ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2019
Leveraging Latent Dirichlet Allocation in processing free-text personal goals among patients undergoing bladder cancer surgery.
Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
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- Integrating Structured and Unstructured EHR Data for Predicting Mortality by Machine Learning and Latent Dirichlet Allocation Method.International journal of environmental research and public health · 2023Article
- Extracting information and inferences from a large text corpus.International journal of information technology : an official journal of Bharati Vidyapeeth's Institute of Computer Applications and Management · 2023Article
- Integrating unsupervised and supervised learning techniques to predict traumatic brain injury: A population-based study.Intelligence-based medicine · 2023Article
- Health-related Quality of Life for Patients Undergoing Radical Cystectomy: Results of a Large Prospective Cohort.European urology · 2022Review
- Social network and HIV/AIDS: A bibliometric analysis of global literature.Frontiers in public health · 2022Article
- The Text Mining Technique Applied to the Analysis of Health Interventions to Combat Congenital Syphilis in Brazil: The Case of the "Syphilis No!" Project.Frontiers in public health · 2022Article
- Text mining of Reddit posts: Using latent Dirichlet allocation to identify common parenting issues.PloS one · 2022Article
- Categorising patient concerns using natural language processing techniques.BMJ health & care informatics · 2021Article
- Medical needs related to the endoscopic technology and colonoscopy for colorectal cancer diagnosis.BMC cancer · 2021Article
- Grounded reality meets machine learning: A deep-narrative analysis framework for energy policy research.Energy research & social science · 2020Article
- Global mapping of interventions to improve quality of life of patients with depression during 1990-2018.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2020Review
- Global mapping of interventions to improve the quality of life of patients with cardiovascular diseases during 1990-2018.Health and quality of life outcomes · 2020Review
- How have excessive electronics devices and Internet uses been concerned? Implications for global research agenda from a bibliometric analysis.Journal of behavioral addictions · 2020Article
- Global Mapping of Research Trends on Interventions to Improve Health-Related Quality of Life in Asthma Patients.International journal of environmental research and public health · 2020Article
- Ileal conduit or orthotopic neobladder: selection and contemporary patterns of use.Current opinion in urology · 2020Review
- Interventions to Improve the Quality of Life of Patients with Chronic Obstructive Pulmonary Disease: A Global Mapping During 1990-2018.International journal of environmental research and public health · 2020Review
- Modeling the Research Landscapes of Artificial Intelligence Applications in Diabetes (GAPInternational journal of environmental research and public health · 2020Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
purposeAs we begin to leverage Big Data in health care settings and particularly in assessing patient-reported outcomes, there is a need for novel analytics to address unique challenges. One such challenge is in coding transcribed interview data, typically free-text entries of statements made during a face-to-face interview. Latent Dirichlet Allocation (LDA) offers statistical rigor and consistency in automating the interpretation of patients' expressed concerns and coping strategies.
methodsLDA was applied to interview data collected as part of a prospective, longitudinal study of QOL in N = 211 patients undergoing radical cystectomy and urinary diversion for bladder cancer. LDA analyzed personal goal statements to extract the latent topics and themes, stratified by time, and on things patients wanted to accomplish and prevent. Model comparison metrics determined the number of topics to extract.
resultsLDA extracted seven latent topics. Prior to surgery, patients' priorities were primarily in cancer surgery and recovery. Six months after the surgery, they were replaced by goals on regaining a sense of normalcy, to resume work, to enjoy life more fully, and to appreciate friends and family more. LDA model parameters showed changing priorities, e.g., immediate concerns on surgery and resuming employment decreased post-surgery and were replaced by concerns over cancer recurrence and a desire to remain healthy and strong.
conclusionsNovel Big Data analytics such as LDA offer the possibility of summarizing personal goals without the need for conventional fixed-length measures and resource-intensive qualitative data coding.
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