Development of a digital treatment analyzer for the management of prostate cancer patients, with the help of real world data and use of predictive modelling
Prostate cancer is the second most diagnosed cancer in the world. Treatment guidelines involve a multitude of therapies, however adherence to them is not fully established, while lack of personalized treatment strategies fails to put the patient as an individual clinical profile at the center of the...
Saved in:
| Main Authors: | Lev Korolkov, Heather A Robinson, Konstantinos Mouratis |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
SAGE Publishing
2025-04-01
|
| Series: | Digital Health |
| Online Access: | https://doi.org/10.1177/20552076251326021 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
The Use of Machine Learning for Analyzing Real-World Data in Disease Prediction and Management: Systematic Review
by: Norah Hamad Alhumaidi, et al.
Published: (2025-06-01) -
Real-World Application of Digital Morphology Analyzers: Practical Issues and Challenges in Clinical Laboratories
by: Hanah Kim, et al.
Published: (2025-03-01) -
ESMO Real-World Data and Digital Oncology: a journal to understand how health systems can help provide better cancer care
by: Rodrigo Dienstmann, MD, MBA
Published: (2023-11-01) -
Using real world data to bridge the evidence gap left by prostate cancer screening trials
by: N. Norori, et al.
Published: (2024-12-01) -
Prostate cancer management—helping your patient choose what is best for him
by: Christiaan F. Heyns, et al.
Published: (2008-10-01)