人工智能工具在皮肤黑色素瘤诊断中的基本要素。

Q4 Biochemistry, Genetics and Molecular Biology
Giulia Querzoli, Giulia Veronesi, Barbara Corti, Alessia Nottegar, Emi Dika
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引用次数: 0

摘要

皮肤黑色素瘤(CM)的发病率在过去几年中急剧增加。早期诊断对预后至关重要。人工智能(AI)工具被建议用于临床医生和病理学家,作为诊断过程中的辅助支持。我们在此概述了潜在的人工智能工具在组织病理学中评估皮肤病变时应考虑的最重要参数。首先,识别黑素细胞或非黑素细胞的性质。此外,黑素细胞病变应根据至少四个参数进行分层:轮廓和不对称性;细胞的鉴定和空间分布;有丝分裂计数;出现溃疡。根据参数的数量,人工智能工具可以对CM的风险进行分层,并优先考虑病理学家的工作。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Basic Elements of Artificial Intelligence Tools in the Diagnosis of Cutaneous Melanoma.

Cutaneous melanoma (CM) incidence has dramatically increased in the last years. Early diagnosis is of paramount importance in terms of prognosis. Artificial Intelligence (AI) tools are being proposed for clinicians and pathologists as an adjunct support in the diagnostic process. We described herein an overview of the most important parameters that a potential AI tool should take into consideration in histopathology to evaluate a skin lesion. First of all, recognition of a melanocytic or non-melanocytic nature. Furthermore, melanocytic lesions should be stratified according to at least four parameters: silhouette and asymmetry; identification and spatial distribution of the cells; mitosis count; presence of ulceration. According to the number of parameters the AI tools might stratify the risk of CM and prioritize the pathologist's work.

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来源期刊
Critical Reviews in Oncogenesis
Critical Reviews in Oncogenesis Biochemistry, Genetics and Molecular Biology-Cancer Research
CiteScore
1.70
自引率
0.00%
发文量
17
期刊介绍: The journal is dedicated to extensive reviews, minireviews, and special theme issues on topics of current interest in basic and patient-oriented cancer research. The study of systems biology of cancer with its potential for molecular level diagnostics and treatment implies competence across the sciences and an increasing necessity for cancer researchers to understand both the technology and medicine. The journal allows readers to adapt a better understanding of various fields of molecular oncology. We welcome articles on basic biological mechanisms relevant to cancer such as DNA repair, cell cycle, apoptosis, angiogenesis, tumor immunology, etc.
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