Introduction

Raman and Infrared spectroscopic techniques are being used for the analysis of different types of cancers and other biological molecules. It is possible to identify cancers from normal tissues both in fresh and fixed tissues. These techniques can be used not only for the early diagnosis of cancer but also for monitoring the progression of the disease. Furthermore, chemical pathways to the progression of the disease process can be understood and followed.

Areas covered

More recently, Artificial Intelligence (AI), Neural Network (NN), and Machine Learning are being combined with spectroscopy, which is making it easier to understand the chemical structural details of cancers and biological molecules more precisely and accurately. In this report, these aspects are being outlined by using breast cancer as a specific example.

Expert opinion

A pathway showing to combine vibrational spectroscopy with AI and ML has immense potential in predicting various stages of different disease processes, in particular, in cancer diagnosis, staging, and designing treatment. This will result in improved patient care pathways.

中文翻译：

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人工智能和振动光谱在癌症诊断中的作用。

介绍

拉曼和红外光谱技术正被用于分析不同类型的癌症和其他生物分子。可以从新鲜组织和固定组织中的正常组织中识别癌症。这些技术不仅可用于癌症的早期诊断，还可用于监测疾病的进展。此外，可以理解和跟踪疾病过程进展的化学途径。

覆盖区域

最近，人工智能 (AI)、神经网络 (NN) 和机器学习正在与光谱学相结合，这使得更准确、更准确地了解癌症和生物分子的化学结构细节变得更加容易。在本报告中，这些方面以乳腺癌为例进行了概述。

专家意见

将振动光谱学与 AI 和 ML 相结合的途径在预测不同疾病过程的各个阶段方面具有巨大的潜力，特别是在癌症诊断、分期和设计治疗方面。这将导致改善患者护理途径。