Artificial Intelligence & Tissue Biomarkers: Advantages, Risks and Perspectives for Pathology

被引：28

作者：

Lancellotti, Cesare ^{[1
,2
]}

Cancian, Pierandrea ^{[3
]}

Savevski, Victor ^{[3
]}

Kotha, Soumya Rupa Reddy ^{[1
,2
]}

Fraggetta, Filippo ^{[4
]}

Graziano, Paolo ^{[5
]}

Di Tommaso, Luca ^{[1
,2
]}

机构：

[1] Humanitas Univ, Dept Biomed Sci, Via Rita Levi Montalcini 4, I-20090 Milan, Italy

[2] Humanitas Res Hosp, Pathol Unit, Via Manzoni 56, I-20089 Milan, Italy

[3] Humanitas Res Hosp, IRCCS, Artificial Intelligence Ctr, Via Manzoni 56, I-20089 Milan, Italy

[4] Cannizzaro Hosp, Dept Pathol, I-95021 Catania, Italy

[5] Fdn IRCCS Casa Sollievo Sofferenza, Pathol Unit, I-71013 San Giovanni Rotondo, FG, Italy

来源：

CELLS | 2021年 / 10卷 / 04期

关键词：

biomarker; artificial intelligence; pathology; personalized medicine; TUMOR-INFILTRATING LYMPHOCYTES; CONVOLUTIONAL NEURAL-NETWORKS; COMPUTER-EXTRACTED FEATURES; IMAGE-ANALYSIS; LUNG ADENOCARCINOMA; DIGITAL PATHOLOGY; PREDICT RESPONSE; PROSTATE-CANCER; DEEP; CLASSIFICATION;

D O I：

10.3390/cells10040787

中图分类号：

Q2 [细胞生物学];

学科分类号：

071009 ; 090102 ;

摘要：

Tissue Biomarkers are information written in the tissue and used in Pathology to recognize specific subsets of patients with diagnostic, prognostic or predictive purposes, thus representing the key elements of Personalized Medicine. The advent of Artificial Intelligence (AI) promises to further reinforce the role of Pathology in the scenario of Personalized Medicine: AI-based devices are expected to standardize the evaluation of tissue biomarkers and also to discover novel information, which would otherwise be ignored by human review, and use them to make specific predictions. In this review we will present how AI has been used to support Tissue Biomarkers evaluation in the specific field of Pathology, give an insight to the intriguing field of AI-based biomarkers and discuss possible advantages, risk and perspectives for Pathology.

引用

页数：12

共 50 条

[1] Artificial intelligence for biomarkers in cancer pathology
Kather, Jakob Nikolas
JOURNAL OF PATHOLOGY, 2024, 264 : S52 - S52
[2] Physician perspectives on integration of artificial intelligence into diagnostic pathology
Sarwar, Shihab
Dent, Anglin
Faust, Kevin
Richer, Maxime
Djuric, Ugljesa
Van Ommeren, Randy
Diamandis, Phedias
NPJ DIGITAL MEDICINE, 2019, 2 (1)
[3] Physician perspectives on integration of artificial intelligence into diagnostic pathology
Shihab Sarwar
Anglin Dent
Kevin Faust
Maxime Richer
Ugljesa Djuric
Randy Van Ommeren
Phedias Diamandis
npj Digital Medicine, 2
[4] Ethical and Regulatory Perspectives on Generative Artificial Intelligence in Pathology
Jackson, Brian R.
Rashidi, Hooman H.
Lennerz, Jochen K.
de Baca, M. E.
ARCHIVES OF PATHOLOGY & LABORATORY MEDICINE, 2025, 149 (02) : 123 - 129
[5] ARTIFICIAL MACROMOLECULES, ADVANTAGES AND RISKS
GRUBER, UF
ACTA ANAESTHESIOLOGICA SCANDINAVICA, 1981, 25 : 22 - 22
[6] Artificial Intelligence in Pathology
Cohen, Stanley
Levenson, Richard
Pantanowitz, Liron
AMERICAN JOURNAL OF PATHOLOGY, 2021, 191 (10): : 1670 - 1672
[7] Artificial Intelligence in Pathology
Foersch, Sebastian
Klauschen, Frederick
Hufnagl, Peter
Roth, Wilfried
DEUTSCHES ARZTEBLATT INTERNATIONAL, 2021, 118 (12): : 199 - +
[8] Artificial Intelligence in Pathology
Chang, Hye Yoon
Jung, Chan Kwon
Woo, Junwoo Isaac
Lee, Sanghun
Cho, Joonyoung
Kim, Sun Woo
Kwak, Tae-Yeong
JOURNAL OF PATHOLOGY AND TRANSLATIONAL MEDICINE, 2019, 53 (01) : 1 - 12
[9] Use of Generative Artificial Intelligence in Educational Environments: An Initial Student Perspective of the Risks and Advantages
Romero Robles, Laura Eugenia
Ek, Jackeline Iturbe
2024 IEEE GLOBAL ENGINEERING EDUCATION CONFERENCE, EDUCON 2024, 2024,
[10] Artificial Intelligence in Ophthalmology: Advantages and Limits
Costin, Hariton-Nicolae
Fira, Monica
Goras, Liviu
APPLIED SCIENCES-BASEL, 2025, 15 (04):

← 1 2 3 4 5 →