56 research outputs found
A Structural and Functional Analysis of Human Brain MRI with Attention Deficit Hyperactivity Disorder
No full textAttention Deficit Hyperactivity Disorder (ADHD) affects 5-10% of children worldwide. Its effects are mainly behavioral, manifesting in symptoms such as inattention, hyperactivity, and impulsivity. If not monitored and treated, ADHD may adversely affect a child\u27s health, education, and social life. Furthermore, the neurological disorder is currently diagnosed through interviews and opinions of teachers, parents, and physicians. Because this is a subjective method of identifying ADHD, it is easily prone to error and misdiagnosis. Therefore, there is a clear need to develop an objective diagnostic method for ADHD.
The focus of this study is to explore the use of machine language classifiers on information from the brain MRI and fMRI of both ADHD and non-ADHD subjects. The imaging data are preprocessed to remove any intra-subject and inter-subject variation. For both MRI and fMRI, similar preprocessing stages are performed, including normalization, skull stripping, realignment, smoothing, and co-registration. The next step is to extract features from the data. For MRI, anatomical features such as cortical thickness, surface area, volume, and intensity are obtained. For fMRI, region of interest (ROI) correlation coefficients between 116 cortical structures are determined.
A large number of image features are collected, yet many of them may include redundant and useless information. Therefore, the features used for training and testing the classifiers are selected in two separate ways, feature ranking and stability selection, and their results are compared. Once the best features from MRI and fMRI are determined, the following classifiers are trained and tested through leave-one-out cross validation, experimenting with varying feature numbers, for each imaging modality and feature selection method: support vector machine, support vector regression, random forest, and elastic net.
Thus, there are four experiments (MRI-rank, MRI-stability, fMRI-rank, fMRI-stability) with four classifiers in each for a total of 16 classifiers trained per each feature count attempted. The results of each classifier are the decisions of each subject, ADHD or non-ADHD. Finally, a classifier decision ensemble is created through the combination of the outputs of the best classifiers in a majority voting method that includes results of both the MRI and fMRI classifiers and keeps both feature selection results independent.
The results suggest that ADHD is more easily identified through fMRI because the classification accuracies are a lot higher using fMRI data rather than MRI data. Furthermore, significant activity correlation differences exist between the brain\u27s frontal lobe and cerebellum and also the left and right hemispheres among ADHD and non-ADHD subjects. When including MRI decisions with fMRI in the classifier ensemble, performance is boosted to a high ADHD detection accuracy of 96.2%, suggesting that MRI information assists in validating fMRI classification decisions.
This study is an important step towards the development of an automatic and objective method for ADHD diagnosis. While more work is needed to externally validate and improve the classification accuracy, new applications of current methods with promising results are introduced here
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Association Between Preresidency Peer-reviewed Publications and Future Academic Productivity or Career Choice Among Ophthalmology Residency Applicants
No full textImportance Ophthalmology-residency selection committees require robust metrics to review applicants. Participation in research activities is a core component of the application process for its perceived association with future academic productivity.Objective To evaluate the correlation between the number of preresidency peer-reviewed publications (PPPs) and subsequent peer-reviewed publications or career choices of ophthalmology residency graduates.Design, Setting, and Participants In this cross-sectional study, names of ophthalmology residency graduates were obtained. PubMed-indexed publication records were generated and publications were categorized as preresidency, intraresidency, and postresidency. First author and journal publications with an impact factor (IF) score of 3 or more were recorded. Current academic and community-based career statuses were designated. Names were obtained from cohort and alumni lists on residency program websites or by emailing program directors. Participants included US Accreditation Council for Graduate Medical Education-accredited ophthalmology residency graduates from 2013 to 2016.Main Outcomes and Measures The primary outcome measure was association of PPPs with later publications, first authorship, and journal publications with an IF score of 3 or more. The secondary outcome measure was difference in characteristics associated with academic vs community-based ophthalmologist.Results A total of 964 ophthalmologists (52% of graduates) were studied and most (85.5%) had PubMed-indexed publications. First authorship (rho = 0.71; 95% CI, 0.67-0.74; P < .001) had a strong positive correlation with intraresidency publications, while journal publications with an IF score of 3 or more (rho = 0.56; 95% CI, 0.51-0.60; P < .001) and PPPs (rho = 0.38; 95% CI, 0.32-0.43; P < .001) had moderate and weak positive correlations, respectively. For postresidency publications, journal publications with an IF score of 3 or more (rho = 0.86; 95% CI, 0.84-0.87; P < .001) had the strongest positive correlation followed by first authorship (rho = 0.77; 95% CI, 0.74-0.79; P < .001) and PPPs (rho = 0.26; 95% CI, 0.20-0.31; P < .001). Preresidency (t = 3.3; P = .001), intraresidency (t = 4.1; P < .001), postresidency (t = 7.5; P < .001), first author (t = 6.6; P < .001), and journal publications with an IF score of 3 or more (t = 5.9; P < .001) were greater for academic ophthalmologists compared with community-based ophthalmologists.Conclusions and Relevance Preresidency publication history is at least weakly correlated with future publications or work in an academic setting among ophthalmologists. Multiple factors associated with academic productivity were evaluated; however, adjustment for multiple analyses was not done and further testing is required to prove whether these factors are predictive
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Gender representation in pediatric ophthalmology: an analysis of trends over a decade
No full textTo assess trends in gender representation in pediatric ophthalmology.
