To apply artificial intelligence (AI) for automated identification of corneal condition and prediction of the likelihood of need for future keratoplasty intervention from optical coherence tomography ...(OCT)-based corneal parameters.
Cohort study.
We collected 12,242 corneal OCT images from 3162 subjects using CASIA OCT Imaging Systems (Tomey, Japan). We included 3318 measurements collected at the baseline visit of each patient. A total of 333 eyes had post-operative penetrating keratoplasty (PKP), lamellar keratoplasty (LKP), deep anterior keratoplasty (DALK), descemet's stripping automated endothelial keratoplasty (DSAEK) or descemet's membrane endothelial keratoplasty (DMEK) intervention.
We developed a pipeline including linear and nonlinear data transformations followed by unsupervised machine learning and applied on corneal parameters from the baseline visit of each patient. Five non-overlapping clusters of eyes were identified. Post hoc analyses revealed that clusters corresponded to different likelihoods of need for future keratoplasty. These clusters on a 2-dimensional map can be used by clinicians and surgeons to identify patients with higher risk of need for future keratoplasty intervention.
The likelihood of the need for future surgery.
The mean age of participants was 69.7 (standard deviation; SD = 16.1) and 59% were female. The normalized likelihood of need for future corneal keratoplasty intervention for eyes mapped onto clusters one to five were 2.2%, 1.0%, 33.1%, 32.7%, and 31.0%, respectively.
The AI system can assist the (cornea) surgeon in identifying those patients who may be at higher risk for future keratoplasty using comprehensive corneal shape, thickness, and elevation parameters. Future research utilizing independent datasets is necessary to validate the proposed system.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Localization and tracking of a mobile node (MN) in non-line-of-sight (NLOS) scenarios, based on time-of-arrival (TOA) measurements, is considered in this paper. We develop a constrained form of a ...square-root unscented Kalman filter (SRUKF), where the sigma points of the unscented transformation are projected onto the feasible region by solving constrained optimization problems. The feasible region is the intersection of several disks formed by the NLOS measurements. We show how we can reduce the size of the optimization problem and formulate it as a convex quadratically constrained quadratic program, which depends on the Cholesky factor of the a posteriori error covariance matrix of the SRUKF. As a result of these modifications, the proposed constrained SRUKF (CSRUKF) is more efficient and has better numerical stability compared to the constrained unscented Kalman filter (UKF). Through simulations, we also show that the CSRUKF achieves a smaller localization error compared to other techniques and that its performance is robust under different NLOS conditions.
The aim of this study was to assess the capabilities of ChatGPT-4.0 and ChatGPT-3.5 for diagnosing corneal eye diseases based on case reports and compare with human experts.
We randomly selected 20 ...cases of corneal diseases including corneal infections, dystrophies, and degenerations from a publicly accessible online database from the University of Iowa. We then input the text of each case description into ChatGPT-4.0 and ChatGPT-3.5 and asked for a provisional diagnosis. We finally evaluated the responses based on the correct diagnoses, compared them with the diagnoses made by 3 corneal specialists (human experts), and evaluated interobserver agreements.
The provisional diagnosis accuracy based on ChatGPT-4.0 was 85% (17 correct of 20 cases), whereas the accuracy of ChatGPT-3.5 was 60% (12 correct cases of 20). The accuracy of 3 corneal specialists compared with ChatGPT-4.0 and ChatGPT-3.5 was 100% (20 cases, P = 0.23, P = 0.0033), 90% (18 cases, P = 0.99, P = 0.6), and 90% (18 cases, P = 0.99, P = 0.6), respectively. The interobserver agreement between ChatGPT-4.0 and ChatGPT-3.5 was 65% (13 cases), whereas the interobserver agreement between ChatGPT-4.0 and 3 corneal specialists was 85% (17 cases), 80% (16 cases), and 75% (15 cases), respectively. However, the interobserver agreement between ChatGPT-3.5 and each of 3 corneal specialists was 60% (12 cases).
The accuracy of ChatGPT-4.0 in diagnosing patients with various corneal conditions was markedly improved than ChatGPT-3.5 and promising for potential clinical integration. A balanced approach that combines artificial intelligence-generated insights with clinical expertise holds a key role for unveiling its full potential in eye care.
