Education Courses

April 22, 2023 | New Orleans, La.

Education Courses

ARVO is pleased to present the Education Course selection for 2023. All courses will be held in-person April 22 at the New Orleans Ernest N. Morial Convention Center (900 Convention Center Blvd, New Orleans, La. 70130). Courses may be added on to your registration for the 2023 Annual Meeting. Choose between Full-day or Half-day courses. Information about each course is listed below. 

Full-day courses 

Full-day course fee    By March 15 After March 15
Member $235 $289
Member-in-Training $175 $199
Nonmember $310 $364
Nonmember-in-Training $215 $239


Improving artificial intelligence (AI) and data trust in ophthalmology: From clinical trials to real-world adoption

8am – 4:30pm

Daniela Ferrara, MD, MS, PhD, FASRS, Tufts University School of Medicine
Daniel S.W. Ting, MD, PhD, Singapore National Eye Centre
Dawn Sim, MBBS, FRCOphth, PhD, Genentech Roche

Despite widespread research in Artificial Intelligence (AI), many ophthalmologists remain unfamiliar with the potential of AI-based tools in clinical medicine, since AI/ machine learning (ML) sits at the intersection of multiple scientific fields (e.g., computer science, mathematics, probability/statistics) that are not traditionally included in medical education or in studies of the biological sciences.

Attend this course to improve your understanding of Artificial Intelligence (AI), its current strengths and weaknesses, and potential for future development. Glean insights from case-studies of real-world applications of AI-based tools: learn about clinical trials/drug development basics, fundamental principles of AI, ML and DL, opportunities and challenges to development and adoption (including data sharing and privacy, device standardization, regulatory aspects, and transparency).

After attending this course, you will be able to:

  • Describe the basic steps of the drug development process- from molecule discovery to clinical trials to regulatory approval
  • Define fundamental concepts of Artificial Intelligence (AI) and machine learning
  • Identify the limitations and trade-offs of using Big Data, artificial intelligence, and machine learning in clinical trials and drug development

This activity is not eligible for AMA PRA Category 1 Credit™.

Diabetic retinopathy: Moving the field forward

8am – 4:30pm

Renu A Kowluru, PhD, FARVO, Wayne State University, Kresge Eye Institute
Arup Das, MD, PhD, University of New Mexico School of Medicine, NM VA Health Care System

The pathophysiology of diabetic retinopathy is extraordinarily complex, which can be intimidating to researchers new to this subject. Progress in the development of treatments, the management of diabetic macular edema and proliferative diabetic retinopathy remains challenging-- with newer pharmacotherapy protocols based on results of recently finished, multi-center clinical trials and the use of new diagnostic tools.

A balanced discussion by both clinicians and basic scientists will address the gaps in our understanding of the disease and will include conversations with experts on novel approaches to tackle the problem. Participants of this session will leave with the ability to design a research project using appropriate experimental models and gain an understanding of how to set up a clinical trial with exposure to information regarding genetic associations and novel single cell technology and imaging techniques.

After attending this course, you will be able to:

  • Discuss the clinical aspects, epidemiology, systemic factors, and genetics of diabetic retinopathy
  • Describe the new experimental models, molecular mechanism and role of various retinal cell types.
  • Cite recent updates on novel therapies, diagnostic studies, and novel biomarkers

The use of electrophysiologic techniques in vision research

8am – 4:30pm

Mitchell Brigell, PhD, FARVO, Occuphire Pharma
Laura Frishman, PhD, FARVO, University of Houston

With the advent of new therapies for blinding diseases, there is an increasing need for functional outcome measurements that can be made in animal models and human clinical research. Electrophysiologic techniques have advanced in recent years, however these techniques are not widely taught in PhD or MD programs, and as a result are underutilized in basic, translational, and clinical vision research.

Attend this course if you are interested in gaining insights into the use of electrophysiologic techniques to probe the visual system, by engaging in a discussion on the origins of electrophysiologic signals recorded from the retina, and standardized techniques for recording these signals. Attendees will gain real world insights from subject matter experts regarding applications in acquired and inherited diseases of the retina and optic nerve and animal models of these diseases.

After attending this course, you will be able to:

  • Incorporate electrophysiological measures into your research
  • Distinguish the cellular origins of the responses and their relation to structural and other functional measures of retinal and optic nerve function
  • Explain international standards for recording and interpreting electrophysiologic signals
  • Describe recent technological advances that afford new insights into function of the visual pathways

Half-day courses


Half-day course fee By March 15 After March 15
Member $140 $175
Member-in-training $105 $120
Nonmember $185 $220
Nonmember-in-training $130 $145


Using electronic health records (EHR) data: Data readiness and FAIR principles

8am – Noon

Kerry Goetz, MS, National Eye Institute (NEI)
Michelle Hribar, PhD, MS, Oregon Health & Science University (OHSU)/National Eye Institute (NEI)

The learning health system requires researchers to interpret high-dimensional heterogeneous medical data while also making efficient and accurate decisions regarding diagnosis and treatment. Widespread adoption of electronic health records (EHRs) has resulted in the collection of massive amounts of clinical data, however, EHR data has not yet achieved data readiness (data that are high quality, available, interoperable, and have clearly defined provenance).

Attend this course if you are interested in the secondary use of electronic health record (EHR) data for research. Instructors will present a framework for FAIR Data Principles (Findable, Accessible, Interoperable, and Reusable), and participants will gain valuable insights regarding data standards and common data models, including the Observational Medical Outcomes Partnership (OMOP) CDM and the importance in research use of health care data.

