Emerging role of deep learning-based artificial intelligence in tumor pathology

Cancer Communications

article

Yahui Jiang¹  Meng Yang²  Shuhao Wang³  Xiangchun Li²  Yan Sun¹ 

[1] Department of Pathology, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Tianjin Cancer Institute and Hospital, Tianjin Medical University;Department Epidemiology and Biostatistics, Key Laboratory of Cancer Prevention and Therapy, Tianjin's Clinical Research Center for Cancer, National Clinical Research Center for Cancer, Tianjin Cancer Institute and Hospital, Tianjin Medical University;Institute for Interdisciplinary Information Sciences, Tsinghua University

关键词: artificial intelligence-assisted bioinformatic analysis;    artificial intelligence;    deep learning;    pathology;    tumor;   

DOI  :  10.1002/cac2.12012

学科分类：社会科学、人文和艺术（综合）

来源: Springer

【 摘 要 】

The development of digital pathology and progression of state-of-the-art algorithms for computer vision have led to increasing interest in the use of artificial intelligence (AI), especially deep learning (DL)-based AI, in tumor pathology. The DL-based algorithms have been developed to conduct all kinds of work involved in tumor pathology, including tumor diagnosis, subtyping, grading, staging, and prognostic prediction, as well as the identification of pathological features, biomarkers and genetic changes. The applications of AI in pathology not only contribute to improve diagnostic accuracy and objectivity but also reduce the workload of pathologists and subsequently enable them to spend additional time on high-level decision-making tasks. In addition, AI is useful for pathologists to meet the requirements of precision oncology. However, there are still some challenges relating to the implementation of AI, including the issues of algorithm validation and interpretability, computing systems, the unbelieving attitude of pathologists, clinicians and patients, as well as regulators and reimbursements. Herein, we present an overview on how AI-based approaches could be integrated into the workflow of pathologists and discuss the challenges and perspectives of the implementation of AI in tumor pathology.

【 授权许可】

CC BY|CC BY-NC-ND