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Articles by Terry Spitz
Health equity assessment of machine learning performance (HEAL): a framework and dermatology AI model case study
Keywords Artificial intelligence Machine learning Health equity Dermatology Evidence before this study We searched the PubMed database from Jan 1, 2018 until Aug 31, 2022, for articles using the following search terms: ‘health equity’ AND (‘machine learning’ OR ‘artificial intelligence’). In addition, we searched relevant computer science journals and conference proceedings using similar search terms. The retrieved articles were analysed with respect to the proposed framework components.
Enhancing the reliability and accuracy of AI-enabled diagnosis via complementarity-driven deferral to clinicians - Nature Medicine
Abstract Predictive artificial intelligence (AI) systems based on deep learning have been shown to achieve expert-level identification of diseases in multiple medical imaging settings, but can make errors in cases accurately diagnosed by clinicians and vice versa. We developed Complementarity-Driven Deferral to Clinical Workflow (CoDoC), a system that can learn to decide between the opinion of a predictive AI model and a clinical workflow.
A mobile-optimized artificial intelligence system for gestational age and fetal malpresentation assessment - Communications Medicine
Blind-sweep procedure Blind-sweep ultrasounds consisted of a fixed number of predefined freehand ultrasound sweeps over the gravid abdomen. Certified sonographers completed up to 15 sweeps. Novice operators (“novices”), with 8 h of blind-sweep ultrasound acquisition training, completed six sweeps. Evaluation of both sonographers and novices was limited to a set of six sweeps—three vertical and three horizontal sweeps (Fig. 1b).
Predicting conversion to wet age-related macular degeneration using deep learning - Nature Medicine
Abstract Progression to exudative ‘wet’ age-related macular degeneration (exAMD) is a major cause of visual deterioration. In patients diagnosed with exAMD in one eye, we introduce an artificial intelligence (AI) system to predict progression to exAMD in the second eye.
How AI could predict sight-threatening eye conditions
How AI could predict the development of wet AMD In collaboration with colleagues at DeepMind and Moorfields Eye Hospital NHS Foundation Trust, we’ve developed an artificial intelligence (AI) model that has the potential to predict whether a patient will develop wet AMD within six months. In the future, this system could potentially help doctors plan studies of earlier intervention, as well as contribute more broadly to clinical understanding of the disease and disease progression.
Letter to the Editor: First United Methodist pastor committed to Christianity
OPINION Terry Spitz, Letter to the Editor Published 12:00 p.m. PT Feb. 10, 2020 Buy Photo People gather early morning outside the First United Methodist Church for breakfast on Jan. 8, 2020. (Photo: David Rodriguez/The Salinas Californian) Thank you for last Friday’s coverage of First Methodist Church. I would like to help Adam Stafford in his project to investigate Pastor Lundin’s character. For a start, I urge Mr. Stafford to look at things through the pastor’s eyes.
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