Publications by authors named "Alison McIlvride"
Article Synopsis
- A convolutional neural network (CNN)-based algorithm developed to distinguish atypical ductal hyperplasia (ADH) from ductal carcinoma in situ (DCIS) is validated using a new dataset of 280 mammographic images from 140 patients.
- The study involved a rigorous analysis of these images, utilizing advanced CNN techniques and standard metrics to assess diagnostic performance, focusing on sensitivity, specificity, and accuracy.
- Results showed the algorithm achieved a high area under the curve (0.90), with diagnostic accuracy at 80.7%, sensitivity at 63.9%, and specificity at 93.7%, confirming its effectiveness on unseen data.
Development of a New Patient-reported Outcome Instrument to Evaluate Treatments for Scars: The SCAR-Q.
Plast Reconstr Surg Glob Open
April 2018
Background: Every year millions of individuals acquire scars. A literature review of patient-reported outcome (PRO) instruments identified content limitations in existing scar-specific measures. The aim of this study was to develop a new PRO instrument called SCAR-Q for children and adults with surgical, traumatic, and burn scars.
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