Breast cancer prognosis through the use of multi-modal classifiers: current state of the art and the way forward

IF 2.5 3区生物学 Q3 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Briefings in Functional Genomics Pub Date : 2024-05-01 DOI:10.1093/bfgp/elae015

Archana Mathur, Nikhilanand Arya, Kitsuchart Pasupa, Sriparna Saha, Sudeepa Roy Dey, Snehanshu Saha

引用次数: 0

Abstract

We present a survey of the current state-of-the-art in breast cancer detection and prognosis. We analyze the evolution of Artificial Intelligence-based approaches from using just uni-modal information to multi-modality for detection and how such paradigm shift facilitates the efficacy of detection, consistent with clinical observations. We conclude that interpretable AI-based predictions and ability to handle class imbalance should be considered priority.

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通过使用多模态分类器进行乳腺癌预后分析：技术现状与未来方向

我们介绍了当前乳腺癌检测和预后的最新进展。我们分析了基于人工智能的方法从仅使用单模态信息到多模态检测的演变过程，以及这种模式转变如何促进检测的有效性，并与临床观察结果保持一致。我们的结论是，应优先考虑基于人工智能的可解释预测和处理类别不平衡的能力。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Briefings in Functional Genomics BIOTECHNOLOGY & APPLIED MICROBIOLOGY-GENETICS & HEREDITY

CiteScore

6.30

自引率

2.50%

发文量

审稿时长

6-12 weeks

期刊介绍： Briefings in Functional Genomics publishes high quality peer reviewed articles that focus on the use, development or exploitation of genomic approaches, and their application to all areas of biological research. As well as exploring thematic areas where these techniques and protocols are being used, articles review the impact that these approaches have had, or are likely to have, on their field. Subjects covered by the Journal include but are not restricted to: the identification and functional characterisation of coding and non-coding features in genomes, microarray technologies, gene expression profiling, next generation sequencing, pharmacogenomics, phenomics, SNP technologies, transgenic systems, mutation screens and genotyping. Articles range in scope and depth from the introductory level to specific details of protocols and analyses, encompassing bacterial, fungal, plant, animal and human data. The editorial board welcome the submission of review articles for publication. Essential criteria for the publication of papers is that they do not contain primary data, and that they are high quality, clearly written review articles which provide a balanced, highly informative and up to date perspective to researchers in the field of functional genomics.