Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Syed Javeed Pasha"'
Autor:
Syed Javeed Pasha, E. Syed Mohamed
Publikováno v:
Informatics in Medicine Unlocked, Vol 32, Iss , Pp 101064- (2022)
Currently, there is an increased need for employing machine learning (ML) and data mining in the healthcare system domain, applications of which play a pivotal role in providing beneficial knowledge to society by utilizing the available data. There a
Externí odkaz:
https://doaj.org/article/241fe26b8fca4d23b6c93e3d14b694ac
Autor:
Syed Javeed Pasha, E. Syed Mohamed
Publikováno v:
IEEE Access, Vol 8, Pp 184087-184108 (2020)
Presently, the application of machine learning (ML) and data mining (DM) techniques have a vital role in healthcare systems and wisely convert all obtainable data into beneficial knowledge. It is proven from the literature works that a chance of 12%
Externí odkaz:
https://doaj.org/article/d0adbb23162f483194fbe564a0494238
Autor:
Syed Javeed Pasha, E. Syed Mohamed
Publikováno v:
2020 International Conference on Inventive Computation Technologies (ICICT).
Machine Learning (ML) and Data Mining (DM) play a vital role in enhancing the performance of tasks such as disease risk prediction in healthcare communities, resulting in better serving of the societies. A chance of 12% error remains in the diagnosis
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::46ee00a8b728a979265b806fb5c72581
https://doi.org/10.1109/icict48043.2020.9112406
https://doi.org/10.1109/icict48043.2020.9112406
Autor:
Syed Javeed Pasha, E. Syed Mohamed
Publikováno v:
2019 5th International Conference On Computing, Communication, Control And Automation (ICCUBEA).
Use of machine learning (ML) and data mining (DM) algorithms has surfaced more often in the recent years for disease risk prediction problems in the healthcare communities. Several traditional feature selection models are combined with the DM and ML
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::17de4d544bc4cf73b3c0574dc05f69e9
https://doi.org/10.1109/iccubea47591.2019.9129304
https://doi.org/10.1109/iccubea47591.2019.9129304