Use of Patient-Reported Outcomes in Risk Prediction Model Development to Support Cancer Care Delivery: A Scoping Review
PURPOSE The integration of patient-reported outcomes (PROs) into electronic health
records (EHRs) has enabled systematic collection of symptom data to manage post …
records (EHRs) has enabled systematic collection of symptom data to manage post …
[HTML][HTML] Taking shared decision making for prostate cancer to the next level: Requirements for a Dutch treatment decision aid with personalized risks on side effects
LMJ Hochstenbach, D Determann, RRR Fijten… - Internet …, 2023 - Elsevier
Background Different curative treatment modalities need to be considered in case of
localized prostate cancer, all comparable in terms of survival and recurrence though …
localized prostate cancer, all comparable in terms of survival and recurrence though …
A comparison of machine learning models for predicting urinary incontinence in men with localized prostate cancer
Introduction Urinary incontinence (UI) is a common side effect of prostate cancer treatment,
but in clinical practice, it is difficult to predict. Machine learning (ML) models have shown …
but in clinical practice, it is difficult to predict. Machine learning (ML) models have shown …
[HTML][HTML] The value of PROMs for predicting erectile dysfunction in prostate cancer patients with Bayesian network
B Osong, H Hasannejadasl, H van der Poel… - Technical Innovations & …, 2024 - Elsevier
Purpose This study aims to develop and externally validate a clinically plausible Bayesian
network structure to predict one-year erectile dysfunction in prostate cancer patients by …
network structure to predict one-year erectile dysfunction in prostate cancer patients by …
Patients' Attitudes Towards the Use of AI-Based Decision Aids for Breast Cancer Treatment Decision-Making: A Qualitative Study
H Hasannejadasl, C Offermann, E Essink, A Dekker… - 2023 - researchsquare.com
Objectives: While AI has the potential to transform cancer care, there has been limited
progress in incorporating AI tools into clinical practice. As healthcare providers work towards …
progress in incorporating AI tools into clinical practice. As healthcare providers work towards …
Development of a Machine Learning-Based Model for the Prediction of Long-Term Erectile Dysfunction after COVID-19 Recovery: A Prospective Observational Study
FN Alvarez, MCC Redondo, NS Martin, AG Viña… - 2024 - preprints.org
Objectives: To develop a machine learning-based model for the identification of features
involved in the prediction of long-term erectile dysfunction (ED) after COVID-19 recovery …
involved in the prediction of long-term erectile dysfunction (ED) after COVID-19 recovery …