Automated extraction of treatment patterns from social media posts: an exploratory analysis in renal cell carcinoma
| Autor: | Sreeram V Ramagopalan, Laura McDonald, B. Malcolm, Andrew Cox, E. Merinopoulou |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Cancer Research
020205 medical informatics Applied psychology Antineoplastic Agents 02 engineering and technology Web Browser Machine Learning 03 medical and health sciences 0302 clinical medicine Renal cell carcinoma Antineoplastic Combined Chemotherapy Protocols 0202 electrical engineering electronic engineering information engineering medicine Data Mining Humans Social media Carcinoma Renal Cell business.industry General Medicine Exploratory analysis medicine.disease Kidney Neoplasms Variation (linguistics) Oncology 030220 oncology & carcinogenesis Data Interpretation Statistical Observational study business Social Media Algorithms |
| Zdroj: | Future oncology (London, England). 15(31) |
| ISSN: | 1744-8301 |
| Popis: | Aim: The use of health-related social media forums by patients is increasing and the size of these forums creates a rich record of patient opinions and experiences, including treatment histories. This study aimed to understand the possibility of extracting treatment patterns in an automated manner for patients with renal cell carcinoma, using natural language processing, rule-based decisions, and machine learning. Patients & methods: Obtained results were compared with those from published observational studies. Results: 42 comparisons across seven therapies, three lines of treatment, and two-time periods were made; 37 of the social media estimates fell within the variation seen across the published studies. Conclusion: This exploratory work shows that estimating treatment patterns from social media is possible and generates results within the variation seen in published studies, although further development and validation of the approach is needed. |
| Databáze: | OpenAIRE |
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