Emerging Technologies for Timely Point-of-Care Diagnostics of Skin Cancer

Area of Science:

• Oncology and Medical Diagnostics
• Biomedical Engineering
• Spectroscopy

Background:

• Skin cancer is a global health concern, with rising incidence linked to UV radiation, population changes, and inadequate screening.
• Current diagnostic methods for skin cancer are often invasive, slow, costly, and lack portability, necessitating advancements in diagnostic technology.

Purpose of the Study:

• To review and consolidate recent advancements in skin cancer diagnostics across medical and engineering fields.
• To highlight Raman spectroscopy and artificial intelligence as key technologies for developing rapid, accurate, point-of-care diagnostic tools for skin cancer.

Main Methods:

• Overview of traditional and emerging skin cancer detection methods, including chemo-biophysical sensing techniques.
• Focus on Raman spectroscopy for non-invasive molecular fingerprint detection in dermatological samples.
• Integration of artificial intelligence as a decision support tool for diagnostic accuracy.

Main Results:

• Raman spectroscopy demonstrates potential as a rapid, non-invasive diagnostic tool for skin cancer, offering molecular-level insights.
• The combination of Raman spectroscopy and AI can enhance diagnostic accuracy and support clinical decision-making.
• Progress is being made towards translating these technologies into practical point-of-care applications.

Conclusions:

• There is an urgent need for improved skin cancer diagnostics due to rising global incidents.
• Raman spectroscopy, augmented by artificial intelligence, presents a promising pathway for developing advanced, non-invasive, point-of-care diagnostic solutions for skin cancer.
• Further development and translation are crucial for real-world application and timely intervention in skin cancer management.