Use of artificial intelligence (AI) is a burgeoning field in otolaryngology and the communication sciences. A virtual symposium on the topic was convened from Duke University on October 26, 2020, and was attended by more than 170 participants worldwide. This review presents summaries of all but one of the talks presented during the symposium; recordings of all the talks, along with the discussions for the talks, are available at https://www.youtube.com/watch?v=ktfewrXvEFg and https://www.youtube.com/watch?v=-gQ5qX2v3rg . Each of the summaries is about 2500 words in length and each summary includes two figures. This level of detail far exceeds the brief summaries presented in traditional reviews and thus provides a more-informed glimpse into the power and diversity of current AI applications in otolaryngology and the communication sciences and how to harness that power for future applications. 

Harnessing the Power of Artificial Intelligence in Otolaryngology and the Communication Sciences

This study was done to explore the utility of artificial intelligence (AI) and machine learning in the diagnosis and grouping of intraocular retinoblastoma (iRB).It was a retrospective observational study using AI and Machine learning, Computer Vision (OpenCV).Of 771 fundus images of 109 eyes, 181 images had no tumor and 590 images displayed iRB based on review by two independent ocular oncologists (with an interobserver variability of <1%). The sensitivity, specificity, positive predictive value, and negative predictive value of the trained AI model were 85%, 99%, 99.6%, and 67%, respectively. Of 109 eyes, the sensitivity, specificity, positive predictive value, and negative predictive value for detection of RB by AI model were 96%, 94%, 97%, and 91%, respectively. Of these, the eyes were normal (n = 31) or belonged to groupA (n=1), B (n=22), C (n=8), D (n=23),and E (n=24) RB based on review by two independent ocular oncologists (with an interobserver variability of 0%). The sensitivity, specificity, positive predictive value, and negative predictive value of the trained AI model were 100%, 100%, 100%, and 100% for group A; 82%, 20 21 98%, 90%, and 96% for group B; 63%, 99%, 83%, and 97% for group C; 78%, 98%, 90%, and 94% for group D, and 92%, 91%, 73%, and 98% for group E, respectively.Based on our study, we conclude that the AI model for iRB is highly sensitive in the detection of RB with high specificity for the classification of iRB. 

Artificial intelligence and machine learning in ocular oncology: Retinoblastoma

Artificial intelligence is a multidisciplinary and collaborative science, the ability of deep learning for image feature extraction and processing gives it a unique advantage in dealing with problems in ophthalmology. The deep learning system can assist ophthalmologists in diagnosing characteristic fundus lesions in glaucoma, such as retinal nerve fiber layer defects, optic nerve head damage, optic disc hemorrhage, etc. Early detection of these lesions can help delay structural damage, protect visual function, and reduce visual field damage. The development of deep learning led to the emergence of deep convolutional neural networks, which are pushing the integration of artificial intelligence with testing devices such as visual field meters, fundus imaging and optical coherence tomography to drive more rapid advances in clinical glaucoma diagnosis and prediction techniques. This article details advances in artificial intelligence combined with visual field, fundus photography, and optical coherence tomography in the field of glaucoma diagnosis and prediction, some of which are familiar and some not widely known. Then it further explores the challenges at this stage and the prospects for future clinical applications. In the future, the deep cooperation between artificial intelligence and medical technology will make the datasets and clinical application rules more standardized, and glaucoma diagnosis and prediction tools will be simplified in a single direction, which will benefit multiple ethnic groups.

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The application of artificial intelligence in glaucoma diagnosis and prediction

Artificial intelligence applications and cataract management: A systematic review.

Artificial intelligence in retinal image analysis: Development, advances, and challenges.

Artificial Intelligence: the unstoppable revolution in ophthalmology.

We all live in a hybrid world of both online and offline experiences. Especially since the start of the COVID-19 pandemic in 2020, we are now more connected than ever. The aim of the metaverse, which is made up of the terms “meta” which means “beyond”, and “verse” which comes from the word “universe”, is to simplify these means of communication by minimising inconveniences and improving experiences in the physical world. Simultaneously, the multitude of data that is part of our lives is moving us towards an irreversibly digital future. Data are the raw material that feeds machine learning and artificial intelligence algorithms, which allow us to make decisions based on the analysis of historical events, and to predict future behaviour. In addition to this, 6G, the sixth generation of hyper-speed mobile connectivity, together with new models of cloud computing, will allow for disruptive developments economy, machine learning, social analytics, blockchain, and health, among many others. Digital transformation is already part of our lives, and the health sector and the therapeutic field of ophthalmology are no exceptions. New technologies based on metaverse are emerging to improve medical education and training as well as processes and procedures in all stages of patient journey from diagnosis, monitoring, surgical procedures and adherence to medical treatment. We are facing a “virtual life” that is evolving amidst social and ethical challenges. Will the metaverse really allow the virtual and physical space to come together? Will it improve patient healthcare in the field of ophthalmology?

/pdf/metaverse-in-ophthalmology-the-convergence-of-virtual-and-1l7f11bv.pdf

Metaverse in Ophthalmology: The Convergence of Virtual and Physical Space in Eye Care

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Artificial Intelligence: the unstoppable revolution in ophthalmology.

Metaverse in Ophthalmology: The Convergence of Virtual and Physical Space in Eye Care