Deep learning transforms colorectal cancer biomarker prediction from histopathology images

Pekka Ruusuvuori; Mira Valkonen; Leena Latonen

doi:10.1016/j.ccell.2023.08.006

Deep learning transforms colorectal cancer biomarker prediction from histopathology images

Pekka Ruusuvuori, Mira Valkonen, Leena Latonen

Tutkimustuotos: Keskustelupuheenvuoro › Scientific

2 Sitaatiot (Scopus)

Abstrakti

Artificial intelligence (AI) is rapidly gaining interest in medicine, including pathological assessments for personalized medicine. In this issue of Cancer Cell, Wagner et al. demonstrate superior accuracy of transformer-based deep learning in predicting biomarker status in CRC. The work has implications for increased efficiency and accuracy in clinical diagnostics guiding treatment decisions in precision oncology.

Alkuperäiskieli	Englanti
Sivut	1543-1545
Sivumäärä	3
Julkaisu	Cancer Cell
Vuosikerta	41
Numero	9
DOI - pysyväislinkit	https://doi.org/10.1016/j.ccell.2023.08.006
Tila	Julkaistu - 11 syysk. 2023
OKM-julkaisutyyppi	B1 Kirjoitus tieteellisessä aikakausilehdessä

!!ASJC Scopus subject areas

Oncology
Cancer Research

YK:n kestävän kehityksen tavoitteet

Tämä tuotos edistää seuraavia kestävän kehityksen tavoitteita:

Pääsy asiakirjaan

10.1016/j.ccell.2023.08.006

Siteeraa tätä

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title = "Deep learning transforms colorectal cancer biomarker prediction from histopathology images",

abstract = "Artificial intelligence (AI) is rapidly gaining interest in medicine, including pathological assessments for personalized medicine. In this issue of Cancer Cell, Wagner et al. demonstrate superior accuracy of transformer-based deep learning in predicting biomarker status in CRC. The work has implications for increased efficiency and accuracy in clinical diagnostics guiding treatment decisions in precision oncology.",

author = "Pekka Ruusuvuori and Mira Valkonen and Leena Latonen",

note = "Funding Information: This work was financially supported by Research Council of Finland (# 341967 # 334782 P.R. and # 334774 L.L.), ERAPerMed ABCAP (P.R., L.L.), and Cancer Foundation Finland (P.R., L.L.). Publisher Copyright: {\textcopyright} 2023 Elsevier Inc.",

year = "2023",

month = sep,

day = "11",

doi = "10.1016/j.ccell.2023.08.006",

language = "English",

volume = "41",

pages = "1543--1545",

journal = "Cancer Cell",

issn = "1535-6108",

publisher = "Elsevier",

number = "9",

}

TY - JOUR

T1 - Deep learning transforms colorectal cancer biomarker prediction from histopathology images

AU - Ruusuvuori, Pekka

AU - Valkonen, Mira

AU - Latonen, Leena

N1 - Funding Information: This work was financially supported by Research Council of Finland (# 341967 # 334782 P.R. and # 334774 L.L.), ERAPerMed ABCAP (P.R., L.L.), and Cancer Foundation Finland (P.R., L.L.). Publisher Copyright: © 2023 Elsevier Inc.

PY - 2023/9/11

Y1 - 2023/9/11

N2 - Artificial intelligence (AI) is rapidly gaining interest in medicine, including pathological assessments for personalized medicine. In this issue of Cancer Cell, Wagner et al. demonstrate superior accuracy of transformer-based deep learning in predicting biomarker status in CRC. The work has implications for increased efficiency and accuracy in clinical diagnostics guiding treatment decisions in precision oncology.

AB - Artificial intelligence (AI) is rapidly gaining interest in medicine, including pathological assessments for personalized medicine. In this issue of Cancer Cell, Wagner et al. demonstrate superior accuracy of transformer-based deep learning in predicting biomarker status in CRC. The work has implications for increased efficiency and accuracy in clinical diagnostics guiding treatment decisions in precision oncology.

U2 - 10.1016/j.ccell.2023.08.006

DO - 10.1016/j.ccell.2023.08.006

M3 - Comment/debate

C2 - 37652005

AN - SCOPUS:85169512694

SN - 1535-6108

VL - 41

SP - 1543

EP - 1545

JO - Cancer Cell

JF - Cancer Cell

IS - 9

ER -

Deep learning transforms colorectal cancer biomarker prediction from histopathology images

Abstrakti

!!ASJC Scopus subject areas

YK:n kestävän kehityksen tavoitteet

Pääsy asiakirjaan

Sormenjälki

Siteeraa tätä