Revolutionizing Ophthalmology : the Integration of Artificial Intelligence Algorithms / Espaillat Espaillat.

Format:

Book

Author/Creator:

Espaillat, Espaillat, author.

Series:

Eye and vision research developments series.

Eye and Vision Research Developments Series

Language:

English

Subjects (All):

Ophthalmology--Data processing.

Ophthalmology.

Artificial intelligence--Medical applications.

Artificial intelligence.

Physical Description:

1 online resource (175 pages)

Edition:

First edition.

Place of Publication:

New York, NY : Nova Science Publishers, Inc., [2024]

Summary:

"This book delves into the cutting-edge advancements of AI in ophthalmology, covering a wide range of topics from glaucoma detection to oculomics, retinal diseases, cataract, cornea, refractive surgery, and anterior segment diseases. This comprehensive book explores the intersection of artificial intelligence and eye care, offering insights into how AI is revolutionizing the diagnosis and treatment of various eye conditions. Additionally, the book delves into important ethical considerations surrounding AI in ophthalmology and provides in-depth discussions on AI performance metrics. With engaging content and expert analysis, this book is essential reading for anyone interested in the transformative potential of AI in the field of eye care. Explore the fascinating world of AI in ophthalmology and discover how groundbreaking technologies are reshaping the future of healthcare"-- Provided by publisher.

Contents:

Intro

Contents

Preface

Acknowledgments

Chapter 1

Fundamentals of Artificial Intelligence

Introduction

Understanding Artificial Intelligence

Demystifying the AI Training Process and Learning Models

Applications in Healthcare

Addressing Ethical Considerations

Conclusion

References

Chapter 2

Exploring Artificial Intelligence System Algorithms in Ophthalmology: Innovation and Experimentation

Convolutional Neural Networks (CNNs)

Recurrent Neural Networks (RNNs)

Support Vector Machines (SVMs)

Generative Adversarial Networks (GANs)

Reinforcement Learning

Linear and Nonlinear Regression

Logistic Regression

Naive Bayes

K-Means Clustering

Decision Trees

Key Differences between a DT and a Random Forest (RF) AI Algorithm

K-Nearest Neighbor (KNN) Algorithm

Chapter 3

Enhancing Understanding of Performance Evaluation Metrics for Artificial Intelligence Algorithms

Importance of Performance Evaluation Metrics

Standard Performance Evaluation Metrics for AI Algorithms

Overfitting and Underfitting Machine Learning Models

Selecting Performance Evaluation Metrics

Chapter 4

Evaluating Artificial Intelligence Systems in Ophthalmology and Addressing Implementation Ethical Considerations

Exploring Promising Frontiers

Ethical Considerations

Mitigating Ethical Risks

Chapter 5

Revolutionizing Medicine: How Artificial Intelligence is Transforming the Diagnosis and Treatment of Orbital and Eyelid Diseases

Diagnostic Capabilities

Surgical Planning and Intervention

Training and Research Advancements

Revolutionizing Orbital and Lacrimal Disease Management with AI Technology.

Future Implications and Considerations

Chapter 6

Advancements in Artificial Intelligence: Transforming the Diagnosis and Treatment of Cornea Diseases and Refractive Surgery

Diagnostic and Surgical AI applications of Conjunctiva and Cornea Diseases

Chapter 7

Using Artificial Intelligence to Revolutionize Diagnosis and Treatment of Cataracts and IOL Calculations

AI in Cataract Diagnosis

AI in IOL Calculation and Cataract Surgery Planning

Intraoperative and Postoperative AI Applications during Cataract Surgery

Future Perspectives and Challenges

Chapter 8

Artificial Intelligence for Enhanced Diagnosis and Treatment of Glaucoma

AI in Glaucoma Diagnosis

AI: ML Glaucoma Detection Models

Supervised Glaucoma ML Detection Models

Unsupervised Glaucoma ML Detection Models

Deep Learning Glaucoma Detection Models

AI in Detecting Glaucoma Progression

AI-Assisted Treatment Strategies

Chapter 9

Enhancing Diagnosis and Treatment of Retinal Diseases through Artificial Intelligence

AI in Retinal Disease Diagnosis

Diabetic Retinopathy

AI DR Screening Software Models

Age-Related Macular Degeneration

Retinopathy of Prematurity

Inherited Retinal Diseases

Challenges and Future Directions

Chapter 10

Ocular Biomarkers for Enhanced Systemic Risk Assessment through Artificial Intelligence

Advancements in AI for Extracting Retinal Microvascular Parameters

Utilizing AI-Generated Microvascular Parameters for Cardiovascular Risk Evaluation

About the Author

Index

Blank Page.

Notes:

Description based on publisher supplied metadata and other sources.

Description based on print version record.

Includes bibliographical references and index.

ISBN:

9798895300763

OCLC:

1455129246