Cargando…
A survey on detecting healthcare concept drift in AI/ML models from a finance perspective
Data is incredibly significant in today's digital age because data represents facts and numbers from our regular life transactions. Data is no longer arriving in a static form; it is now arriving in a streaming fashion. Data streams are the arrival of limitless, continuous, and rapid data. The...
Autores principales: | M. S., Abdul Razak, C. R., Nirmala, B. R., Sreenivasa, Lahza, Husam, Lahza, Hassan Fareed M. |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10150933/ https://www.ncbi.nlm.nih.gov/pubmed/37139355 http://dx.doi.org/10.3389/frai.2022.955314 |
Ejemplares similares
-
A novel technique for detecting sudden concept drift in healthcare data using multi-linear artificial intelligence techniques
por: M. S., Abdul Razak, et al.
Publicado: (2022) -
The Relationship Between Performance and Trust in AI in E-Finance
por: Maier, Torsten, et al.
Publicado: (2022) -
The Greatest Challenge to Using AI/ML for Primary Health Care: Mindset or Datasets?
por: Troncoso, Erica L.
Publicado: (2020) -
Exploring gender biases in ML and AI academic research through systematic literature review
por: Shrestha, Sunny, et al.
Publicado: (2022) -
Editorial: AI in Healthcare: From Data to Intelligence
por: Hulsen, Tim, et al.
Publicado: (2022)