@inproceedings{WeberSeepoldMart{\´i}nez Madrid2022,
  author    = {Weber, Lucas and Seepold, Ralf and Mart{\´i}nez Madrid, Natividad},
  title     = {Democratizing digital health algorithms: RESTful machine learning web services},
  booktitle = {Social innovation in long-term care through digitalization : proceedings of the German-Italian Workshop LTC-2021, Ancona, Italy, 2-4 November 2021 (Lecture notes in bioengineering)},
  editor    = {Conti, Massimo and Orcioni, Simone},
  isbn      = {978-3-031-16854-3},
  doi       = {10.1007/978-3-031-16855-0_2},
  institution = {Informatik},
  pages     = {7 -- 15},
  year      = {2022},
  abstract  = {There have been substantial research efforts for algorithms to improve continuous and automated assessment of various health-related questions in recent years. This paper addresses the deployment gap between those improving algorithms and their usability in care and mobile health applications. In practice, most algorithms require significant and founded technical knowledge to be deployed at home or support healthcare professionals. Therefore, the digital participation of persons in need of health care professionals lacks a usable interface to use the current technological advances. In this paper, we propose applying algorithms taken from research as web-based microservices following the common approach of a RESTful service to bridge the gap and make algorithms accessible to caregivers and patients without technical knowledge and extended hardware capabilities. We address implementation details, interpretation and realization of guidelines, and privacy concerns using our self-implemented example. Also, we address further usability guidelines and our approach to those.},
  language  = {en}
}