Predicting Multiple Diseases Using Machine Learning: A Symptom-Based Model for Medical Diagnosis
The new innovations of ML and DL has improved and delivering better results in many areas, with healthcare being one of them. The paper discussed in this work focuses on the use of the machine learning methods to predict multiple diseases given 132 symptoms. In this study, 42 diseases were considered as a target granule, and there are numerous training and testing samples. The proposed approach should be useful to physicians by giving a reliable method of disease prediction that can meet the objective of improving physicians' decision making and patients' care.
Authors
- Khakimjon Zaynidinov
- Sonal Pathak (ORCID: https://orcid.org/0000-0003-4435-1614)
- Bakhtiyor Makhkamov
- Ibrohimbek Yusupov (ORCID: https://orcid.org/0000-0002-2166-6683)
- Temurbek Kuchkorov (ORCID: https://orcid.org/0000-0003-4041-1843)
- Danish Ather (ORCID: https://orcid.org/0000-0003-1596-5553)
Institutions
- Tashkent University of Information Technology (UZ)
Publication Details
- Published
- 2024-11-07
- DOI
- https://doi.org/10.1109/icisct64202.2024.10956787
- Citations
- 4
- Primary Topic
- Artificial Intelligence in Healthcare
- Type
- article
- Field-Weighted Citation Impact
- 2.83