In this retrospective study, the names of oral and poster presenters at the American Association for Pediatric Ophthalmology and Strabismus (AAPOS) annual meetings and the first and last authors of articles published in Journal of AAPOS (J AAPOS) from 2011 to 2019 were recorded. The gender of presenters and authors was determined with the aid of an online gender tool in conjunction with a comprehensive internet search.
A total of 2,633 presentations, and 2,777 authors were included. Over the study period, female representation in both conferences and journal authorship increased (P > 0.01 and P = 0.01 resp.). Overall, women comprised 44% of oral presentations and 57% of poster presentations at the annual meetings. Of publications in J AAPOS, women comprised 47% of first authors and 38% of last authors. The gender of the first author did not correlate with the gender of the last author (P = 0.9). Conference roles that had the greatest gender disparities were named lecture speakers (27% female vs 73% male [P = 0.01]) and program committee members (34% female vs 66% male [P > 0.01]).
Over the last decade, there has been an increase in representation of women at both AAPOS conferences and authorship in J AAPOS. Gender disparities persist in higher-visibility positions
Microbiome and immune-mediated dry eye: a review
No full textIn this review, we aim to summarise key articles that explore relationships between the gut and ocular surface microbiomes (OSMs) and immune-mediated dry eye. The gut microbiome has been linked to the immune system by way of stimulating or mitigating a proinflammatory or anti-inflammatory lymphocyte response, which may play a role in the severity of autoimmune diseases. Although the ‘normal’ gut microbiome varies among individuals and demographics, certain autoimmune diseases have been associated with characteristic gut microbiome changes. Less information is available on relationships between the OSM and dry eye. However, microbiome manipulation in multiple compartments has emerged as a therapeutic strategy, via diet, prebiotics and probiotics and faecal microbial transplant, in individuals with various autoimmune diseases, including immune-mediated dry eye
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The Microbiome and Ocular Surface Disease
No full textThe human body lives in a symbiotic relationship with the bacteria, viruses, fungi, and protozoa that make up the microbiome. In this review, we discuss the compositions of the gut and ocular surface microbiomes in relationship to health and disease.The gut microbiome is dominated by Firmicutes, whereas the ocular surface is dominated by Proteobacteria. The compositions of the microbiome are similar between individuals at the phyla level, but differ at the genus level. Alterations in the microbiome have been associated with disease. For example, ocular diseases such as uveitis, dry eye, and keratitis have been associated with gut dysbiosis. In addition, ocular surface dysbiosis has been reported in diseases including dry eye, blepharitis, keratitis, and diabetic retinopathy.Compositions of the gut and ocular surface microbiomes have been found to differ in disease states compared with controls. Further understanding of dysbiosis specific to a disease is needed to target these surfaces for therapeutic strategies
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Surgeon demographic and surgical volume trends in adult strabismus surgery in the United States
No full textTo explore the influence of career stage, gender, and age on procedural trends of surgeons performing strabismus surgery.
