Millions of thyroid biopsies are done every year based on very subjective criteria to find thyroid cancer in a very small percentage of population with an invasive technique which may not be diagnostic 1 out of 7 times.

AIBx is a clinical decision support tool.

Uses deep learning to find similar thyroid ultrasound images from our database and displays it along with the associated diagnosis.

Physician's can compare these similar images to their test image and reach a clinical decision.


Similar Images

Physician in Loop

Explainable AI

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AIBx Demo

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References:

Thomas, J., & Haertling, T. (2020). AIBx, artificial intelligence model to risk stratify thyroid nodules. Thyroid.

Other articles and book chapters referencing AIBx:

  • Orloff, L. A. (2020). Artificial Intelligence plus Human Interpretation for Thyroid Nodule Risk Stratification: An Image Similarity Model Keeps the Physician in the Loop. Clinical Thyroidology, 32(6), 276-278.

  • Unnikrishnan, A. G., & Kalra, S. (2020). Could artificial intelligence help in the risk stratification of thyroid nodules?. Thyroid Research and Practice, 17(2), 51.

  • Thomas, J. (2020). Application of Artificial Intelligence in Thyroidology. Artificial Intelligence: Applications in Healthcare Delivery, 273.

  • Thomas, J., Ledger, G. A., & Mamillapalli, C. K. (2020). Use of artificial intelligence and machine learning for estimating malignancy risk of thyroid nodules. Current Opinion in Endocrinology, Diabetes and Obesity, 27(5), 345-350.

  • Wang, S., Xu, J., Tahmasebi, A., Daniels, K., Liu, J. B., Curry, J., ... & Eisenbrey, J. R. (2020). Incorporation of a Machine Learning Algorithm With Object Detection Within the Thyroid Imaging Reporting and Data System Improves the Diagnosis of Genetic Risk. Frontiers in Oncology, 10, 2481.

  • 李铃睿, 杜博, & 陈创. (2020). 人工智能在甲状腺癌精准化诊疗中的研究进展.

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