Health Surveill 2016;2(2):e157

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Understanding the Dimensions of Medical Crowdfunding: A Visual Analytics Approach

It used a visual analytics approach and data crawled from the popular GoFundMe platform.

Jie Ren, Viju Raghupathi, Wullianallur Raghupathi

J Med Internet Res 2020;22(7):e18813

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Visual Analytic Tools and Techniques in Population Health and Health Services Research: Protocol for a Scoping Review

IntroductionIn the first formal use of the term visual analytics (VA) in 2005, Thomas and Cook defined it as the “science of analytical reasoning facilitated by interactive visual interfaces” in their seminal book, Illuminating the Path [1,2].

Jawad Ahmed Chishtie, Jessica Babineau, Iwona Anna Bielska, Monica Cepoiu-Martin, Michael Irvine, Andriy Koval, Jean-Sebastien Marchand, Luke Turcotte, Tara Jeji, Susan Jaglal

JMIR Res Protoc 2019;8(10):e14019

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Understanding User Experience: Exploring Participants’ Messages With a Web-Based Behavioral Health Intervention for Adolescents With Chronic Pain

We take a visual analytics approach, which facilitates interpretation of complex data by combining concepts from data mining, machine learning, human-computer interaction, and human cognition [32].

Annie T Chen, Aarti Swaminathan, William R Kearns, Nicole M Alberts, Emily F Law, Tonya M Palermo

J Med Internet Res 2019;21(4):e11756

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Natural Language Search Interfaces: Health Data Needs Single-Field Variable Search

, and visual presentation.BackgroundThere are numerous websites that provide access to the results of large-scale surveys (eg, the Office for National Statistics [12] in the UK, Eurostat [13] in the European Union, and the Bureau of Labor Statistics [14] and

Caroline Jay, Simon Harper, Ian Dunlop, Sam Smith, Shoaib Sufi, Carole Goble, Iain Buchan

J Med Internet Res 2016;18(1):e13

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Analytics for Investigation of Disease Outbreaks: Web-Based Analytics Facilitating Situational Awareness in Unfolding Disease Outbreaks

Hence, Web-based analytics that facilitate outbreak investigation have the potential to improve outbreak control around the world.

Nileena Velappan, Ashlynn Rae Daughton, Geoffrey Fairchild, William Earl Rosenberger, Nicholas Generous, Maneesha Elizabeth Chitanvis, Forest Michael Altherr, Lauren A Castro, Reid Priedhorsky, Esteban Luis Abeyta, Leslie A Naranjo, Attelia Dawn Hollander, Grace Vuyisich, Antonietta Maria Lillo, Emily Kathryn Cloyd, Ashvini Rajendra Vaidya, Alina Deshpande

JMIR Public Health Surveill 2019;5(1):e12032

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Improving Detection of Disease Re-emergence Using a Web-Based Tool (RED Alert): Design and Case Analysis Study

9] with visual analytics to help detect/warn and understand potential re-emergence at both local and global levels for 4 diseases: measles, cholera, dengue, and yellow fever.

Nidhi Parikh, Ashlynn R Daughton, William Earl Rosenberger, Derek Jacob Aberle, Maneesha Elizabeth Chitanvis, Forest Michael Altherr, Nileena Velappan, Geoffrey Fairchild, Alina Deshpande

JMIR Public Health Surveill 2021;7(1):e24132

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Marrying Medical Domain Knowledge With Deep Learning on Electronic Health Records: A Deep Visual Analytics Approach

In this study, we present DG-Viz, which brings together the power of deep learning (ie, an interpretable RNN model) and visual analytics to predict clinical risks and visually interpret the EHR prediction results.

Rui Li, Changchang Yin, Samuel Yang, Buyue Qian, Ping Zhang

J Med Internet Res 2020;22(9):e20645

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How High-Risk Comorbidities Co-Occur in Readmitted Patients With Hip Fracture: Big Data Visual Analytical Approach

Such studies have focused on using unsupervised machine learning methods such as clustering (eg, hierarchical and partitioning clustering), dimensional reduction methods (eg, principal component analysis), and visual analytics (eg, network visualization and

Suresh K Bhavnani, Bryant Dang, Rebekah Penton, Shyam Visweswaran, Kevin E Bassler, Tianlong Chen, Mukaila Raji, Rohit Divekar, Raed Zuhour, Amol Karmarkar, Yong-Fang Kuo, Kenneth J Ottenbacher

JMIR Med Inform 2020;8(10):e13567

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