Data on ophthalmologists who performed strabismus surgery and on the Medicare beneficiaries who underwent surgery between 2012 and 2017 was retrieved from Medicare Provider Utilization and Payment Data.
A total of 133 strabismus surgeons (78.9% male and 21.1% female) were reimbursed by Centers for Medicare and Medicaid Services for 10,598 strabismus procedures during the study period. The overall number of strabismus surgeries increased (P = 0.039) over time. Most surgeons were 50-59 years of age (n = 45 [33.8%]), with an average age of 54.5 ± 9.5 years. The number of services per physician did not differ by gender (85 ± 97 procedures/male surgeon and 60 ± 149 procedures/female surgeon [P = 0.13]). There was no difference in the gender proportion of physicians, with 0-9 post-fellowship years of experience (P = 0.32), but there were significantly more men with 10-19 (P = 0.003), 20-29 (P < 0.001), and 30-39 (P < 0.001) years of post-fellowship experience. There was no difference in the number of procedures performed between women and men 30-39 (P = 0.83) or 60-69 (P = 0.48) years of age; however, women 40-49 (P = 0.009) and 50-59 (P < 0.001) years of age performed significantly fewer procedures per surgeon than men.
Women performed significantly fewer surgeries midcareer compared to their male counterparts
Automatic Segmentation And Quantification Of White And Brown Adipose Tissues From Pet/Ct Scans
No full textIn this paper, we investigate the automatic detection of white and brown adipose tissues using Positron Emission Tomography/Computed Tomography (PET/CT) scans, and develop methods for the quantification of these tissues at the whole-body and body-region levels. We propose a patient-specific automatic adiposity analysis system with two modules. In the first module, we detect white adipose tissue (WAT) and its two sub-types from CT scans: Visceral Adipose Tissue (VAT) and Subcutaneous Adipose Tissue (SAT). This process relies conventionally on manual or semi-automated segmentation, leading to inefficient solutions. Our novel framework addresses this challenge by proposing an unsupervised learning method to separate VAT from SAT in the abdominal region for the clinical quantification of central obesity. This step is followed by a context driven label fusion algorithm through sparse 3D Conditional Random Fields (CRF) for volumetric adiposity analysis. In the second module, we automatically detect, segment, and quantify brown adipose tissue (BAT) using PET scans because unlike WAT, BAT is metabolically active. After identifying BAT regions using PET, we perform a co-segmentation procedure utilizing asymmetric complementary information from PET and CT. Finally, we present a new probabilistic distance metric for differentiating BAT from non-BAT regions. Both modules are integrated via an automatic body-region detection unit based on one-shot learning. Experimental evaluations conducted on 151 PET/CT scans achieve state-of-the-art performances in both central obesity as well as brown adiposity quantification
Correlation Between Altmetric Scores and Citation Count in 4 High-Impact Plastic Surgery Journals
No full textBackground The Altmetric Attention Score (AAS) aims to determine the impact of research articles throughout the internet and social media outlets. The AAS is a weighted average of the interaction on platforms including Twitter, Facebook, Reddit, and more.Objectives The aim of this study was to investigate the relationship between the AAS and traditional bibliometrics across plastic surgery journals.Methods Articles, number of citations (NOC), and H-index information in Annals of Plastic Surgery (APS), Plastic and Reconstructive Surgery (PRS), Plastic and Reconstructive Surgery Global Open (PRS GO), and Aesthetic Surgery Journal (ASJ) from 2017, 2018, and 2019 were queried with the Scopus Online Tool. AAS metrics were collected with the Altmetric Score Calculator Bookmarklet. Descriptive statistics, Spearman rank-correlation analyses, and analyses of variance were performed to measure associations between NOC and AAS.Results A total of 3612 articles were analyzed. NOC was weakly correlated with AAS in APS, PRS GO, and ASJ, and moderately correlated with AAS in PRS. NOC was weakly correlated with Twitter mentions in APS, PRS GO, and ASJ, and moderately correlated in PRS. NOC was weakly correlated with news outlet reporting. The H-index of the first author showed more significant correlations with the AAS than the H-index of the last author.Conclusions NOC and H-index of the first author correlated with AAS in the plastic surgery literature, suggesting AAS may be a useful adjunct to traditional bibliometrics when evaluating the impact and reach of peer-reviewed articles
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