{"title":"Enhancing Nanomaterial-Based Optical Spectroscopic Detection of Cancer through Machine Learning","authors":"Célia Sahli, Kenry","doi":"10.1021/acsmaterialslett.4c01267","DOIUrl":null,"url":null,"abstract":"Optical spectroscopic techniques relying on light–matter interactions, such as Raman scattering, fluorescence, and infrared absorbance spectroscopy, offer numerous advantages to complement existing cancer detection methods. By combining these spectroscopic techniques with rationally engineered nanomaterials, cancer cells and tissues can be more specifically targeted, and the readout signals can be substantially enhanced. Further integration of machine learning with its potential to identify subtle malignancy indicators may significantly improve the capability of nanomaterial-enabled optical spectroscopy to delineate cancer more precisely. As such, the synergistic integration of optical spectroscopy, nanomaterials, and machine learning may provide unique opportunities for the development of more selective, sensitive, and accurate cancer diagnostic technologies, which can be leveraged to optimize therapeutic strategies and minimize unnecessary interventions to ultimately enhance patient survival outcomes. This Perspective describes numerous strategies incorporating optical spectroscopy, nanomaterials, and machine learning to improve cancer detection and summarizes our outlook on the current landscape and potential future directions of this emerging field.","PeriodicalId":19,"journal":{"name":"ACS Materials Letters","volume":null,"pages":null},"PeriodicalIF":9.6000,"publicationDate":"2024-09-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Materials Letters","FirstCategoryId":"92","ListUrlMain":"https://doi.org/10.1021/acsmaterialslett.4c01267","RegionNum":1,"RegionCategory":"化学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MATERIALS SCIENCE, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
Optical spectroscopic techniques relying on light–matter interactions, such as Raman scattering, fluorescence, and infrared absorbance spectroscopy, offer numerous advantages to complement existing cancer detection methods. By combining these spectroscopic techniques with rationally engineered nanomaterials, cancer cells and tissues can be more specifically targeted, and the readout signals can be substantially enhanced. Further integration of machine learning with its potential to identify subtle malignancy indicators may significantly improve the capability of nanomaterial-enabled optical spectroscopy to delineate cancer more precisely. As such, the synergistic integration of optical spectroscopy, nanomaterials, and machine learning may provide unique opportunities for the development of more selective, sensitive, and accurate cancer diagnostic technologies, which can be leveraged to optimize therapeutic strategies and minimize unnecessary interventions to ultimately enhance patient survival outcomes. This Perspective describes numerous strategies incorporating optical spectroscopy, nanomaterials, and machine learning to improve cancer detection and summarizes our outlook on the current landscape and potential future directions of this emerging field.
期刊介绍:
ACS Materials Letters is a journal that publishes high-quality and urgent papers at the forefront of fundamental and applied research in the field of materials science. It aims to bridge the gap between materials and other disciplines such as chemistry, engineering, and biology. The journal encourages multidisciplinary and innovative research that addresses global challenges. Papers submitted to ACS Materials Letters should clearly demonstrate the need for rapid disclosure of key results. The journal is interested in various areas including the design, synthesis, characterization, and evaluation of emerging materials, understanding the relationships between structure, property, and performance, as well as developing materials for applications in energy, environment, biomedical, electronics, and catalysis. The journal has a 2-year impact factor of 11.4 and is dedicated to publishing transformative materials research with fast processing times. The editors and staff of ACS Materials Letters actively participate in major scientific conferences and engage closely with readers and authors. The journal also maintains an active presence on social media to provide authors with greater visibility.