scholarly journals Diabetic Retinopathy Diagnosis Based on RA-EfficientNet

2021 ◽  
Vol 11 (22) ◽  
pp. 11035
Author(s):  
San-Li Yi ◽  
Xue-Lian Yang ◽  
Tian-Wei Wang ◽  
Fu-Rong She ◽  
Xin Xiong ◽  
...  
Keyword(s):  
Diabetic Retinopathy ◽  
Detection Efficiency ◽  
Small Sample Size ◽  
Image Features ◽  
Small Sample ◽  
Size Difference ◽  
Diagnostic Model ◽  
Learning Technology ◽  
Kappa Score ◽  
Grade Classification

The early detection and grade diagnosis of diabetic retinopathy (DR) are very important for the avoidance of blindness, and using deep learning methods to automatically diagnose DR has attracted great attention. However, the small amount of DR data limits its application. To automatically learn the disease’s features and detect DR more accurately, we constructed a DR grade diagnostic model. To realize the model, the authors performed the following steps: firstly, we preprocess the DR images to solve the existing problems in an APTOS 2019 dataset, such as size difference, information redundancy and the data imbalance. Secondly, to extract more valid image features, a new network named RA-EfficientNet is proposed, in which a residual attention (RA) block is added to EfficientNet to extract more features and to solve the problem of small differences between lesions. EfficientNet has been previously trained on the ImageNet dataset, based on transfer learning technology, to overcome the small sample size problem of DR. Lastly, based on the extracted features, two classifiers are designed, one is a 2-grade classifier and the other a 5-grade classifier. The 2-grade classifier can diagnose DR, and the 5-grade classifier provides 5 grades of diagnosis for DR, as follows: 0 for No DR, 1 for mild DR, 2 for moderate, 3 for severe and 4 for proliferative DR. Experiments show that our proposed RA-EfficientNet can achieve better performance, with an accuracy value of 98.36% and a kappa score of 96.72% in a 2-grade classification and an accuracy value of 93.55% and a kappa score of 91.93% in a 5-grade classification. The results indicate that the proposed model effectively improves DR detection efficiency and resolves the existing limitation of manual feature extraction.

Transfer learning with convolutional neural networks for small sample size problem in machinery fault diagnosis

2019 ◽  
Vol 233 (14) ◽  
pp. 5131-5143 ◽  
Author(s):  
Dengyu Xiao ◽  
Yixiang Huang ◽  
Chengjin Qin ◽  
Zhiyu Liu ◽  
Yanming Li ◽  
...  
Keyword(s):  
Neural Networks ◽  
Fault Diagnosis ◽  
Sample Size ◽  
Transfer Learning ◽  
Small Sample Size ◽  
Small Sample ◽  
Diagnostic Model ◽  
Source Data ◽  
Target Data ◽  
Machinery Fault Diagnosis

Data-driven machinery fault diagnosis has gained much attention from academic research and industry to guarantee the machinery reliability. Traditional fault diagnosis frameworks are commonly under a default assumption: the training and test samples share the similar distribution. However, it is nearly impossible in real industrial applications, where the operating condition always changes over time and the quantity of the same-distribution samples is often not sufficient to build a qualified diagnostic model. Therefore, transfer learning, which possesses the capacity to leverage the knowledge learnt from the massive source data to establish a diagnosis model for the similar but small target data, has shown potential value in machine fault diagnosis with small sample size. In this paper, we propose a novel fault diagnosis framework for the small amount of target data based on transfer learning, using a modified TrAdaBoost algorithm and convolutional neural networks. First, the massive source data with different distributions is added to the target data as the training data. Then, a convolutional neural network is selected as the base learner and the modified TrAdaBoost algorithm is employed for the weight update of each training sample to form a stronger diagnostic model. The whole proposition is experimentally demonstrated and discussed by carrying out the tests of six three-phase induction motors under different operating conditions and fault types. Results show that compared with other methods, the proposed framework can achieve the highest fault diagnostic accuracy with inadequate target data.

scholarly journals The Association between VDR Gene Polymorphisms and Diabetic Retinopathy Susceptibility: A Systematic Review and Meta-Analysis

2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Yun Zhang ◽  
Wei Xia ◽  
Ping Lu ◽  
Huijuan Yuan
Keyword(s):  
Diabetic Retinopathy ◽  
Sample Size ◽  
Gene Polymorphisms ◽  
Small Sample Size ◽  
Meta Analysis ◽  
Small Sample ◽  
Additive Models ◽  
Vdr Gene ◽  
Foki Polymorphism ◽  
Vdr Gene Polymorphisms

