Výsledky vyhledávání - "Perry J Pickhardt"

Akademický článek

Automated CT biomarkers for opportunistic prediction of future cardiovascular events and mortality in an asymptomatic screening population: a retrospective cohort study

Autor: Perry J Pickhardt, ProfMD, Peter M Graffy, MPH, Ryan Zea, MS, Scott J Lee, MD, Jiamin Liu, PhD, Veit Sandfort, MD, Ronald M Summers, ProfMD

Publikováno v: The Lancet: Digital Health, Vol 2, Iss 4, Pp e192-e200 (2020)

Summary: Background: Body CT scans are frequently done for a wide range of clinical indications, but potentially valuable biometric information typically goes unused. We aimed to compare the prognostic ability of automated CT-based body composition b

Externí odkaz: https://doaj.org/article/16ec226ad2fb4ec2b034f32ec4466710

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Akademický článek

Correlation of HbA1c levels with CT-based body composition biomarkers in diabetes mellitus and metabolic syndrome

Autor: Joshua D. Warner, Glen M. Blake, John W. Garrett, Matthew H. Lee, Leslie W. Nelson, Ronald M. Summers, Perry J. Pickhardt

Publikováno v: Scientific Reports, Vol 14, Iss 1, Pp 1-14 (2024)

Abstract Diabetes mellitus and metabolic syndrome are closely linked with visceral body composition, but clinical assessment is limited to external measurements and laboratory values including hemoglobin A1c (HbA1c). Modern deep learning and AI algor

Externí odkaz: https://doaj.org/article/0805c1dcca86498cacadbe56501210ff

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Akademický článek

Addressing the challenge of assessing physician-level screening performance: mammography as an example.

Autor: Elizabeth S Burnside, Yunzhi Lin, Alejandro Munoz del Rio, Perry J Pickhardt, Yirong Wu, Roberta M Strigel, Mai A Elezaby, Eve A Kerr, Diana L Miglioretti

Publikováno v: PLoS ONE, Vol 9, Iss 2, p e89418 (2014)

Motivated by the challenges in assessing physician-level cancer screening performance and the negative impact of misclassification, we propose a method (using mammography as an example) that enables confident assertion of adequate or inadequate perfo

Externí odkaz: https://doaj.org/article/32ca70d627d546eeb0311639069a7260

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Akademický článek

Author Correction: Opportunistic detection of type 2 diabetes using deep learning from frontal chest radiographs

Publikováno v: Nature Communications, Vol 15, Iss 1, Pp 1-1 (2024)

Externí odkaz: https://doaj.org/article/e2d1fcc1da9a4a75bc20a627cd3c3ba8

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Akademický článek

Opportunistic detection of type 2 diabetes using deep learning from frontal chest radiographs

Publikováno v: Nature Communications, Vol 14, Iss 1, Pp 1-12 (2023)

Abstract Deep learning (DL) models can harness electronic health records (EHRs) to predict diseases and extract radiologic findings for diagnosis. With ambulatory chest radiographs (CXRs) frequently ordered, we investigated detecting type 2 diabetes

Externí odkaz: https://doaj.org/article/7a733957020f47618b736360b6cd8f9b

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Akademický článek

Multi-scale characterizations of colon polyps via computed tomographic colonography

Autor: Weiguo Cao, Marc J. Pomeroy, Yongfeng Gao, Matthew A. Barish, Almas F. Abbasi, Perry J. Pickhardt, Zhengrong Liang

Publikováno v: Visual Computing for Industry, Biomedicine, and Art, Vol 2, Iss 1, Pp 1-12 (2019)

Abstract Texture features have played an essential role in the field of medical imaging for computer-aided diagnosis. The gray-level co-occurrence matrix (GLCM)-based texture descriptor has emerged to become one of the most successful feature sets fo

Externí odkaz: https://doaj.org/article/c5fcc9c7ca4e467c8b3be4680bf9746b

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