Cargando…

Artificial Intelligence in Retinopathy of Prematurity Diagnosis

Retinopathy of prematurity (ROP) is a leading cause of childhood blindness worldwide. The diagnosis of ROP is subclassified by zone, stage, and plus disease, with each area demonstrating significant intra- and interexpert subjectivity and disagreement. In addition to improved efficiencies for ROP sc...

Descripción completa

Detalles Bibliográficos
Autores principales:	Scruggs, Brittni A., Chan, R. V. Paul, Kalpathy-Cramer, Jayashree, Chiang, Michael F., Campbell, J. Peter
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	The Association for Research in Vision and Ophthalmology 2020
Materias:	Special Issue
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7343673/ https://www.ncbi.nlm.nih.gov/pubmed/32704411 http://dx.doi.org/10.1167/tvst.9.2.5

Ejemplares similares

Synthetic Medical Images for Robust, Privacy-Preserving Training of Artificial Intelligence: Application to Retinopathy of Prematurity Diagnosis
por: Coyner, Aaron S., et al.
Publicado: (2022)

Plus Disease in Retinopathy of Prematurity: Convolutional Neural Network Performance Using a Combined Neural Network and Feature Extraction Approach
por: Yildiz, Veysi M., et al.
Publicado: (2020)

Introduction to Machine Learning, Neural Networks, and Deep Learning
por: Choi, Rene Y., et al.
Publicado: (2020)

Evaluation of an Artificial Intelligence System for Retinopathy of Prematurity Screening in Nepal and Mongolia
por: Cole, Emily, et al.
Publicado: (2022)

Assessment of Retinopathy of Prematurity Regression and Reactivation Using an Artificial Intelligence–Based Vascular Severity Score
por: Eilts, Sonja K., et al.
Publicado: (2023)

Health Economic and Safety Considerations for Artificial Intelligence Applications in Diabetic Retinopathy Screening
por: Xie, Yuchen, et al.
Publicado: (2020)

Peripheral OCT Assisted by Scleral Depression in Retinopathy of Prematurity
por: Scruggs, Brittni A., et al.
Publicado: (2021)

Current Challenges and Barriers to Real-World Artificial Intelligence Adoption for the Healthcare System, Provider, and the Patient
por: Singh, Rishi P., et al.
Publicado: (2020)

Applications of Artificial Intelligence to Electronic Health Record Data in Ophthalmology
por: Lin, Wei-Chun, et al.
Publicado: (2020)

Oxygenation Fluctuations Associated with Severe Retinopathy of Prematurity: Insights from a Multimodal Deep Learning Approach
por: Lin, Wei-Chun, et al.
Publicado: (2023)

Improved Training Efficiency for Retinopathy of Prematurity Deep Learning Models Using Comparison versus Class Labels
por: Hanif, Adam, et al.
Publicado: (2022)

Convolutional Neural Network Based on Fluorescein Angiography Images for Retinopathy of Prematurity Management
por: Lepore, Domenico, et al.
Publicado: (2020)

Quantification of Early Neonatal Oxygen Exposure as a Risk Factor for Retinopathy of Prematurity Requiring Treatment
por: Chen, Jimmy S., et al.
Publicado: (2021)

Artificial Intelligence and Glaucoma: Going Back to Basics
por: AlRyalat, Saif Aldeen, et al.
Publicado: (2023)

Artificial Intelligence Mapping of Structure to Function in Glaucoma
por: Mariottoni, Eduardo B., et al.
Publicado: (2020)

Artificial Intelligence Algorithms for Analysis of Geographic Atrophy: A Review and Evaluation
por: Arslan, Janan, et al.
Publicado: (2020)

Artificial Intelligence for Automated Overlay of Fundus Camera and Scanning Laser Ophthalmoscope Images
por: Cavichini, Melina, et al.
Publicado: (2020)

How Artificial Intelligence Can Transform Randomized Controlled Trials
por: Lee, Cecilia S., et al.
Publicado: (2020)

Challenges for future directions for artificial intelligence integrated nursing simulation education
por: Jung, Sunyoung
Publicado: (2023)

Transfer Learning for Automated OCTA Detection of Diabetic Retinopathy
por: Le, David, et al.
Publicado: (2020)

Artificial Intelligence Algorithms to Diagnose Glaucoma and Detect Glaucoma Progression: Translation to Clinical Practice
por: Mursch-Edlmayr, Anna S., et al.
Publicado: (2020)

A Clinician's Guide to Artificial Intelligence: How to Critically Appraise Machine Learning Studies
por: Faes, Livia, et al.
Publicado: (2020)

Artificial intelligence for microbial biotechnology: beyond the hype
por: Robinson, Serina L.
Publicado: (2021)

Artificial Intelligence to Stratify Severity of Age-Related Macular Degeneration (AMD) and Predict Risk of Progression to Late AMD
por: Bhuiyan, Alauddin, et al.
Publicado: (2020)

Ganirelix and the prevention of premature luteinizing hormone surges
por: Mannaerts, Bernadette
Publicado: (2023)

Environmentally sustainable development and use of artificial intelligence in health care
por: Richie, Cristina
Publicado: (2022)

Advantages of Widefield Optical Coherence Tomography in the Diagnosis of Retinopathy of Prematurity
por: Nguyen, Thanh-Tin P., et al.
Publicado: (2022)

A riddle, wrapped in a mystery, inside an enigma: How semantic black boxes and opaque artificial intelligence confuse medical decision‐making
por: Pierce, Robin, et al.
Publicado: (2021)

Ensemble Deep Learning for Diabetic Retinopathy Detection Using Optical Coherence Tomography Angiography
por: Heisler, Morgan, et al.
Publicado: (2020)

Patient-specific, mechanistic models of tumor growth incorporating artificial intelligence and big data
por: Lorenzo, Guillermo, et al.
Publicado: (2023)

Quantifying Microvascular Abnormalities With Increasing Severity of Diabetic Retinopathy Using Optical Coherence Tomography Angiography
por: Nesper, Peter L., et al.
Publicado: (2017)

Artificial intelligence and its applications in digital hematopathology
por: Hu, Yongfei, et al.
Publicado: (2022)

Artificial Intelligence and Behavioral Science Through the Looking Glass: Challenges for Real-World Application
por: Mac Aonghusa, Pol, et al.
Publicado: (2021)

Multidimensional Functional and Structural Evaluation Reveals Neuroretinal Impairment in Early Diabetic Retinopathy
por: Joltikov, Katherine A., et al.
Publicado: (2017)

Leveraging Multimodal Deep Learning Architecture with Retina Lesion Information to Detect Diabetic Retinopathy
por: Tseng, Vincent S., et al.
Publicado: (2020)

Systematic Comparison of Heatmapping Techniques in Deep Learning in the Context of Diabetic Retinopathy Lesion Detection
por: Van Craenendonck, Toon, et al.
Publicado: (2020)

Fast and Automated Hyperreflective Foci Segmentation Based on Image Enhancement and Improved 3D U-Net in SD-OCT Volumes with Diabetic Retinopathy
por: Xie, Sha, et al.
Publicado: (2020)

Automatic Identification of Referral-Warranted Diabetic Retinopathy Using Deep Learning on Mobile Phone Images
por: Ludwig, Cassie A., et al.
Publicado: (2020)

Artificial intelligence approaches to predict coronary stenosis severity using non-invasive fractional flow reserve
por: Carson, Jason M, et al.
Publicado: (2020)

Artificial intelligence promotes the diagnosis and screening of diabetic retinopathy
por: Huang, Xuan, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_7n62o0bjfn6isnu9apt7k30ogm