To assess the performance of convolutional neural networks (CNNs) for automated diagnosis of dry eye (DE) in patients undergoing video keratoscopy based on single ocular surface video frames.
This ...retrospective cohort study included 244 ocular surface videos from 244 eyes of 244 subjects based on corneal topography. A total of 116 eyes were normal while 128 eyes had DE based on clinical evaluations.
We developed a deep transfer learning model to directly identify DE from ocular surface videos. We evaluated the performance of the CNN model based on objective accuracy metrics. We assessed the clinical relevance of the findings by evaluating class activations maps.
Area under the receiver operating characteristics curve (AUC), accuracy, specificity, and sensitivity.
The AUC of the model for discriminating normal eyes from eyes with DE was 0.98. Network activation maps suggested that the lower paracentral cornea was the most important region for detection of DE by the CNN model.
Deep transfer learning achieved a high diagnostic accuracy in detecting DE based on non-invasive ocular surface videos at levels that may prove useful in clinical practice.
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GEOZS, IJS, IMTLJ, KILJ, KISLJ, NLZOH, NUK, OILJ, PNG, SAZU, SBCE, SBJE, UILJ, UL, UM, UPCLJ, UPUK, ZAGLJ, ZRSKP
Purpose: Clinical diagnosis of dry eye disease is based on a subjective Ocular Surface Disease Index questionnaire or various objective tests, however, these diagnostic methods have several ...limitations. Methods: We conducted a comprehensive review of articles discussing various applications of artificial intelligence (AI) models in the diagnosis of the dry eye disease by searching PubMed, Web of Science, Scopus, and Google Scholar databases up to December 2022. We initially extracted 2838 articles, and after removing duplicates and applying inclusion and exclusion criteria based on title and abstract, we selected 47 eligible full-text articles. We ultimately selected 17 articles for the meta-analysis after applying inclusion and exclusion criteria on the full-text articles. We used the Standards for Reporting of Diagnostic Accuracy Studies to evaluate the quality of the methodologies used in the included studies. The performance criteria for measuring the effectiveness of AI models included area under the receiver operating characteristic curve, sensitivity, specificity, and accuracy. We calculated the pooled estimate of accuracy using the random-effects model. Results: The meta-analysis showed that pooled estimate of accuracy was 91.91% (95% confidence interval: 87.46–95.49) for all studies. The mean (±SD) of area under the receiver operating characteristic curve, sensitivity, and specificity were 94.1 (±5.14), 89.58 (±6.13), and 92.62 (±6.61), respectively. Conclusions: This study revealed that AI models are more accurate in diagnosing dry eye disease based on some imaging modalities and suggested that AI models are promising in augmenting dry eye clinics to assist physicians in diagnosis of this ocular surface condition.
Single-cell RNA sequencing (scRNA-seq) provides a high throughput, quantitative and unbiased framework for scientists in many research fields to identify and characterize cell types within ...heterogeneous cell populations from various tissues. However, scRNA-seq based identification of discrete cell-types is still labor intensive and depends on prior molecular knowledge. Artificial intelligence has provided faster, more accurate, and user-friendly approaches for cell-type identification. In this review, we discuss recent advances in cell-type identification methods using artificial intelligence techniques based on single-cell and single-nucleus RNA sequencing data in vision science. The main purpose of this review paper is to assist vision scientists not only to select suitable datasets for their problems, but also to be aware of the appropriate computational tools to perform their analysis. Developing novel methods for scRNA-seq data analysis remains to be addressed in future studies.
The change in glaucoma surgical volumes due to the coronavirus disease 2019 pandemic was not uniform across procedure types and was unequal between rural and urban practice locations.
To quantify the ...impact of the coronavirus disease 2019 pandemic on surgical volumes performed by fellowship-trained glaucoma subspecialists.
