Bibliographic Details
| Title: |
Factors to improve distress and fatigue in Cancer survivorship; further understanding through text analysis of interviews by machine learning |
| Authors: |
Kyungmi Yang, Jina Kim, Mison Chun, Mi Sun Ahn, Eunae Chon, Jinju Park, Mijin Jung |
| Source: |
BMC Cancer, Vol 21, Iss 1, Pp 1-16 (2021) |
| Publisher Information: |
BMC, 2021. |
| Publication Year: |
2021 |
| Collection: |
LCC:Neoplasms. Tumors. Oncology. Including cancer and carcinogens |
| Subject Terms: |
Cancer survivorship, Distress, Fatigue, Machine learning, Text analysis, Neoplasms. Tumors. Oncology. Including cancer and carcinogens, RC254-282 |
| More Details: |
Abstract Background From patient-reported surveys and individual interviews by health care providers, we attempted to identify the significant factors related to the improvement of distress and fatigue for cancer survivors by text analysis with machine learning techniques, as the secondary analysis using the single institute data from the Korean Cancer Survivorship Center Pilot Project. Methods Surveys and in-depth interviews from 322 cancer survivors were analyzed to identify their needs and concerns. Among the keywords in the surveys, including EQ-VAS, distress, fatigue, pain, insomnia, anxiety, and depression, distress and fatigue were focused. The interview transcripts were analyzed via Korean-based text analysis with machine learning techniques, based on the keywords used in the survey. Words were generated as vectors and similarity scores were calculated by the distance related to the text’s keywords and frequency. The keywords and selected high-ranked ten words for each keyword based on the similarity were then taken to draw a network map. Results Most participants were otherwise healthy females younger than 50 years suffering breast cancer who completed treatment less than 6 months ago. As the 1-month follow-up survey’s results, the improved patients were 56.5 and 58.4% in distress and fatigue scores, respectively. For the improvement of distress, dyspepsia (p = 0.006) and initial scores of distress, fatigue, anxiety, and depression (p |
| Document Type: |
article |
| File Description: |
electronic resource |
| Language: |
English |
| ISSN: |
1471-2407 |
| Relation: |
https://doaj.org/toc/1471-2407 |
| DOI: |
10.1186/s12885-021-08438-8 |
| Access URL: |
https://doaj.org/article/d09c263aff8342358fa715a19f3885a8 |
| Accession Number: |
edsdoj.09c263aff8342358fa715a19f3885a8 |
| Database: |
Directory of Open Access Journals |
|
Full text is not displayed to guests. |
Login for full access.
|
