Publications by authors named "G T Gold"
Developing a Research Center for Artificial Intelligence in Medicine.
Mayo Clin Proc Digit Health
December 2024
Artificial intelligence (AI) and machine learning (ML) are driving innovation in biosciences and are already affecting key elements of medical scholarship and clinical care. Many schools of medicine are capitalizing on the promise of these new technologies by establishing academic units to catalyze and grow research and innovation in AI/ML. At Stanford University, we have developed a successful model for an AI/ML research center with support from academic leaders, clinical departments, extramural grants, and industry partners.
View Article and Find Full Text PDFBackground: Post-traumatic osteoarthritis (PTOA) often follows anterior cruciate ligament reconstruction (ACLR), leading to early cartilage degradation. Change in mean T fails to capture subject-specific spatial-temporal variations, highlighting the need for robust quantitative methods for early PTOA detection and monitoring.
Purpose/hypothesis: Develop and apply 3D T cluster analysis to ACLR and healthy knees over 2.
Article Synopsis
- Analyzing the shapes of tissues and organs is crucial for diagnosing diseases like osteoarthritis, which affects many Americans; a new dataset called ShapeMed-Knee has been introduced to support this analysis.
- ShapeMed-Knee contains 9,376 high-resolution 3D shapes of femur bones and cartilage, along with benchmarks for accuracy and clinical prediction tasks, enhancing the understanding of osteoarthritis.
- The authors developed a cutting-edge hybrid neural shape model using ShapeMed-Knee that significantly improves reconstruction accuracy and accurately predicts localized osteoarthritis features, with plans to make the dataset, code, and benchmarks publicly available.
In computed tomography (CT) imaging, optimizing the balance between radiation dose and image quality is crucial due to the potentially harmful effects of radiation on patients. Although subjective assessments by radiologists are considered the gold standard in medical imaging, these evaluations can be time-consuming and costly. Thus, objective methods, such as the peak signal-to-noise ratio and structural similarity index measure, are often employed as alternatives.
View Article and Find Full Text PDFArticle Synopsis
- - The text discusses the importance of analyzing the shapes of tissues and organs for diagnosing diseases, focusing on osteoarthritis, which affects a significant number of people in the U.S.
- - A new 3D shape dataset called ShapeMed-Knee has been introduced, containing 9,376 high-resolution models of the femur bone and cartilage, along with benchmarks for accuracy and clinical prediction tasks.
- - The study presents a hybrid neural shape model that outperforms existing models in accuracy and the ability to predict features related to osteoarthritis, aiming to improve medical diagnostics while providing open access to the dataset and tools.