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Data Mining and Machine Learning (DM2L)

Data Mining and Machine Learning

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Contact Us

Investigator / Contact Person Siamak Yousefi, Ph.D., FARVO
Office 305-243-5411
Email siamak.yousefi@miami.edu

Cornea Research Network

A Multimodal, AI-Driven Platform for Corneal Disease Characterization and Diagnostics

Mission

The Cornea Research Network (CRN) is a collaborative initiative focused on advancing corneal disease research through large-scale, multimodal data integration and artificial intelligence. CRN aims to enable early detection, objective staging, progression prediction, and personalized management of corneal disorders.


Scientific Scope

CRN addresses a broad range of corneal diseases, including:

  • Keratoconus and ectatic disorders
  • Post-refractive surgery ectasia
  • Corneal dystrophies and degenerations
  • Infectious and inflammatory keratitis
  • Corneal scarring and transplantation outcomes

Key objectives include:

  • Early detection of subclinical and forme fruste disease
  • Quantitative staging and risk stratification
  • Prediction of progression and treatment response
  • Decision support for intervention timing and modality

Current Collaborators

University of Miami, Miller School of Medicine / Bascom Palmer Eye Institute

  • Amr Saad Mohamed Elsawy
  • Shelby Solomon Darnell

University of Baghdad, College of Education for Pure Sciences (KECBU), Iraq

  • Ali Altimemy

University of Brest, France

  • Mostafa Elhabib Daho

University of Dubai, United Arab Emirates

  • Marwa Chendeb
  • Noor Aburaed (first name not specified)

Morgan State University, United States

  • Shiva Mehravaran

University of Maryland School of Medicine, United States

  • Waqas Munir

Refractive Surgery Center (Refraktives Zentrum), Germany

  • Suphi Taneri

Jichi Medical University, Japan

  • Hidenori Takahashi

University of Sao Paolo, Brazil

  • Rossen Hazarbassanov

Asuit University, Egypt

  • Hazem Abdelmotaal

Other Collaborators

  • Amir Rahdar
  • Alexandru Lavric

Datasets and Modalities

Imaging

  • Corneal tomography (Pentacam, Orbscan)
  • Corneal topography
  • Anterior segment OCT
  • Biomechanical imaging (e.g., Corvis ST dynamic deformation)
  • Slit-lamp photography

Clinical and Surgical Data

  • Refraction and visual acuity
  • Contact lens and refractive surgery history
  • Cross-linking and surgical interventions
  • Postoperative and longitudinal outcomes

Biomechanics and Biophysics

  • Corneal stiffness metrics
  • Dynamic deformation parameters
  • Structure–biomechanics relationships

Genetics (where available)

  • Keratoconus-associated variants
  • Polygenic risk profiling
  • Gene–environment interaction analysis

AI and Analytics Framework

CRN leverages advanced AI methodologies to:

  • Detect early ectatic changes beyond human recognition
  • Integrate structure, shape, and biomechanics
  • Predict individual risk of progression
  • Guide personalized treatment pathways
  • Enable explainable and clinically interpretable models

Collaborative Model

CRN is structured as a multi-institutional, open research platform, enabling:

  • Standardized imaging and annotation protocols
  • Multi-site validation of AI models
  • Prospective and retrospective studies
  • Academic–industry collaboration

Partners include:

  • Cornea and refractive surgery centers
  • Biomedical engineers and AI scientists
  • Imaging and device manufacturers

Impact

CRN seeks to:

  • Redefine early diagnosis of corneal disease
  • Reduce preventable vision loss
  • Improve surgical planning and outcomes
  • Accelerate translation of AI into corneal practice
  • Establish globally validated corneal biomarkers

Get Involved

CRN invites:

  • Clinical and surgical cornea centers
  • Data scientists and engineers
  • Imaging technology partners
  • Trainees and collaborators worldwide

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