Wearable Temperature Sensor and Artificial Intelligence to Reduce Hospital Workload
13th International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2022, and 12th World Congress on Information and Communication Technologies, WICT 2022
; 649 LNNS:796-805, 2023.
Article
in English
| Scopus | ID: covidwho-2294685
ABSTRACT
Patient sensing and data analytics provide information that plays an important role in the patient care process. Patterns identified from data and Machine Learning (ML) algorithms can identify risk/abnormal patients' data. Due to automatization this process can reduce workload of medical staff, as the algorithms alert for possible problems. We developed an integrated approach to monitor patients' temperature applied to COVID-19 elderly patients and an ML process to identify abnormal behavior with alerts to physicians. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Data analytics; Data transmission; Machine learning; Remote healthcare monitoring; Sensor; Wearable sensors; Data communication systems; Data-transmission; Healthcare monitoring; Integrated approach; Learning process; Machine learning algorithms; Machine-learning; Patient care process; Patient data; Medical problems
Full text:
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Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
13th International Conference on Innovations in Bio-Inspired Computing and Applications, IBICA 2022, and 12th World Congress on Information and Communication Technologies, WICT 2022
Year:
2023
Document Type:
Article
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