Predicting Depression Risk in Patients with Cancer Using Multimodal Data

Anne De Hond; Marieke Van Buchem; Claudio Fanconi; Mohana Roy; Douglas Blayney; Ilse Kant; Ewout Steyerberg; Tina Hernandez-Boussard

doi:10.3233/SHTI230274

Predicting Depression Risk in Patients with Cancer Using Multimodal Data

Anne De Hond^*, Marieke Van Buchem, Claudio Fanconi, Mohana Roy, Douglas Blayney, Ilse Kant, Ewout Steyerberg, Tina Hernandez-Boussard

^*Corresponding author for this work

Intensive Care Medicine

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

1 Downloads (Pure)

Abstract

When patients with cancer develop depression, it is often left untreated. We developed a prediction model for depression risk within the first month after starting cancer treatment using machine learning and Natural Language Processing (NLP) models. The LASSO logistic regression model based on structured data performed well, whereas the NLP model based on only clinician notes did poorly. After further validation, prediction models for depression risk could lead to earlier identification and treatment of vulnerable patients, ultimately improving cancer care and treatment adherence.

Original language	English
Title of host publication	Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023
Editors	Maria Hagglund, Madeleine Blusi, Stefano Bonacina, Lina Nilsson, Inge Cort Madsen, Sylvia Pelayo, Anne Moen, Arriel Benis, Lars Lindskold, Parisis Gallos
Publisher	IOS Press
Pages	817-818
Number of pages	2
Volume	302
ISBN (Electronic)	9781643683881
DOIs	https://doi.org/10.3233/SHTI230274
Publication status	Published - 18 May 2023
Event	33rd Medical Informatics Europe Conference: Caring is Sharing - Exploiting the Value in Data for Health and Innovation, MIE2023 - Gothenburg, Sweden Duration: 22 May 2023 → 25 May 2023

Publication series

Name	Studies in Health Technology and Informatics
Volume	302
ISSN (Print)	0926-9630
ISSN (Electronic)	1879-8365

Conference

Conference	33rd Medical Informatics Europe Conference: Caring is Sharing - Exploiting the Value in Data for Health and Innovation, MIE2023
Country/Territory	Sweden
City	Gothenburg
Period	22/05/23 → 25/05/23

Keywords

depression
machine learning
Natural Language Processing
oncology

Access to Document

10.3233/SHTI230274Licence: CC BY-NC

SHTI-302-SHTI230274Final published version, 115 KBLicence: CC BY-NC

Cite this

De Hond, A., Van Buchem, M., Fanconi, C., Roy, M., Blayney, D., Kant, I., Steyerberg, E., & Hernandez-Boussard, T. (2023). Predicting Depression Risk in Patients with Cancer Using Multimodal Data. In M. Hagglund, M. Blusi, S. Bonacina, L. Nilsson, I. C. Madsen, S. Pelayo, A. Moen, A. Benis, L. Lindskold, & P. Gallos (Eds.), Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023 (Vol. 302, pp. 817-818). (Studies in Health Technology and Informatics; Vol. 302). IOS Press. https://doi.org/10.3233/SHTI230274

De Hond, Anne ; Van Buchem, Marieke ; Fanconi, Claudio et al. / Predicting Depression Risk in Patients with Cancer Using Multimodal Data. Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023. editor / Maria Hagglund ; Madeleine Blusi ; Stefano Bonacina ; Lina Nilsson ; Inge Cort Madsen ; Sylvia Pelayo ; Anne Moen ; Arriel Benis ; Lars Lindskold ; Parisis Gallos. Vol. 302 IOS Press, 2023. pp. 817-818 (Studies in Health Technology and Informatics).

@inproceedings{13f0ac5e572a4400971aaf5e8b09fd35,

title = "Predicting Depression Risk in Patients with Cancer Using Multimodal Data",

abstract = "When patients with cancer develop depression, it is often left untreated. We developed a prediction model for depression risk within the first month after starting cancer treatment using machine learning and Natural Language Processing (NLP) models. The LASSO logistic regression model based on structured data performed well, whereas the NLP model based on only clinician notes did poorly. After further validation, prediction models for depression risk could lead to earlier identification and treatment of vulnerable patients, ultimately improving cancer care and treatment adherence.",

keywords = "depression, machine learning, Natural Language Processing, oncology",

author = "\{De Hond\}, Anne and \{Van Buchem\}, Marieke and Claudio Fanconi and Mohana Roy and Douglas Blayney and Ilse Kant and Ewout Steyerberg and Tina Hernandez-Boussard",

note = "Publisher Copyright: {\textcopyright} 2023 European Federation for Medical Informatics (EFMI) and IOS Press.; 33rd Medical Informatics Europe Conference: Caring is Sharing - Exploiting the Value in Data for Health and Innovation, MIE2023 ; Conference date: 22-05-2023 Through 25-05-2023",

