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The issues and trends in healthcare delivery are constantly changing. The COVID-19 pandemic is one recent issue that wreaked havoc on healthcare systems, causing a shortage of healthcare workers, high demand for medicines and supplies, and increased medical expenditure due to a lack of insurance. Other issues include rising healthcare costs and care fragmentation.
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Artificial Intelligence in Head and Neck Cancer: Innovations, Applications, and Future Directions.

Tuan D Pham¹, Muy-Teck Teh¹, Domniki Chatzopoulou¹

¹Barts and The London School of Medicine and Dentistry, Queen Mary University of London, Turner Street, London E1 2AD, UK.

Current Oncology (Toronto, Ont.)

|September 27, 2024

Summary

This summary is machine-generated.

Artificial intelligence (AI) enhances head and neck cancer (HNC) care through improved diagnostics and personalized treatments. Further research and collaboration are key to overcoming challenges and realizing AI's full potential in HNC.

Keywords:

artificial intelligence biomarker discovery deep learning early detection explainable machine intelligence head and neck cancer imaging techniques natural language processing oral cancer personalized treatment

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Area of Science:

Oncology
Medical Informatics
Computer Science

Background:

Artificial intelligence (AI) is transforming healthcare, with significant potential in head and neck cancer (HNC) management.
Current HNC care faces challenges in diagnostic accuracy, treatment personalization, and data integration.

Purpose of the Study:

To review advancements in AI technologies and their applications in head and neck cancer care.
To explore the integration of AI with various data sources for improved HNC diagnostics and treatment.
To identify challenges and future directions for AI in HNC.

Main Methods:

Review of current literature on AI applications in head and neck cancer.
Analysis of AI technologies such as deep learning and natural language processing.
Exploration of AI integration with imaging, genomics, and electronic health records.

Main Results:

AI demonstrates potential in enhancing diagnostic accuracy and personalizing treatment strategies for HNC.
Integration of AI with diverse data sources aids in early detection, biomarker discovery, and treatment planning.
Challenges include data quality, algorithmic bias, and the need for interdisciplinary collaboration.

Conclusions:

AI offers promising breakthroughs for head and neck cancer diagnostics, personalized therapies, and patient outcomes.
Addressing challenges and fostering collaboration are essential for equitable and effective AI implementation in HNC.
Emerging innovations like explainable AI and AI-powered robotics will further advance the field.