After attending this course, you will be able to:

  • Assess challenges and opportunities in using EHR data
  • Cite methods for evaluating data readiness
  • Describe how FAIR principles apply to EHR data

We’ve got the power! Power and sample size calculations for ophthalmology and vision research

8 – Noon

Alison Abraham, PhD, MS, MHS, Colorado School of Public Health; Sue Anschutz Rodgers Eye Center
Gui-shuang Ying, PhD, Perelman School of Medicine, University of Pennsylvania

Power and sample size calculations are critical in the optimal design of studies yet oftentimes perplex even experienced researchers. Few investigators or researchers have a firm grasp on the concept of power, and how it relates to sample size and to hypothesis testing, which can be a helpful tool in efficiently preparing grant applications or planning studies.

This course is designed for clinicians, basic scientists, and vision researchers, to provide them with the tools to better plan studies, communicate with biostatisticians and write approach sections of grants. Instructors will offer guidance on more complicated study designs that require specialized power calculations for more advanced learners. Attendees will examine practical examples of study planning and will receive resources including software code and practical examples in ophthalmic and vision research.

After attending this Education Course, you will be able to:

  • Describe the concepts of power and sample size, and their relation to hypothesis testing
  • Assess what information is needed to perform the calculations and how to determine it in practice, based on the study question
  • Calculate required sample sizes for one- and two-sample hypothesis testing within common study designs (cross-sectional, longitudinal clinical trial or cohort study, case-control study)
  • Use modern computational and graphical tools in assessing power and sample size

The ABCs of randomized controlled trials

1 – 5pm

Tianjing Li, MD, MHS, PhD, Department of Ophthalmology, University of Colorado Anschutz Medical Campus
Penny Asbell, MD, FACS, MBA, FARVO, Department of Ophthalmology, University of Tennessee Health Science Center

Randomized control trials (RCTs) are a key tool in the evaluation of new strategies for the prevention and treatment of eye diseases and conditions since they provide the most evidence on efficacy and safety for making informed decisions on patient care. 

This course introduces eye and vision researchers to the fundamentals of RCTs, and engages them in a discussion regarding key considerations for designing and conducting RCTs. After taking this course participants will gain an understanding of the necessity of RCTs, and insights into how they are designed, initiated, organized, coordinated, monitored, and documented.

After attending this course, you will be able to:

  • Describe RCT design: when and why RCTs are necessary
  • Understand methods to minimize bias in the design and conduct of RCTs
  • Recognize RCT conduct (protocol and data integrity)

Registries in ophthalmic diseases: Their development and use in research

1 – 5pm

Anne Lynch MB, BCH, BAO, MSPH, Department of Ophthalmology, University of Colorado School of Medicine; Colorado School of Public Health
Jennifer Patnaik, PhD, Division of Ophthalmic Epidemiology, Department of Ophthalmology, University of Colorado School of Medicine; Colorado School of Public Health

Over the past few decades there has been an emergence of several large Ophthalmologic registries, notably the IRIS and SOURCE registries, which are national databases that have utilized downloading data from the electronic medical record. Registries can be very useful for quality improvement and supporting evidence-based medicine which are important for clinical practice, however, lack of hands-on experience in handling datasets and insufficient course-work in database management oftentimes leads to inadequate management of these databases.

Attend this course if you are an eye and vision researcher contemplating setting up databases for eye diseases and are interested in hearing “lessons-learned” from setting up registries, specifically: AMD, cataract outcomes, and retinopathy of prematurity, and in other areas of ophthalmology such as: Big data, Inherited retinal disease, Neuro-ophthalmology and multi-site registries.Participants will leave with helpful tools to conduct their research and insights into how to manage data and build registries.

After attending this Education Course, you will be able to:

  • Set up a registry/database and understand the key steps to include in the process
  • Conduct quality research from an existing registry/database
  • Describe the challenges associated with the use of an existing database/registry and specifically with the use of longitudinal data
  • Add modules to an existing database in order to continue to build and advance the utility of the registry


Interpreting genetic tests: The basics of molecular diagnosis through application of results

1 – 5pm

Ramiro Maldonado, MD, Duke University
Robert Hufnagel, MD, PhD, National Institutes of Health (NIH)
Kristy Lee, MS, CGC, University of North Carolina (UNC)

Interpreting genetic testing results is a complex skill that requires an understanding of basic genetic principles, molecular techniques in genetic testing, and clinical implications of genes, variants, and phenotypes. Rapid advancements in genetics and genomics have created expertise gaps among healthcare providers and researchers for interpreting genetic testing for clinical purpose- however, understanding the distinct types of genetic testing and how to discern between pathogenic and benign variation variants is key in disease diagnosis, treatment, and prevention.

Attend this course if you are struggling with the interpretation of genetic testing results. Learn from experts in the field who will cover genetic testing and genetic counseling issues, as well as clinical information about syndromic and non-syndromic inherited ocular diseases Attendees will walk away with practical tips for the genetic diagnosis of inherited ocular diseases, and a comprehension of aspects ranging from ophthalmological evaluation to variant curation, including genetic counseling, research consortia, and public databases.

After attending this Education Course, you will be able to:

  • Describe the molecular basis of genetic testing
  • Classify the most common syndromic and non-syndromic inherited ocular diseases
  • Interpret positive, inconclusive and negative genetic testing results
  • Apply new concepts to utilize public databases for gene and variant curation

ACCME Accreditation with commendation logo

Physician accreditation statement

The Association for Research in Vision and Ophthalmology (ARVO) is accredited by the Accreditation Council for Continuing Medical Education (ACCME) to provide continuing medical education for physicians.

International Attendees: The American Medical Association (AMA) has determined that physicians not licensed in the U.S. who participate in CME activities are eligible for AMA PRA Category 1 Credit™.