Machine learning models for 180-day mortality prediction of patients with advanced cancer using patient-reported symptom data.
Saved in:
| Title: | Machine learning models for 180-day mortality prediction of patients with advanced cancer using patient-reported symptom data. |
|---|---|
| Authors: | Xu C; MD Anderson Center for INSPiRED Cancer Care (Integrated Systems for Patient-Reported Data), The University of Texas MD Anderson Cancer Center, Houston, TX, USA.; Division of Patient-Centered Analytics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA., Subbiah IM; Department of Palliative, Rehabilitation and Integrative Medicine, University of Texas MD Anderson Cancer Center, Houston, TX, USA., Lu SC; MD Anderson Center for INSPiRED Cancer Care (Integrated Systems for Patient-Reported Data), The University of Texas MD Anderson Cancer Center, Houston, TX, USA.; Division of Patient-Centered Analytics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA., Pfob A; MD Anderson Center for INSPiRED Cancer Care (Integrated Systems for Patient-Reported Data), The University of Texas MD Anderson Cancer Center, Houston, TX, USA.; Department of Obstetrics and Gynecology, University Breast Unit, Heidelberg University Hospital, Heidelberg, Germany., Sidey-Gibbons C; MD Anderson Center for INSPiRED Cancer Care (Integrated Systems for Patient-Reported Data), The University of Texas MD Anderson Cancer Center, Houston, TX, USA. cgibbons@mdanderson.org.; Division of Patient-Centered Analytics, The University of Texas MD Anderson Cancer Center, Houston, TX, USA. cgibbons@mdanderson.org.; Symptom Research CAO, The University of Texas MD Anderson Cancer Center, 1515 Holcombe Blvd. Unit 1055, Houston, TX, 77030-4009, USA. cgibbons@mdanderson.org. |
| Source: | Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation [Qual Life Res] 2023 Mar; Vol. 32 (3), pp. 713-727. Date of Electronic Publication: 2022 Oct 29. |
| Publication Type: | Journal Article |
| Journal Info: | Publisher: Springer Netherlands Country of Publication: Netherlands NLM ID: 9210257 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1573-2649 (Electronic) Linking ISSN: 09629343 NLM ISO Abbreviation: Qual Life Res Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
|
Full text is not displayed to guests.
Login for full access.
|
|
| ISSN: | 1573-2649 |
|---|---|
| DOI: | 10.1007/s11136-022-03284-y |
