Monitoring Symptoms of COVID-19: Review of Mobile Apps

Autor: Suzanna Schmeelk, Alison Davis, Qiaozheng Li, Caroline Shippey, Michelle Utah, Annie Myers, Meghan Reading Turchioe, Ruth Masterson Creber

Publikováno v: JMIR mHealth and uHealth, Vol 10, Iss 6, p e36065 (2022)

BackgroundMobile health (mHealth) apps have facilitated symptom monitoring of COVID-19 symptoms globally and have been used to share data with health care professionals and support disease prediction, prevention, management, diagnostics, and improvem

Externí odkaz: https://doaj.org/article/a711a4d005334692b6364512882c761d

Python Cryptographic Secure Scripting Concerns: A Study of Three Vulnerabilities

Autor: Grace LaMalva, Suzanna Schmeelk, Dristi Dinesh

Publikováno v: Lecture Notes in Networks and Systems ISBN: 9783031280726

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::cf6869035f06191abb8748b884104863
https://doi.org/10.1007/978-3-031-28073-3_42

Ambient Intelligence Security Checks: Identifying Integrity Vulnerabilities in Industry Scripts

Autor: Suzanna Schmeelk, Shannon Roth, Julia Rooney, Mughees Tariq, Khalil Wood, John Kamen, Denise Dragos

Publikováno v: Lecture Notes in Networks and Systems ISBN: 9783031160745

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::09b46b2f4e56f284ca9575bad1332f62
https://doi.org/10.1007/978-3-031-16075-2_43

Mobile Software Assurance Informed through Knowledge Graph Construction: The OWASP Threat of Insecure Data Storage

Autor: Suzanna Schmeelk, Lixin Tao

Publikováno v: Journal of Computer Science Research. 2:17-29

Many organizations, to save costs, are moving to the Bring Your Own Mobile Device (BYOD) model and adopting applications built by third-parties at an unprecedented rate. Our research examines software assurance methodologies specifically focusing on

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_________::78c54304510beddf913f7891ee09e3db
https://doi.org/10.30564/jcsr.v2i2.1765

Classifying Cyber-Risky Clinical Notes by Employing Natural Language Processing

Autor: Suzanna Schmeelk, Martins Samuel Dogo, Braja Patra, Yifan Peng

Publikováno v: Proc Annu Hawaii Int Conf Syst Sci
Schmeelk, S, Dogo, M S, Peng, Y & Patra, B G 2022, Classifying cyber-risky clinical notes by employing natural language processing . in Proceedings of the 55th Hawaii International Conference on System Sciences, HICSS 2022 . Hawaii International Conference on System Sciences: Proceedings, pp. 4140-4146 . < http://hdl.handle.net/10125/79841 >

Clinical notes, which can be embedded into electronic medical records, document patient care delivery and summarize interactions between healthcare providers and patients. These clinical notes directly inform patient care and can also indirectly info

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4b4be8bd19f071a5824e049c887f04fb
https://europepmc.org/articles/PMC9076271/