Current roles of artificial intelligence in ophthalmology

Artificial intelligence (AI) studies are increasingly reporting successful results in the diagnosis and prognosis prediction of ophthalmological diseases as well as systemic disorders. The goal of this review is to detail how AI can be utilized in making diagnostic predictions to enhance the clinical setting. It is crucial to keep improving methods that emphasize clarity in AI models. This makes it possible to evaluate the information obtained from ocular imaging and easily incorporate it into therapeutic decision-making procedures. This will contribute to the wider acceptance and adoption of AI-based ocular imaging in healthcare settings combining advanced machine learning and deep learning techniques with new developments. Multiple studies were reviewed and evaluated, including AI-based algorithms, retinal images, fundus and optic nerve head (ONH) photographs, and extensive expert reviews. In these studies, carried out in various countries and laboratories of the world, it is seen those complex diagnoses, which can be detected systemic diseases from ophthalmological images, can be made much faster and with higher predictability, accuracy, sensitivity, and specificity, in addition to ophthalmological diseases, by comparing large numbers of images and teaching them to the computer. It is now clear that it can be taken advantage of AI to achieve diagnostic certainty. Collaboration between the fields of medicine and engineering foresees promising advances in improving the predictive accuracy and precision of future medical diagnoses achieved by training machines with this information. However, it is important to keep in mind that each new development requires new additions or updates to various social, psychological, ethical, and legal regulations

Lessons Learned from the Point-of-Care Use of a Facial Analysis Technology

Purpose We aimed to evaluate the utility of facial analysis technology for genetic diagnoses in a typical pediatric genetic clinic. Methods A retrospective review identified children (aged <18 years) who had not previously received a definitive genetic diagnosis and underwent a comprehensive genetic evaluation. Their photographs and relevant clinical non-facial features were uploaded to the CLINIC application of the Face2Gene web interface, and the resulting analysis was accessed and correlated to the molecular diagnosis. Results Of the 23 children included, the overall diagnostic yield in this study was 60.9% (14/23). In total, 64.3% of patients had the correct condition suggested in the top 10 differential diagnoses. The gestalt similarity was only 55.6%, but the phenotypic features added by the clinician showed a similarity of more than the medium level in all patients. Conclusion Our data underscore the usefulness of facial analysis technology as an auxiliary point-of-care tool in pediatric genetic clinics, and we also present some considerations to increase accuracy

Diagnosis of Dentofacial Anomolies

It is very challenging to understand and analyse anomalies of dentofacial region. Diagnosis plays a very important role in the further treatment of any condition related to orofacial anomalies. Diagnosis includes taking complete history and required investigations and conclusion. History gives more information towards clinical path, and investigation will lay more emphasis on conclusion. Anomalies involving dentofacial region may be related to tooth, maxilla, mandible, soft tissue anomalies and syndromic conditions. Dentofacial anomolies not only involve the dentofascial region but can spread to various other vital organs, so sometimes correlating the systemic problem will be of prime importance. When the other body is involved, the varied presentation will be a challenge in diagnosis. Multiple organs should be investigated for an diagnostic conclusion. Brining diagnostic information of anomalies is the aim of the chapter. Here, we cover various clinical features, diagnostic criteria, and investigation protocols of dentofacial anomalies

The role of epigenetic factors in the pathogenesis of familial X-linked mental retardation (XLMR)

Mental retardation (MR) is a handicap with severe implications not only for thosethat suffer from this disability, but also for their families, society and the welfaresystems which support them. A large proportion of these individuals are afflictedwith the X-linked form of the condition. To date a total of 87 genes have beenimplicated in the pathogenesis of X-linked mental retardation (XLMR)

What volume increase is needed for the management of raised intracranial pressure in children with craniosynostosis?

Craniosynostosis describes a fusion of one or more sutures in the skull. It can occur in isolation or as part of a syndrome. In either setting, it is a condition which may lead to raised intracranial pressure. The exact cause of raised intracranial pressure in craniosynostosis is unknown. It may be due to; a volume mismatch between the intracranial contents and their containing cavity, venous hypertension, hydrocephalus or airway obstruction, which is often a sequela of an associated syndrome. At Great Ormond Street Hospital, after hydrocephalus and airway obstruction have been treated, the next surgical treatment of choice is cranial vault expansion. This expansion has been shown to reduce intracranial pressure, interestingly despite its success, the reasons behind its benefits are not fully understood. Using reconstructed 3-dimensional imaging, accurate measurement of cranial volumes can now be achieved. The aim of this project is to use the advances in 3-dimensional imaging and image processing to provide novel information on the volume changes that occur following cranial vault expansion. This information will be combined with clinical metrics to create a greater understanding of the causes of raised intracranial pressure in craniosynostosis, why cranial vault expansion treats them and whether there is an optimal volume expansion

Craniofacial anomalies in children: diagnosis, management, outcomes

The causes of facial anomalies in children may be congenital, traumatic, oncologic (or in some cases) remain unknown. Many of these craniofacial conditions warrant further elucidation of the clinical features, to allow accurate diagnosis and targeted management. Long term outcome studies of children with craniofacial anomalies, are essential to evaluate treatment protocols and to aid those who treat affected children to improve and advance their standards of care. These objectives require clinicians, along with their scientific colleagues to strive to increase their recognition of morphological anomalies and understanding of the underlying disease processes, so as to develop specific management strategies. The aim is to find new answers to improve the quality of life of affected children throughout the world. This collection of papers has been prompted by a desire to contribute towards that goal

Exome Sequencing in X Linked Intellectual Disability : A novel mutation in the CUL4B gene underlying Cabezas syndrome

In this study we have applied exome sequencing of the X-chromosome in order to identify a mutation in a Finnish family with X–Linked Intellectual Disability (XLID). We identified a novel mutation in the Cullin 4B gene (CUL4B) that has previously shown to cause Cabezas syndrome. The mutation was identified using Agilent array that covers 93% of the coding region of chromosome X. The mutation is located in exon 20 resulting in premature stop codon in exon 21 where aspartic acid is changed to a premature stop codon D806X. Here we present a detailed clinical phenotype of the three affected brothers. CUL4B is a ubiquitin E3 ligase subunit implicated in the regulation of several biological processes, and CUL4B is the first XLID gene that encodes an E3 ubiquitin ligase. Our findings elucidate the functional significance of CUL4B in human cognition and in other aspects of human development

SUPPORT for ME: Substance Use Disorder Prevalence and Treatment Capacity Assessment

The aim of this report was to understand the sociodemographic and geographic distribution of substance use disorder (SUD) prevalence in Maine, through a claims-based analysis which assessed current statewide capacity to address SUD by examining current SUD treatment and recovery infrastructure, service utilization patterns, and geographic distribution of services and usage throughout the state to identify any gaps in treatment and recovery capacity. The authors would like to note that this report was completed during the planning phase of the SUPPORT for ME project, which was funded by the Centers for Medicare & Medicaid Services (CMS) via the SUPPORT Act passed by Congress in 2018. This assessment utilized numerous data sources, one of which was Medicaid claims data from Maine’s Office of MaineCare Services. This was the first attempt to utilize claims data to estimate prevalence and capacity related to SUD in the State. In future work, the authors aim to have more engagement with clinical providers and data stakeholders which may lead to alterations or updates to the methodologies utilized to produce this report. FMI: Please contact M.Lindsey Smith, PhD at [email protected]