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Validation of an Artificial Intelligence-based Algorithm for Skeletal Age Assessment

2018-05-23 19:36:11 | BioPortfolio

Summary

The purpose of this study is to understand the effects of using a Artificial Intelligence algorithm for skeletal age estimation as a computer-aided diagnosis (CADx) system. In this prospective real-time study, the investigators will send de-identified hand radiographs to the Artificial Intelligence algorithm and surface the output of this algorithm to the radiologist, who will incorporate this information with their normal workflows to make a diagnosis of the patient's bone age. All radiologists involved in the study will be trained to recognize the surfaced prediction to be the output of the Artificial Intelligence algorithm. The radiologists' diagnosis will be final and considered independent to the output of the algorithm.

Description

The investigators are targeting to study the effect of their Artificial Intelligence algorithm on the radiologists' estimation of skeletal age. Currently, radiologists make the estimation using only the patients' radiographic images and health records. As part of this study, the radiologists will make diagnoses about their patients using the patients' radiographic images, health records, and the output of the CADx algorithm. The investigators wish to understand how radiologists using the Artificial Intelligence algorithm compare to radiologists who do not for the specific task of estimating skeletal age.

This study is organized as a multi-institutional randomized control trial with two arms - experiment (receiving the Artificial Intelligence algorithm's output) and control (no intervention). Both of these arms will be compared to a clinical reference standard ("gold standard") composed of a panel of radiologists. The metric of comparison will be Mean Absolute Distance (MAD) and Root-Mean-Square (RMS) error. The investigators plan to use statistical tests such as the t-test to determine any statistically-significant difference in skeletal age estimation between the two groups.

The investigators hope to recruit and analyze data from a sample size of 1000 patients.The patients will not undergo any research procedures that deviate from the current standard practices.

Study Design

Conditions

Bone Age

Intervention

BoneAgeModel

Status

Not yet recruiting

Source

Stanford University

Results (where available)

View Results

Links

Published on BioPortfolio: 2018-05-23T19:36:11-0400

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