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

Another study used unipartite networks (where nodes represented comorbidities, and edges between pairs of comorbidities represented the frequency of co-occurrence in patients) to identify clusters of frequently co-occurring comorbidities [21].Although these

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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Extraction of Information Related to Drug Safety Surveillance From Electronic Health Record Notes: Joint Modeling of Entities and Relations Using Knowledge-Aware Neural Attentive Models

the third issue, which was introduced with the n2c2 data set, Wei et al [38] proposed a novel label-encoding scheme to jointly extract ADE, reason, drug attributes, and their relations.Attention-Based Relation ExtractionThe attention mechanism allows neural networks

Bharath Dandala, Venkata Joopudi, Ching-Huei Tsou, Jennifer J Liang, Parthasarathy Suryanarayanan

JMIR Med Inform 2020;8(7):e18417

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Satisfaction Levels and Factors Influencing Satisfaction With Use of a Social App for Neonatal and Pediatric Patient Transfer Information Systems: A Questionnaire Study Among Doctors

Social media are Web-based services that allow users to form interpersonal networks and to use the networks to connect and communicate with new people [7,8].

Iee Choi, Jin Kyu Kim, Sun Jun Kim, Soo Chul Cho, Il Nyeo Kim

JMIR Med Inform 2016;4(3):e26

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Understanding and Addressing Variation in Health Care–Associated Infections After Durable Ventricular Assist Device Therapy: Protocol for a Mixed Methods Study

We will characterize the social networks of providers (eg, nurse practitioners, physician assistants, and physicians) as a measure of provider teamwork.

P Paul Chandanabhumma, Michael D Fetters, Francis D Pagani, Preeti N Malani, John M Hollingsworth, Russell J Funk, Keith D Aaronson, Min Zhang, Robert L Kormos, Carol E Chenoweth, Supriya Shore, Tessa M F Watt, Lourdes Cabrera, Donald S Likosky

JMIR Res Protoc 2020;9(1):e14701

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The Anatomy of the SARS-CoV-2 Biomedical Literature: Introducing the CovidX Network Algorithm for Drug Repurposing Recommendation

Cheng et al [11] introduced a bipartite network-based approach for a drug-target inference method that was proven useful for detecting drug-target interactions in the molecular polypharmacological domain.

Lyndsey Elaine Gates, Ahmed Abdeen Hamed

J Med Internet Res 2020;22(8):e21169

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Association of Social Network Use With Increased Anxiety Related to the COVID-19 Pandemic in Anesthesiology, Intensive Care, and Emergency Medicine Teams: Cross-Sectional Web-Based Survey Study

The Use of Social Networks section analyzed personal and professional use of WhatsApp, the social networks consulted at least once a week, and the average daily time spent on social networks.

Thomas Clavier, Benjamin Popoff, Jean Selim, Marion Beuzelin, Melanie Roussel, Vincent Compere, Benoit Veber, Emmanuel Besnier

JMIR Mhealth Uhealth 2020;8(9):e23153

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Bridging Awareness and Acceptance of Pre-Exposure Prophylaxis Among Men Who Have Sex With Men and the Need for Targeting Chemsex and HIV Testing: Cross-Sectional Survey

If no specific factors were associated with both awareness and acceptance, pairwise correlation between factors significantly associated with either awareness or acceptance were tested and only significant ones were retained, thus creating a bipartite graph

Tsz Ho Kwan, Shui Shan Lee

JMIR Public Health Surveill 2019;5(3):e13083

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Using Partially-Observed Facebook Networks to Develop a Peer-Based HIV Prevention Intervention: Case Study

When networks are incompletely observed, however, an alternate approach is to apply each algorithm to a sample of imputed networks, rather than optimizing just on the observed dataset [56].

Aditya Subhash Khanna, Steven Michael Goodreau, Stuart Michaels, John Alexis Schneider

J Med Internet Res 2018;20(9):e11652

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Artificial Intelligence in Health Care: Bibliometric Analysis

The top 5 AI technologies are machine learning, artificial neural networks, deep learning neural networks, electronic health records, and support vector machines.

Yuqi Guo, Zhichao Hao, Shichong Zhao, Jiaqi Gong, Fan Yang

J Med Internet Res 2020;22(7):e18228

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“Down the Rabbit Hole” of Vaccine Misinformation on YouTube: Network Exposure Study

For the two networks based on provaccine and antivaccine key phrases (“search networks”), we collected the first 6 videos’ URLs and fetched three depth levels of related videos.

Lu Tang, Kayo Fujimoto, Muhammad (Tuan) Amith, Rachel Cunningham, Rebecca A Costantini, Felicia York, Grace Xiong, Julie A Boom, Cui Tao

J Med Internet Res 2021;23(1):e23262

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