PulseExploreJournal ClubDebatesTrendingResearchersJournals
Instagram
HomeExploreJournal ClubTrending
Synapse
⌘+K
Synapse
May 15, 2026Journal of Cloud Computing Advances Systems and ApplicationsOpen Access

Parallel and extremely fast learning neural network for healthcare big data applications

View Full Paper
Ask AI
Bookmark
Share

Authors

DKDoaa Yaseen KhudhurASAbdul Samad ShibghatullahALAliza Abdul Latif

Discussion

Loading...

Member takes

Overview

Randomized trial demonstrates improved speed and accuracy in healthcare data analysis, indicating efficient real-time insights.

Key Points

  • This study aims to present a novel neural network framework to enhance processing speed and accuracy in healthcare big data applications.
  • Introduced the eXtremely Fast Learning Network (XFLN) for direct output weight calculation without backpropagation.
  • Developed a Tikhonov-regularized fast pseudoinverse algorithm for better numerical stability.
  • Implemented the Parallel and eXtremely Fast Learning Neural Network (PXFLN) for multi-core processing.
  • PXFLN achieved speedups of up to 280 times compared to traditional methods.
  • Scalability improved with processing costs reduced by as much as 90% as the number of processes increased.
  • Experiments showed enhanced accuracy in predictions on various healthcare datasets.

Cite This Study

Khudhur et al. (2026) studied this question.

synapsesocial.com/papers/6a06b998e7dec685947ac5dchttps://doi.org/10.1186/s13677-026-00909-2
View Full Paper
Ask AI
Bookmark
Share