Artificial intelligence-integrated wearable biomedical devices for cancer management

Area of Science:

• Biomedical Engineering
• Oncology
• Artificial Intelligence

Background:

• Cancer is a leading global cause of death, necessitating improved early diagnosis and intervention.
• Traditional cancer diagnostics are invasive, costly, and limit real-time monitoring and patient compliance.
• Wearable biomedical devices (WBDs) offer continuous, non-invasive monitoring and potential for integrated therapy.

Purpose of the Study:

• To review artificial intelligence (AI)-integrated WBDs for cancer screening, diagnosis, and therapy.
• To highlight innovations addressing limitations in current cancer management strategies.
• To discuss future directions for AI-powered WBDs in oncology.

Main Methods:

• Review of current literature on AI-integrated WBDs in cancer care.
• Analysis of innovations in WBD design, materials, and integrated technologies.
• Exploration of AI applications for signal processing and data analysis in WBDs.

Main Results:

• AI-integrated WBDs enable continuous, non-invasive in situ monitoring and real-time tissue imaging.
• Innovations include conformable structures, advanced adhesives, and integrated sensors/drug delivery modules.
• AI integration significantly improves signal-to-noise ratio (SNR) and real-time data processing for enhanced monitoring.

Conclusions:

• AI-integrated WBDs represent a promising advancement for early cancer detection, diagnosis, and personalized therapy.
• Further development is needed to improve SNR, reduce false positives, and ensure patient data privacy.
• These technologies have the potential to revolutionize cancer management by enabling precise, on-demand interventions.