Aims. Studies on the associations of vitamin D receptor (VDR) gene polymorphisms with diabetic retinopathy (DR) susceptibility reported conflicting results. A systematic meta-analysis was undertaken to clarify this topic.Methods. A systematic search of electronic databases (PubMed, EMBASE, and CNKI) was carried out until March 31, 2016. The pooled odds ratio (OR) and 95% confidence interval (CI) were used to assess the strength of the association.Results. A total of 7 studies fulfilling the inclusion criteria were included in this meta-analysis (649 cases and 707 controls). Pooled ORs showed a significant association between FokI polymorphism and DR risk in all the four genetic models (OR=1.612(1.354~1.921), 1.988 (1.481~2.668), 1.889 (1.424~2.505), and 2.674 (1.493~4.790) in allelic, dominant, recessive, and additive models, resp.,PZ<0.01), but not for TaqI or BsmI polymorphism (PZ>0.05). Similar results were found in the subgroup analysis. Sensitivity analysis indicated that the results were relatively stable and reliable. Results of Begg’s and Egger’s tests suggested a lack of publication bias.Conclusions. Our meta-analysis demonstrated that DR was significantly associated with VDR gene FokI polymorphism. However, due to the relatively small sample size in this meta-analysis, further studies with a larger sample size should be done to confirm the findings.

scholarly journals Association of gut microbiota with cerebral cortex and cerebrovascular abnormality in human mild traumatic brain injury

2020 ◽  
Author(s):  
Lijun Bai ◽  
Tianhui Li ◽  
Ming Zhang ◽  
Shan Wang ◽  
Shuoqiu Gan ◽  
...  
Keyword(s):  
Traumatic Brain Injury ◽  
Brain Injury ◽  
Gut Microbiota ◽  
Mild Traumatic Brain Injury ◽  
Small Sample Size ◽  
Small Sample ◽  
Diagnostic Model ◽  
Mild Tbi ◽  
Cerebrovascular Injury ◽  
Α Diversity

AbstractKey roles of the gut–brain axis in brain injury development have been suggested in various mouse models; however, little is known about its functional significance in human mild traumatic brain injury (TBI). Here, we decipher this axis by profiling the gut microbiota in 98 acute mild TBI patients and 62 matched controls, and subgroup of them also measured circulating mediators and applied neuroimaging. Mild TBI patients had increased α-diversity and different overall microbial compositions compared with controls. 25-microbial genus classifiers distinguish patients from controls with an area under the receiver operating characteristic curve (AUC) of 0.889, while adding serum mediators and neuroimaging features further improved performance even in a small sample size (AUC = 0.969). Numerous correlations existed between gut bacteria, aberrant cortical thickness and cerebrovascular injury. Co-occurrence network analysis revealed two unique gut–brain axes in patients: 1) altered intestinal Lachnospiraceae_NK4A136_group and Eubacterium_ruminantium_group-increased serum GDNF-subcallosal hypertrophy and cerebrovascular injury; 2) decreased intestinal Eubacterium_xylanophilum_group–upregulated IL-6–thinned anterior insula. Our findings provide a new integrated mechanistic understanding and diagnostic model of mild TBI.

scholarly journals Diabetic dermopathy (shin spots) and diabetic retinopathy – Are they associated?

2020 ◽  
Vol 2 ◽  
pp. 99-103
Author(s):  
Joan Felicita Samson ◽  
Mariam Philip ◽  
Shimna Clara Prasad ◽  
Libu Gnanaseelan Kanakamma
Keyword(s):  
Diabetes Mellitus ◽  
Diabetic Retinopathy ◽  
Regression Analysis ◽  
Sample Size ◽  
Small Sample Size ◽  
Small Sample ◽  
Diabetic Microangiopathy ◽  
Diabetic Patients ◽  
Duration Of Diabetes ◽  
The Mean

Objectives: Shin spots and diabetic retinopathy are considered as manifestations of diabetic microangiopathy. However, there are only a few studies about this possible association. We undertook this study to confirm a possible association between shin spots and diabetic retinopathy. Materials and Methods: A total of 137 patients between the ages of 40 and 70 years having diabetes mellitus of at least 5 years duration were included in the study. These patients were examined for skin and retinal changes. The study period was 6 months. Results: Of the 137 diabetic patients included in this study, 123 (89.8%) had shin spots. The mean age of diabetic patients with shin spots was 59.6 years. Diabetic retinopathy was seen in 83 cases (60.6%), of which 79 (95.2%) had shin spots. The mean duration of diabetes mellitus in patients with shin spots was 12.7 years and it was 8.1 years in those without shin spots. The mean duration of diabetes mellitus in patients with diabetic retinopathy was 13.6 years and it was 9.9 years in those without diabetic retinopathy. On doing regression analysis, it was found that it is the duration of diabetes that was associated with shin spots. Limitations: Small sample size was the limitation. Conclusion: Duration of diabetes mellitus is associated with the presence of dermopathy.

