TY - GEN
T1 - Unsupervised Learning Approach to Drive Therapeutic Precision in a Complex Disease
AU - Zidoum, Hamza
AU - Al-Sawafi, Sumaya
AU - Al Ansari, Aliya
AU - Al-Lawati, Batool
N1 - Publisher Copyright:
© 2022 IEEE.
PY - 2022/4/15
Y1 - 2022/4/15
N2 - Unsupervised and semi-supervised Machine learning (ML) methods have a high potential for driving precision therapeutic in case of complex diseases. The diversity of its clinical phenotypes renders developing effective therapies for complex diseases a particularly challenging task. In this paper, we demonstrate how machine learning unsupervised methods can help researchers in analyzing health data in the case of Systemic Lupus Erythematous (SLE). We identified subgroups of SLE patients related to the disease severity. We analyzed the similarity between samples within these clusters and discovered distinct patterns. The clustering analysis results showed two separate patients clusters that correspond to mild and severe subgroups. The identification of well-defined subgroups of patients can facilitate the development of targeted therapeutics.
AB - Unsupervised and semi-supervised Machine learning (ML) methods have a high potential for driving precision therapeutic in case of complex diseases. The diversity of its clinical phenotypes renders developing effective therapies for complex diseases a particularly challenging task. In this paper, we demonstrate how machine learning unsupervised methods can help researchers in analyzing health data in the case of Systemic Lupus Erythematous (SLE). We identified subgroups of SLE patients related to the disease severity. We analyzed the similarity between samples within these clusters and discovered distinct patterns. The clustering analysis results showed two separate patients clusters that correspond to mild and severe subgroups. The identification of well-defined subgroups of patients can facilitate the development of targeted therapeutics.
KW - Cluster Analysis
KW - Complex Diseases
KW - Healthcare Data
KW - Systemic Lupus Erythematous (SLE)
KW - Unsupervised Learning
UR - http://www.scopus.com/inward/record.url?scp=85139071653&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85139071653&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/f78da037-e99c-346d-84f7-61243c2ab41f/
U2 - 10.1109/icmi55296.2022.9873657
DO - 10.1109/icmi55296.2022.9873657
M3 - Conference contribution
AN - SCOPUS:85139071653
SN - 9781665474832
T3 - 2022 2nd International Conference on Computing and Machine Intelligence (ICMI)
BT - 2022 2nd International Conference on Computing and Machine Intelligence, ICMI 2022 - Proceedings
A2 - Marquez, Fausto Pedro Garcia
A2 - Jamil, Akhtar
A2 - Hameed, Alaa Ali
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2nd International Conference on Computing and Machine Intelligence, ICMI 2022
Y2 - 15 July 2022 through 16 July 2022
ER -