Literature DB >> 33734908

Biomarkers for Progression in Diabetic Retinopathy: Expanding Personalized Medicine through Integration of AI with Electronic Health Records.

Cris Martin P Jacoba1,2, Leo Anthony Celi3,4,5, Paolo S Silva1,2.   

Abstract

The goal of personalized diabetes eye care is to accurately predict in real-time the risk of diabetic retinopathy (DR) progression and visual loss. The use of electronic health records (EHR) provides a platform for artificial intelligence (AI) algorithms that predict DR progression to be incorporated into clinical decision-making. By implementing an algorithm on data points from each patient, their risk for retinopathy progression and visual loss can be modeled, allowing them to receive timely treatment. Data can guide algorithms to create models for disease and treatment that may pave the way for more personalized care. Currently, there exist numerous challenges that need to be addressed before reliably building and deploying AI algorithms, including issues with data quality, privacy, intellectual property, and informed consent.

Entities:  

Keywords:  Artificial intelligence; biomarkers; diabetic retinopathy; electronic health records; personalized medicine

Mesh:

Substances:

Year:  2021        PMID: 33734908      PMCID: PMC8122081          DOI: 10.1080/08820538.2021.1893351

Source DB:  PubMed          Journal:  Semin Ophthalmol        ISSN: 0882-0538            Impact factor:   1.975


  44 in total

Review 1.  Biomarkers and surrogate endpoints: preferred definitions and conceptual framework.

Authors: 
Journal:  Clin Pharmacol Ther       Date:  2001-03       Impact factor: 6.875

2.  Re-identification of familial database records.

Authors:  Bradley Malin
Journal:  AMIA Annu Symp Proc       Date:  2006

3.  Assessing the need for on-site eye care professionals in community health centers.

Authors:  Peter Shin; Brad Finnegan
Journal:  Policy Brief George Wash Univ Cent Health Serv Res Policy       Date:  2009-02

4.  Identification of individuals by trait prediction using whole-genome sequencing data.

Authors:  Christoph Lippert; Riccardo Sabatini; M Cyrus Maher; Eun Yong Kang; Seunghak Lee; Okan Arikan; Alena Harley; Axel Bernal; Peter Garst; Victor Lavrenko; Ken Yocum; Theodore Wong; Mingfu Zhu; Wen-Yun Yang; Chris Chang; Tim Lu; Charlie W H Lee; Barry Hicks; Smriti Ramakrishnan; Haibao Tang; Chao Xie; Jason Piper; Suzanne Brewerton; Yaron Turpaz; Amalio Telenti; Rhonda K Roby; Franz J Och; J Craig Venter
Journal:  Proc Natl Acad Sci U S A       Date:  2017-09-05       Impact factor: 11.205

5.  Effects of medical therapies on retinopathy progression in type 2 diabetes.

Authors:  Emily Y Chew; Walter T Ambrosius; Matthew D Davis; Ronald P Danis; Sapna Gangaputra; Craig M Greven; Larry Hubbard; Barbara A Esser; James F Lovato; Letitia H Perdue; David C Goff; William C Cushman; Henry N Ginsberg; Marshall B Elam; Saul Genuth; Hertzel C Gerstein; Ulrich Schubart; Lawrence J Fine
Journal:  N Engl J Med       Date:  2010-06-29       Impact factor: 91.245

6.  Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: Results from the International Diabetes Federation Diabetes Atlas, 9th edition.

Authors:  Pouya Saeedi; Inga Petersohn; Paraskevi Salpea; Belma Malanda; Suvi Karuranga; Nigel Unwin; Stephen Colagiuri; Leonor Guariguata; Ayesha A Motala; Katherine Ogurtsova; Jonathan E Shaw; Dominic Bright; Rhys Williams
Journal:  Diabetes Res Clin Pract       Date:  2019-09-10       Impact factor: 5.602

7.  Photocoagulation treatment of proliferative diabetic retinopathy. Clinical application of Diabetic Retinopathy Study (DRS) findings, DRS Report Number 8. The Diabetic Retinopathy Study Research Group.

Authors: 
Journal:  Ophthalmology       Date:  1981-07       Impact factor: 12.079

8.  Rosiglitazone and delayed onset of proliferative diabetic retinopathy.

Authors:  Lucy Q Shen; Angie Child; Griffin M Weber; Judah Folkman; Lloyd Paul Aiello
Journal:  Arch Ophthalmol       Date:  2008-06

9.  Association of glycation gap with mortality and vascular complications in diabetes.

Authors:  Ananth U Nayak; Alan M Nevill; Paul Bassett; Baldev M Singh
Journal:  Diabetes Care       Date:  2013-07-08       Impact factor: 19.112

Review 10.  Applications of Artificial Intelligence to Electronic Health Record Data in Ophthalmology.

Authors:  Wei-Chun Lin; Jimmy S Chen; Michael F Chiang; Michelle R Hribar
Journal:  Transl Vis Sci Technol       Date:  2020-02-27       Impact factor: 3.283

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