Artificial Intelligence In The Treatment Of Glaucoma

Glaucoma, the group of eye diseases is characterized by increased intraocular pressure, optic neuropathy and visual field defect patterns. Early and correct diagnosis of glaucoma can prevent irreversible vision loss and glaucomatous structural damages to the eye. However, greater chances of misdiagnosis by the currently used conventional methods for diagnosis open up ways for more advanced techniques like the use of artificial in- telligence (AI). Artificial intelligence coupled with optical coherence tomography imaging creates an algorithm that can be effectively used to make a model of complex data for detection as well as diagnosis of glaucoma. The Book is an attempt to provide state-of-the-art information on various AI techniques used in the diag- nosis and assessment of glaucoma. The second part of the Book is focused on understanding how the AI along with machine learning (ML) can be potentially used to be subjected for software as a medical device (SaMD) in precise diagnosis or early detection of disease conditions.

This book provides a wide-ranging overview of artificial intelligence (AI), machine learning (ML) and deep learning (DL) algorithms in ophthalmology. Expertly written chapters examine AI in age-related macular degeneration, glaucoma, retinopathy of prematurity and diabetic retinopathy screening. AI perspectives, systems and limitations are all carefully assessed throughout the book as well as the technical aspects of DL systems for retinal diseases including the application of Google DeepMind, the Singapore algorithm, and the Johns Hopkins algorithm. Artificial Intelligence in Ophthalmology meets the need for a resource that reviews the benefits and pitfalls of AI, ML and DL in ophthalmology. Ophthalmologists, optometrists, eye-care workers, neurologists, cardiologists, internal medicine specialists, AI engineers and IT specialists with an interest in how AI can help with early diagnosis and monitoring treatment in ophthalmic patients will find this book to be an indispensable guide to an evolving area of healthcare technology.

Glaucoma is considered as a group of eye diseases characterized by optic neuropathy, a specific pattern of visual field defect and increased intraocular pressure. The rise in intraocular pressure leads to compres-sion of the retina and optic nerve that causes progressive, permanent loss of eyesight (Yadav et al., 2019). Glaucoma is known as the major cause of irreversible blindness worldwide (Gupta and Yadav, 2019). It is estimated that approximately 64.3 million individuals are affected by this disease and this number is expected to reach approximately 112 million by 2040 (Tham et al., 2014). Detection of glaucoma disease in its early stages may prevent blindness (Yadav et al., 2020). Undiagnosed glaucoma cases still account for more than 50 % of the cases worldwide the count of undiagnosed glaucoma cases is around 50 % (Gupta et al., 2016). Diagnosis of glaucoma is related to the assessment of the optic disc and the adjacent retinal nerve fibre layer by a trained specialist. Conventional methods for detection of glaucoma have higher chances of being misdiagnosed. Therefore, there is a need for an automated system which prevents misdiagnosis and makes correct use of the available medical data. As electronic medical records are becoming mainstream along with advancement in digital imaging and data storage, it is more important to appropriately utilize clinical data and digital images at this juncture than ever before.

Glaucoma is an eye disease in which the optic nerve is damaged and can permanently damage vision and lead to blindness if left untreated. This book is a complete guide to the diagnosis and management of glaucoma. Divided into five sections, it begins with an introduction to the disease, continuing step by step through its diagnosis, the different types of glaucoma and treatment options. Authored by specialists renowned in their field based in India and the USA, this manual contains 840 images and illustrations.

The Science of Glaucoma Management: From Translational Research to Next-Generation Clinical Practice bridges the gap between laboratory research and clinicians by bringing the latest promising research directly from researchers to clinicians long before they translate into clinical advances, and often before they are presented at conferences. Organized as a series of clinically relevant topics written by world-leading experts, this book summarizes the current state of laboratory and translational research and draws on the potential implications for day-to-day clinical practice. It offers new insights and mind-opening statements through contributions from some of the most respected glaucoma research groups. The book allows glaucoma specialists to explore novel ways to refine and rethink their practice based on the latest discoveries in basic sciences and breakthrough technologies, and to gain a better understanding on how their specialty is evolving and how research may shape tomorrow’s practice. Presents a detailed report on the latest translational research and breakthroughs that may transform glaucoma practice Overviews the specialty from a scientific and clinical point-of-view Written by world-renowned clinicians and researchers in the field of glaucoma Includes insights, opinions and recommendations from some of the most prominent scientists and ophthalmologists Covers hot topics and the latest technologies in glaucoma, such as minimally invasive glaucoma surgery, telemedicine, gene therapy, neuroprotection and artificial intelligence

The book helps to explore the vast expanse of artificial intelligence-based scientific content that has been published in the last few years. Ophthalmology has recently undergone a silent digital revolution, with machine learning and deep learning algorithms consistently outperforming human graders in studies published across the globe. It is high time that a resource that breaks this information behemoth into easily digestible bits comes to the fore. This book simplifies the complex mechanics of algorithms used in ophthalmology and vision science applications. It also tries to address potential ethical issues with machines entering our clinics and patients’ lives. Overall it is essential reading for ophthalmologists/eye care professionals interested in artificial intelligence and everyone who is looking for a deep dive into the exciting world of digital medicine.

This book provides a wide-ranging overview of artificial intelligence (AI), machine learning (ML) and deep learning (DL) algorithms in ophthalmology. Expertly written chapters examine AI in age-related macular degeneration, glaucoma, retinopathy of prematurity and diabetic retinopathy screening. AI perspectives, systems and limitations are all carefully assessed throughout the book as well as the technical aspects of DL systems for retinal diseases including the application of Google DeepMind, the Singapore algorithm, and the Johns Hopkins algorithm. Artificial Intelligence in Ophthalmology meets the need for a resource that reviews the benefits and pitfalls of AI, ML and DL in ophthalmology. Ophthalmologists, optometrists, eye-care workers, neurologists, cardiologists, internal medicine specialists, AI engineers and IT specialists with an interest in how AI can help with early diagnosis and monitoring treatment in ophthalmic patients will find this book to be an indispensable guide to an evolving area of healthcare technology.

This book reveals the applications of AI and IoT in smart healthcare and medical systems. It provides core principles, algorithms, protocols, emerging trends, security problems, and the latest e-healthcare services findings. The book also provides case studies and discusses how AI and IoT applications such as wireless devices, sensors, and deep learning could play a major role in assisting patients, doctors, and pharmaceutical staff. It focuses on how to use AI and IoT to keep patients safe and healthy and, at the same time, empower physicians to deliver superlative care. This book is written for researchers and practitioners working in the information technology, computer science, and medical equipment manufacturing industry for products and services having basic- and high-level AI and IoT applications. The book is also a useful guide for academic researchers and students.