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Summary

Artificial intelligence (AI) shows promise in evaluating thyroid nodules and other medical specimens. Successful implementation requires careful consideration of technology, support, and financial factors.

Keywords:

artificial intelligence review risk stratification thyroid nodules

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Area of Science:

Medical Imaging Analysis
Artificial Intelligence in Healthcare
Diagnostic Technologies

Background:

This review discusses the evolving role of artificial intelligence (AI) in medical diagnostics.
Focus areas include the assessment of thyroid nodules, cervical lymph nodes, and tissue specimens (cytology/histology).
Guidance is provided for healthcare practices considering the integration of AI systems.

Purpose of the Study:

To provide an updated review on AI applications in head and neck diagnostics.
To guide healthcare practices on the evaluation and installation of AI systems.
To summarize the current regulatory status and performance of AI tools in medical assessment.

Main Methods:

Review of current literature and FDA-cleared AI platforms for medical image analysis.
Discussion of performance metrics, particularly in comparison to physician expertise.
Analysis of key considerations for AI system implementation in clinical practice.

Main Results:

Six AI platforms for thyroid nodule sonogram assessment are FDA-cleared, demonstrating good performance, especially against less experienced physicians.
Multimodality large language models show potential but have yielded less impressive results to date.
Software for lymph node and specimen evaluation is promising but not yet commercially available.

Conclusions:

AI tools for thyroid nodule evaluation are increasing, with commercial software for lymph nodes and slide specimens anticipated.
Successful implementation and operation of AI systems necessitate meticulous attention to detail.
Practices must consider IT, vendor support, effectiveness, usability, and finance when installing AI systems, engaging experts throughout the process.