Modelling of Electronic Health Records for Time-Variant Event Learning Beyond Bio-Markers – a Case Study in Prostate Cancer
Electronic health records (EHR) of large populations constitute a vast untapped resource for data-driven diagnosis and disease progression. We develop a model capable of predicting future steps in a patient’s journey for prostate cancer (PC) and its metastases without relying on direct bi...
Main Authors: | Braun, J. (Author), Cantuaria, M.L (Author), Herp, J. (Author), Krogh, M. (Author), Nadimi, E.S (Author), Pedersen, T.B (Author), Poulsen, M.H.A (Author), Sheikh, S.P (Author), Tashk, A. (Author) |
---|---|
Format: | Article |
Language: | English |
Published: |
Institute of Electrical and Electronics Engineers Inc.
2023
|
Subjects: | |
Online Access: | View Fulltext in Publisher View in Scopus |
Similar Items
-
Risk prediction models for biochemical recurrence after radical prostatectomy using prostate-specific antigen and Gleason score
by: Xin-Hai Hu, et al.
Published: (2014-12-01) -
Pre-test 68Ga-PSMA-ligand PET/CT positivity in early biochemical recurrent prostate cancer after radical prostatectomy—validation of a prediction model
by: Pia Kraft, et al.
Published: (2020-02-01) -
Deep Neural Networks Outperform the CAPRA Score in Predicting Biochemical Recurrence After Prostatectomy
by: Paul Sargos, et al.
Published: (2021-02-01) -
A Novel Risk Factor Model Based on Glycolysis-Associated Genes for Predicting the Prognosis of Patients With Prostate Cancer
by: Kaixuan Guo, et al.
Published: (2021-09-01) -
Forecasting Copper Electrorefining Cathode Rejection by Means of Recurrent Neural Networks With Attention Mechanism
by: Pedro Pablo Correa, et al.
Published: (2021-01-01)