Using text mining techniques to extract prostate cancer predictive information (Gleason score) from semi-structured narrative laboratory reports in the Gauteng province, South Africa
Abstract Background Prostate cancer (PCa) is the leading male neoplasm in South Africa with an age-standardised incidence rate of 68.0 per 100,000 population in 2018. The Gleason score (GS) is the strongest predictive factor for PCa treatment and is embedded within semi-structured prostate biopsy na...
Saved in:
Main Authors: | Naseem Cassim, Michael Mapundu, Victor Olago, Turgay Celik, Jaya Anna George, Deborah Kim Glencross |
---|---|
Format: | article |
Language: | EN |
Published: |
BMC
2021
|
Subjects: | |
Online Access: | https://doaj.org/article/e5c0a2466a1d4101804a3a3151c4cc73 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Predicting Gleason score using the initial serum total prostate-specific antigen in Black men with symptomatic prostate adenocarcinoma in Nigeria
by: Nnabugwu II, et al.
Published: (2016) -
The Urine Biomarker PUR-4 Is Positively Associated with the Amount of Gleason 4 in Human Prostate Cancers
by: Richard Y. Ball, et al.
Published: (2021) -
Evaluation of CD10 Expression and Its Relationship with Gleason Score in Prostatic Adenocarcinoma
by: A Ghasemi, et al.
Published: (2021) -
High mortality risk of prostate cancer patients in Asia and West Africa: A systematic review
by: Jude O Okoye
Published: (2020) -
Significant Inter- and Intralaboratory Variation in Gleason Grading of Prostate Cancer: A Nationwide Study of 35,258 Patients in The Netherlands
by: Rachel N. Flach, et al.
Published: (2021)