Prediction of post-treatment recurrence in early-stage breast cancer using deep-learning with mid-infrared chemical histopathological imaging
Abstract Predicting long-term recurrence of disease in breast cancer (BC) patients remains a significant challenge for patients with early stage disease who are at low to intermediate risk of relapse as determined using current clinical tools. Prognostic assays which utilize bulk transcriptomics ign...
Saved in:
Main Authors: | Abigail Keogan, Thi Nguyet Que Nguyen, Pascaline Bouzy, Nicholas Stone, Karin Jirstrom, Arman Rahman, William M. Gallagher, Aidan D. Meade |
---|---|
Format: | Article |
Language: | English |
Published: |
Nature Portfolio
2025-01-01
|
Series: | npj Precision Oncology |
Online Access: | https://doi.org/10.1038/s41698-024-00772-x |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
BROADBAND METHOD FOR GROUP VELOCITY DISPERSION MEASUREMENTS IN THE MID-INFRARED
by: D. S. Klimentov, et al.
Published: (2015-04-01) -
Highly Efficient and achromatic mid-infrared silicon nitride meta-lenses
by: Abdullah Maher, et al.
Published: (2025-01-01) -
Polarization conversion in soft glass fluoride and chalcogenide fibers for mid-infrared applications
by: Md Moinul Islam Khan, et al.
Published: (2025-01-01) -
Progress in mid-infrared optoelectronics for high-speed free-space data throughput
by: Frédéric Grillot, et al.
Published: (2025-01-01) -
Application of Common Components Analysis to Mid-Infrared Spectra for the Authentication of Lebanese Honey
by: Rita El Hajj, et al.
Published: (2024-01-01)