Smart skin-proto: a mobile skin disorders recognizer model Show others and affiliations
2024 (English) In: Intelligent systems: proceedings of 3rd international conference on machine learning, IoT and big data (ICMIB 2023) / [ed] Siba K. Udgata; Srinivas Sethi; Xiao-Zhi Gao, Singapore: Springer, 2024, p. 113-121Conference paper, Published paper (Refereed)
Abstract [en]
With the advancement and rapid development of the internet, the most convenient strategies for patients are mainly provided with digital healthcare systems that mainly includes the use of mobile health technology which is quite efficient. Moreover, this field is slightly shifting and also indicating interest towards the smart and intelligent models as there are quite a lot of benefits associated with it like cost decrement, easy to understand and also including the personal satisfaction of patients. The latest application of m-health medical treatment is now still on the process of the investigation because still users are facing challenges in the clinical environment. This m-health approach can be applied to accurately determine skin cancer symptoms in patients. In this paper, an impact of m-healthcare on disease diagnosis is demonstrated. A new m-health module for skin cancer diagnosis called ‘Smart Skin-Proto’ is developed. Then its usage in skin cancer assessment is also highlighted and upon implementation, the model records optimal performance which records an accuracy of 96.2% with 15 decision trees count. Also the overall latency of this application is less than other existing mobile apps.
Place, publisher, year, edition, pages Singapore: Springer, 2024. p. 113-121
Series
Lecture Notes in Networks and Systems, ISSN 2367-3370, E-ISSN 2367-3389 ; 728
Keywords [en]
Decision tree, Internet of Things (IoT), m-health, Machine Learning (ML), Personalized health, Skin cancer
National Category
Computer Sciences Cancer and Oncology
Identifiers URN: urn:nbn:se:umu:diva-216790 DOI: 10.1007/978-981-99-3932-9_11 Scopus ID: 2-s2.0-85175944276 ISBN: 9789819939312 (print) ISBN: 9789819939329 (electronic) OAI: oai:DiVA.org:umu-216790 DiVA, id: diva2:1814365
Conference 3rd International Conference on Machine Learning, Internet of Things and Big Data, ICMIB 2023, Sarang, March 10-12, 2023
2023-11-242023-11-242023-11-24 Bibliographically approved