Automated and Optimised Machine Learning Algorithms for Healthcare Informatics
Küçük Resim Yok
Tarih
2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Springer Science and Business Media Deutschland GmbH
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Healthcare is a rapidly expanding field with a substantial amount of heterogeneous data driving innumerable health-related tasks. Various healthcare service providers still rely on manual procedures, which can be time-consuming and require significant effort. To automate such manual operations, recent technological advances have emerged in the domain of Machine Learning (ML). ML falls under the subject of Artificial Intelligence (AI), and it gets combined with ‘big data’ to draw meaningful insights. The integration of ML in the healthcare sector has optimized decision-making and predictive analysis. This paper discusses the various application areas of ML in healthcare. Additionally, several ML algorithms used by other researchers in healthcare-related experiments are summarized. A brief review is provided regarding the experiments. This paper delineates the challenges associated with using ML in healthcare. Finally, the paper offers insights into future research directions. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
Açıklama
2nd International Conference on Computing, IoT and Data Analytics, ICCIDA 2023 -- 20 July 2023 through 21 July 2023 -- -- 308639
Anahtar Kelimeler
Artificial Intelligence, Automation, Healthcare, Machine Learning, Optimization, Security
Kaynak
Studies in Computational Intelligence
WoS Q Değeri
Scopus Q Değeri
N/A
Cilt
1145 SCI
