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Interpretable machine learning model for prediction of overall survival in laryngeal cancer

Year of publication

2024

Authors

Alabi, Rasheed Omobolaji; Almangush, Alhadi; Elmusrati, Mohammed; Leivo, Ilmo; Mäkitie, Antti A.

Organizations and authors

University of Turku

Leivo Ilmo

University of Vaasa

Elmusrati Mohammed Salem Orcid -palvelun logo

Alabi Rasheed Omobolaji

University of Helsinki

Almangush Alhadi

Mäkitie Antti A.

Alabi Rasheed Omobolaji

Helsinki University Hospital

Almangush Alhadi

Mäkitie Antti A.

Alabi Rasheed Omobolaji

Publication type

Publication format

Article

Parent publication type

Journal

Article type

Original article

Audience

Scientific

Peer-reviewed

Peer-Reviewed

MINEDU's publication type classification code

A1 Journal article (refereed), original research

Publication channel information

Journal/Series

Acta oto-laryngologica

Parent publication name

Acta Oto-Laryngologica

Publisher

Taylor & Francis

Issue

3

Pages

256-262

ISSN

0001-6489

​Publication forum

50329

​Publication forum level

1

Open access

Open access in the publisher’s service

No

Open access of publication channel

Partially open publication channel

Self-archived

Yes

Other information

Fields of science

Computer and information sciences; Medical biotechnology; Biomedicine; Cancers; Otorhinolaryngology, ophthalmology

Keywords

[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

Publication country

United Kingdom

Internationality of the publisher

International

Language

English

International co-publication

Yes

Co-publication with a company

No

DOI

10.1080/00016489.2023.2301648

The publication is included in the Ministry of Education and Culture’s Publication data collection

Yes