Human and machine: Better at pathology together?

Alexander J. Lazar; Elizabeth G. Demicco

doi:10.1016/j.ccell.2022.06.004

Human and machine: Better at pathology together?

Alexander J. Lazar, Elizabeth G. Demicco

Pathology, Anatomical

Research output: Contribution to journal › Comment/debate › peer-review

3 Scopus citations

Abstract

Meaningful integration of artificial intelligence (AI) will transform the application of “big data” for patient care, diagnosis, and research. In this issue of Cancer Cell, Chen et al. describe a transparent system to integrate histopathology and molecular data to predict outcomes and identify novel biomarkers in cancer.

Original language	English (US)
Pages (from-to)	806-808
Number of pages	3
Journal	Cancer cell
Volume	40
Issue number	8
DOIs	https://doi.org/10.1016/j.ccell.2022.06.004
State	Published - Aug 8 2022

ASJC Scopus subject areas

Oncology
Cancer Research

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10.1016/j.ccell.2022.06.004

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title = "Human and machine: Better at pathology together?",

abstract = "Meaningful integration of artificial intelligence (AI) will transform the application of “big data” for patient care, diagnosis, and research. In this issue of Cancer Cell, Chen et al. describe a transparent system to integrate histopathology and molecular data to predict outcomes and identify novel biomarkers in cancer.",

author = "Lazar, {Alexander J.} and Demicco, {Elizabeth G.}",

note = "Publisher Copyright: {\textcopyright} 2022 Elsevier Inc.",

year = "2022",

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T1 - Human and machine

T2 - Better at pathology together?

AU - Lazar, Alexander J.

AU - Demicco, Elizabeth G.

PY - 2022/8/8

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N2 - Meaningful integration of artificial intelligence (AI) will transform the application of “big data” for patient care, diagnosis, and research. In this issue of Cancer Cell, Chen et al. describe a transparent system to integrate histopathology and molecular data to predict outcomes and identify novel biomarkers in cancer.

AB - Meaningful integration of artificial intelligence (AI) will transform the application of “big data” for patient care, diagnosis, and research. In this issue of Cancer Cell, Chen et al. describe a transparent system to integrate histopathology and molecular data to predict outcomes and identify novel biomarkers in cancer.

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DO - 10.1016/j.ccell.2022.06.004

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AN - SCOPUS:85135730753

SN - 1535-6108

VL - 40

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JO - Cancer cell

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Human and machine: Better at pathology together?

Abstract

ASJC Scopus subject areas

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