ArticleProceedings. International Database Engineering and Applications Symposium2021
Predicting late symptoms of head and neck cancer treatment using LSTM and patient reported outcomes.
Article in Proceedings. International Database Engineering and Applications Symposium, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Exploring the role of health-related quality of life measures in predictive modelling for oncology: a systematic review.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025Pooled it
- Improving Survival Prediction of Head and Neck Cancer Patients by Modeling Long-term Symptom Burden.Proceedings. IEEE International Conference on Healthcare Informatics · 2026Article
- L-VISP: LSTM Visualization for Interpretable Symptom Prediction in Patient Cohorts.Computer graphics forum : journal of the European Association for Computer Graphics · 2026Article
- FlavorCharter: Development of a Smartphone App for Quantifying Food Flavor.Proceedings ... ICDM workshops. IEEE International Conference on Data Mining · 2025Article
- Evaluating Dimensionality Reduction for Patient-Reported Outcome-Based Survival Modeling in Patients With Head and Neck Cancer.JCO clinical cancer informatics · 2025Article
- Dual-Attention BiLSTM for Interpretable Forecasting of Treatment Toxicities.... IEEE-EMBS International Conference on Biomedical and Health Informatics. IEEE-EMBS International Conference on Biomedical and Health Informatics · 2025Article
- mEnergy: Development of a Novel mHealth Multi-device Platform for Near Real-time Remote Assessment of Energy Disorders.Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference · 2025Article
- Using artificial intelligence to predict patient outcomes from patient-reported outcome measures: a scoping review.Health and quality of life outcomes · 2025Article
- Deep Learning Approaches to Forecast Physical and Mental Deterioration During Chemotherapy in Patients with Cancer.Diagnostics (Basel, Switzerland) · 2025Article
- PRO-Based Stratification Improves Model Prediction for Toxicity and Survival of Head and Neck Cancer Patients.IEEE journal of biomedical and health informatics · 2025Article
- AI-Driven Prediction of Symptom Trajectories in Cancer Care: A Deep Learning Approach for Chemotherapy Management.Bioengineering (Basel, Switzerland) · 2024Article
- Collaborative Filtering for the Imputation of Patient Reported Outcomes.Database and expert systems applications : 35th International Conference, DEXA 2024, Naples, Italy, August 26-28, 2024, Proceedings. Part I. Database and Expert Systems Applications Conference (35th : 2024 : Naples, Italy) · 2024Article
- Machine Learning Approaches to Predict Symptoms in People With Cancer: Systematic Review.JMIR cancer · 2024Review
- Roses Have Thorns: Understanding the Downside of Oncological Care Delivery Through Visual Analytics and Sequential Rule Mining.IEEE transactions on visualization and computer graphics · 2024Article
- Predicting Chemotherapy-Related Symptom Deterioration Using Hybrid Deep Learning Architecture.AMIA ... Annual Symposium proceedings. AMIA Symposium · 2024Article
- Article
- Real-World Use of Electronic Patient-Reported Outcome (ePRO) Tools Integrated in the Electronic Medical Record During Radiation Therapy for Head and Neck Cancer: Feasibility Study.The Permanente journal · 2023Article
- Improving Prediction of Late Symptoms using LSTM and Patient-reported Outcomes for Head and Neck Cancer Patients.Proceedings. IEEE International Conference on Healthcare Informatics · 2023Article
- Predicting Childhood Obesity Using Machine Learning: Practical Considerations.BioMedInformatics · 2022Article
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Authors and funding
7 authors.
Funding
Abstract
Patient-Reported Outcome (PRO) surveys are used to monitor patients' symptoms during and after cancer treatment. Acute symptoms refer to those experienced during treatment and late symptoms refer to those experienced after treatment. While most patients experience severe symptoms during treatment, these usually subside in the late stage. However, for some patients, late toxicities persist negatively affecting the patient's quality of life (QoL). In the case of head and neck cancer patients, PRO surveys are recorded every week during the patient's visit to the clinic and at different follow-up times after the treatment has concluded. In this paper, we model the PRO data as a time-series and apply Long-Short Term Memory (LSTM) neural networks for predicting symptom severity in the late stage. The PRO data used in this project corresponds to MD Anderson Symptom Inventory (MDASI) questionnaires collected from head and neck cancer patients treated at the MD Anderson Cancer Center. We show that the LSTM model is effective in predicting symptom ratings under the RMSE and NRMSE metrics. Our experiments show that the LSTM model also outperforms other machine learning models and time-series prediction models for these data.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.