year = "2023",

month = may,

day = "18",

doi = "10.3233/SHTI230274",

language = "English",

volume = "302",

series = "Studies in Health Technology and Informatics",

publisher = "IOS Press",

pages = "817--818",

editor = "Maria Hagglund and Madeleine Blusi and Stefano Bonacina and Lina Nilsson and Madsen, \{Inge Cort\} and Sylvia Pelayo and Anne Moen and Arriel Benis and Lars Lindskold and Parisis Gallos",

booktitle = "Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023",

address = "Netherlands",

}

De Hond, A, Van Buchem, M, Fanconi, C, Roy, M, Blayney, D, Kant, I, Steyerberg, E & Hernandez-Boussard, T 2023, Predicting Depression Risk in Patients with Cancer Using Multimodal Data. in M Hagglund, M Blusi, S Bonacina, L Nilsson, IC Madsen, S Pelayo, A Moen, A Benis, L Lindskold & P Gallos (eds), Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023. vol. 302, Studies in Health Technology and Informatics, vol. 302, IOS Press, pp. 817-818, 33rd Medical Informatics Europe Conference: Caring is Sharing - Exploiting the Value in Data for Health and Innovation, MIE2023, Gothenburg, Sweden, 22/05/23. https://doi.org/10.3233/SHTI230274

Predicting Depression Risk in Patients with Cancer Using Multimodal Data. / De Hond, Anne; Van Buchem, Marieke; Fanconi, Claudio et al.
Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023. ed. / Maria Hagglund; Madeleine Blusi; Stefano Bonacina; Lina Nilsson; Inge Cort Madsen; Sylvia Pelayo; Anne Moen; Arriel Benis; Lars Lindskold; Parisis Gallos. Vol. 302 IOS Press, 2023. p. 817-818 (Studies in Health Technology and Informatics; Vol. 302).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › Academic › peer-review

TY - GEN

T1 - Predicting Depression Risk in Patients with Cancer Using Multimodal Data

AU - De Hond, Anne

AU - Van Buchem, Marieke

AU - Fanconi, Claudio

AU - Roy, Mohana

AU - Blayney, Douglas

AU - Kant, Ilse

AU - Steyerberg, Ewout

AU - Hernandez-Boussard, Tina

PY - 2023/5/18

Y1 - 2023/5/18

N2 - When patients with cancer develop depression, it is often left untreated. We developed a prediction model for depression risk within the first month after starting cancer treatment using machine learning and Natural Language Processing (NLP) models. The LASSO logistic regression model based on structured data performed well, whereas the NLP model based on only clinician notes did poorly. After further validation, prediction models for depression risk could lead to earlier identification and treatment of vulnerable patients, ultimately improving cancer care and treatment adherence.

AB - When patients with cancer develop depression, it is often left untreated. We developed a prediction model for depression risk within the first month after starting cancer treatment using machine learning and Natural Language Processing (NLP) models. The LASSO logistic regression model based on structured data performed well, whereas the NLP model based on only clinician notes did poorly. After further validation, prediction models for depression risk could lead to earlier identification and treatment of vulnerable patients, ultimately improving cancer care and treatment adherence.

KW - depression

KW - machine learning

KW - Natural Language Processing

KW - oncology

UR - https://www.scopus.com/pages/publications/85159763190

U2 - 10.3233/SHTI230274

DO - 10.3233/SHTI230274

M3 - Conference contribution

C2 - 37203503

AN - SCOPUS:85159763190

VL - 302

T3 - Studies in Health Technology and Informatics

SP - 817

EP - 818

BT - Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023

A2 - Hagglund, Maria

A2 - Blusi, Madeleine

A2 - Bonacina, Stefano

A2 - Nilsson, Lina

A2 - Madsen, Inge Cort

A2 - Pelayo, Sylvia

A2 - Moen, Anne

A2 - Benis, Arriel

A2 - Lindskold, Lars

A2 - Gallos, Parisis

PB - IOS Press

T2 - 33rd Medical Informatics Europe Conference: Caring is Sharing - Exploiting the Value in Data for Health and Innovation, MIE2023

Y2 - 22 May 2023 through 25 May 2023

ER -

De Hond A, Van Buchem M, Fanconi C, Roy M, Blayney D, Kant I et al. Predicting Depression Risk in Patients with Cancer Using Multimodal Data. In Hagglund M, Blusi M, Bonacina S, Nilsson L, Madsen IC, Pelayo S, Moen A, Benis A, Lindskold L, Gallos P, editors, Caring is Sharing - Exploiting the Value in Data for Health and Innovation - Proceedings of MIE 2023. Vol. 302. IOS Press. 2023. p. 817-818. (Studies in Health Technology and Informatics). doi: 10.3233/SHTI230274

Predicting Depression Risk in Patients with Cancer Using Multimodal Data

Abstract

Publication series

Conference

Keywords

Access to Document

Other files and links

Fingerprint

Cite this