This retrospective cohort analysis of the Centers for Medicare and Medicaid Services Medicare Public Use File extracted all glaucoma surgeries, including microinvasive glaucoma surgeries (MIGSs), trabeculectomy, goniotomy, lasers, and cataract surgery, performed by fellowship-trained glaucoma surgeons in rural and urban areas between 2016 and 2020. Predicted estimates of 2020 surgical volumes were created utilizing linear squares regression. Percentage change between predicted and observed 2020 surgical volume estimates was analyzed. Statistical significance was achieved at P <0.05.
In 2020, fellowship-trained glaucoma surgeons operated mostly in urban areas (N = 810, 95%). A 29% and 31% decrease in predicted cataract surgery volumes in urban and rural areas, respectively, was observed. Glaucoma surgeries experienced a 36% decrease from predicted estimates (N = 56,781). MIGS experienced an 86% and 75% decrease in rural and urban areas, respectively. Trabeculectomy in rural areas experienced a 16% increase relative to predicted estimates while urban areas experienced a decrease of 3% ( P > 0.05). The number of goniotomies decreased by 10% more in rural areas than in urban areas (-22% and -12%, respectively). Laser procedures decreased by 8% more in urban areas than in rural areas (-18% and -10%, respectively).
Among glaucoma-trained surgeons, glaucoma surgeries experienced a greater volume loss than cataract surgeries. In urban US areas, relative reductions in MIGS and goniotomy volumes in urban areas may have been compensated by greater laser and trabeculectomy volumes. Trabeculectomies in rural areas were the only group exceeding predicted estimates. Glaucoma subspecialists may utilize these findings when planning for future events and in overcoming any remaining unmet need in terms of glaucoma care.
Irregular visual field test frequency at relatively short intervals initially and longer intervals later on in the disease provided acceptable results in detecting glaucoma progression.
It is ...challenging to maintain a balance between the frequency of visual field testing and the long-term costs that may result from insufficient treatment of glaucoma patients. This study aims to simulate real-world circumstances of visual field data to determine the optimum follow-up scheme for the timely detection of glaucoma progression using a linear mixed effects model (LMM).
An LMM with random intercept and slope was used to simulate the series of mean deviation sensitivities over time. A cohort study including 277 glaucoma eyes that were followed for 9.0±1.2 years was used to derive residuals. Data were generated from patients with early-stage glaucoma having various regular and irregular follow-up scenarios and different rates of visual field loss. For each condition, 10,000 series of eyes were simulated, and one confirmatory test was conducted to identify progression.
By doing one confirmatory test, the percentage of incorrect progression detection decreased considerably. The time to detect progression was shorter for eyes with an evenly spaced 4-monthly schedule, particularly in the first 2 years. From then onward, results from twice-a-year testing were similar to results from examinations scheduled 3 times per year.
Irregular visual field test frequency at relatively short intervals initially and longer intervals later on in the disease provided acceptable results in detecting glaucoma progression. This approach could be considered for improving glaucoma monitoring. Moreover, simulating data using LMM may provide a better estimate of the disease progression time.
This paper provides a systematic survey of artificial intelligence (AI) models that have been proposed over the past decade to screen retinal diseases, which can cause severe visual impairments or ...even blindness. The paper covers both the clinical and technical perspectives of using AI models in hosipitals to aid ophthalmologists in promptly identifying retinal diseases in their early stages. Moreover, this paper also evaluates various methods for identifying structural abnormalities and diagnosing retinal diseases, and it identifies future research directions based on a critical analysis of the existing literature. This comprehensive study, which reviews both the conventional and state-of-the-art methods to screen retinopathy across different modalities, is unique in its scope. Additionally, this paper serves as a helpful guide for researchers who want to work in the field of retinal image analysis in the future.
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EMUNI, NUK, SBMB, SBNM, UL, UM, UPUK
Pediculus humanus capitis is a major obligate and district ecto-parasite of human which is distributed in different parts of the world and is under several research projects for population management ...and molecular analysis. In this study, one hundred and seventy head lice were collected from school girls at different high schools in five cities in south east of Tehran Province (Iran). They were analyzed using molecular methods for genotyping lice, Cytochrome Oxidase I (COI), for the first time in Iran. The phylogenetic analysis of the concentrated sequences of the head lice populations showed high divergence among the population collected from different cities. However, samples belonged to each city showed high homology with some of the GenBank sequences.
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