Current Trends of Raman Spectroscopy in Clinic Settings: Opportunities and Challenges

Early clinical diagnosis, effective intraoperative guidance, and an accurate prognosis can lead to timely and effective medical treatment. The current conventional clinical methods have several limitations. Therefore, there is a need to develop faster and more reliable clinical detection, treatment, and monitoring methods to enhance their clinical applications. Raman spectroscopy is noninvasive and provides highly specific information about the molecular structure and biochemical composition of analytes in a rapid and accurate manner. It has a wide range of applications in biomedicine, materials, and clinical settings. This review primarily focuses on the application of Raman spectroscopy in clinical medicine. The advantages and limitations of Raman spectroscopy over traditional clinical methods are discussed. In addition, the advantages of combining Raman spectroscopy with machine learning, nanoparticles, and probes are demonstrated, thereby extending its applicability to different clinical phases. Examples of the clinical applications of Raman spectroscopy over the last 3 years are also integrated. Finally, various prospective approaches based on Raman spectroscopy in clinical studies are surveyed, and current challenges are discussed. The paper systematically demonstrates the status and trends in the application development of Raman combined with machine learning, nanoparticles, and probes in typical clinical diseases. The focus is to explore the limitations and sources of errors in traditional techniques, providing a comprehensive showcase of the typical research outcomes of Raman in clinical settings over the past 3 years. This review offers profound insights for future research.image

Automated summary

This review focuses on the application of Raman spectroscopy in clinical medicine. It discusses the advantages and limitations of Raman spectroscopy over traditional clinical methods, as well as its integration with machine learning, nanoparticles, and probes. The review also provides examples of recent clinical applications and explores prospective approaches and current challenges in clinical studies based on Raman spectroscopy.