| Abstract: The Qualcomm Tricorder XPRIZE competition began in January 2012, with the goal of developing a mobile
device to monitor health parameters and quickly diagnose several common medical conditions. In August 2014, a list of ten
finalists was announced, including a Slovenian team MESI Simplifying diagnostics that brings together companies MESI,
D·Labs, and Gigodesign, and partners from academia, Jozef Stefan Institute and Faculties of Electrotechnics and Medicine
of the University of Ljubljana. In this review, we present the XPRIZE competition, we briefly look at the ten finalists and more
closely at the MESI Simplifying diagnostics approach. Special attention is given to the diagnostic algorithm that was
developed in order to facilitate the diagnostic process. |
| References: [1] http://www.xprize.org/
[2] http://space.xprize.org/ansari-x-prize
[3] http://www.qualcommtricorderxprize.org/
[4] http://www.aezonhealth.com/
[5] http://www.clouddx.com/
[6] http://www.vitalsplus.com/
[7] http://www.dnamedinstitute.com/
[8] http://dbg.ncu.edu.tw/
[9] http://www.basilleaftech.com/
[10] https://www.scanadu.com/
[11] http://www.scanurse.com
[12] http://www.intelesens.com
[13] http://www.simplifyingdiagnostics.com/
[14] Somrak, M., Luštrek, M., Sušteri, J., Krivc, T., Mlinar, A., Travnik, T., Stepan, L., Mavsar, M., Gams, M. (2014). Tricorder: Consumer Medical Device for Discovering Common Medical Conditions, Informatica 38, 81–88.
[15] Somrak, M., Gradišek, A., Luštrek, M., Mlinar, A., Sok, M., Gams, M. Medical diagnostics based on combination of sensor and user-provided data. AIAM/ NetMed 2014, Artificial Intelligence and Assistive Medicine: In: Proceedings of the 3rd International Workshop on Artificial Intelligence and Assistive Medicine co-located with the 21st European Conference on Artificial Intelligence (ECAI 2014), Prague, Czech Republic, 36-40. |
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