A review and comparative study of cancer detection using machine learning: SBERT and SimCSE application
Abstract Background Using visual, biological, and electronic health records data as the sole input source, pretrained convolutional neural networks and conventional machine learning methods have been heavily employed for the identification of various malignancies. Initially, a series of preprocessin...
Main Authors: | Mpho Mokoatle, Vukosi Marivate, Darlington Mapiye, Riana Bornman, Vanessa. M. Hayes |
---|---|
Format: | Article |
Language: | English |
Published: |
BMC
2023-03-01
|
Series: | BMC Bioinformatics |
Subjects: | |
Online Access: | https://doi.org/10.1186/s12859-023-05235-x |
Similar Items
-
SimCSE for Encrypted Traffic Detection and Zero-Day Attack Detection
by: Rotem Bar, et al.
Published: (2022-01-01) -
On-the-fly knowledge distillation model for sentence embedding
by: Zhu, Xuchun
Published: (2024) -
Discriminatory Gleason grade group signatures of prostate cancer: An application of machine learning methods.
by: Mpho Mokoatle, et al.
Published: (2022-01-01) -
TA-SBERT: Token Attention Sentence-BERT for Improving Sentence Representation
by: Jaejin Seo, et al.
Published: (2022-01-01) -
A SimCSE-based model for sentiment analysis in Chinese text messages
by: Song, Haiyang
Published: (2024)