scholarly journals Characterizing Tourism Destination Image Using Photos’ Visual Content

2020 ◽  
Vol 9 (12) ◽  
pp. 730
Author(s):  
Xin Xiao ◽  
Chaoyang Fang ◽  
Hui Lin
Keyword(s):  
Deep Learning ◽  
Visual Information ◽  
Latent Dirichlet Allocation ◽  
Hot Spot ◽  
Small Sample Size ◽  
Small Sample ◽  
Destination Image ◽  
Learning Technology ◽  
Visual Content ◽  
Tourism Destination

“A picture is worth a thousand words”. Analysis of the visual content of tourist photos is an effective way to explore the image of tourist destinations. With the development of computer deep learning and big data mining technology, identifying the content of massive numbers of tourist photos by convolutional neural network (CNN) approaches breaks through the limitations of manual approaches of identifying photos’ visual information, e.g., small sample size, complex identification process, and results deviation. In this study, 531,629 travel photos of Jiangxi were identified as 365 scenes through deep learning technology. Through the latent Dirichlet allocation (LDA) model, five major tourism topics are found and visualized by map. Then, we explored the spatial and temporal distribution characteristics of different tourism scenes based on hot spot analysis technology and the seasonal evaluation index. Our research shows that the visual content mining on travel photos makes it possible to understand the tourism destination image and to reveal the temporal and spatial heterogeneity of the image, thereby providing an important reference for tourism marketing.

scholarly journals 234. Dalbavancin versus Outpatient Parenteral Antimicrobial Therapy with Vancomycin for Treatment of Bone and Joint Infections in a Veteran Population

2021 ◽  
Vol 8 (Supplement_1) ◽  
pp. S226-S226
Author(s):  
Emily A Gibbons ◽  
Teri L Hopkins ◽  
Manuel R Escobar ◽  
Linda Yang ◽  
Elizabeth Walter ◽  
...  
Keyword(s):  
Adverse Effects ◽  
Chart Review ◽  
Small Sample Size ◽  
Small Sample ◽  
Size Difference ◽  
Veterans Health ◽  
Joint Infections ◽  
Bone And Joint Infections ◽  
Baseline Characteristics ◽  
Picc Line

Abstract Background Dalbavancin is a long-acting lipoglycopeptide with broad gram-positive activity. A long half-life makes it an attractive treatment option for bone and joint infections (BJI). Previous studies have demonstrated efficacy of dalbavancin in the treatment of BJI. Based on these studies, our institution established a protocol for using dalbavancin as an alternative to IV antibiotics via PICC line. Methods Chart review was performed to compare outcomes of patients who were treated with dalbavancin versus vancomycin for BJI from 8/2017 –7/2020. Patients that received two doses of dalbavancin for BJI were compared with patients who received OPAT with vancomycin during the same time period. Patients were excluded if they were bacteremic or received dalbavancin for another indication. Data was collected from the Veterans Health Administration’s Corporate Data Warehouse and retrospective chart review. No statistical analyses were performed due to the descriptive nature of this study. Results A total of 59 patients were included; 25 received dalbavancin and 34 received vancomycin. Relevant differences in baseline characteristics included a higher proportion of patients with osteomyelitis (88% vs 74%) and refractory infection (64% vs 44%) in the dalbavancin group. More patients in the dalbavancin group (38% vs 24%) were readmitted for the same infection within one year, required (29% vs 21%) additional surgical intervention, and had increased CRPH on follow-up labs (32% vs 3%). Dalbavancin use likely expedited discharge in at least 5 cases where vancomycin levels were not therapeutic. No significant adverse effects due to dalbavancin were noted, aside from one patient with an increase in serum creatinine. In the vancomycin group, 8 patients changed antibiotics due to adverse effects or difficulty managing levels and 3 patients had ED visits for PICC line care. Conclusion Dalbavancin may be a safe PICC-sparing treatment for BJI, particularly in cases where compliance is of concern, or there are logistical or tolerability issues with vancomycin. Our findings do raise concern for worse outcomes with dalbavancin, but the small sample size, difference in baseline characteristics between groups and descriptive nature of the study preclude any conclusions from being drawn. Disclosures All Authors: No reported disclosures

Probing the ultrastructure of the mitotic and meiotic spindle in eggs: An expeditious approach based on semi-thin (0.25 μm) serial sections

1983 ◽  
Vol 41 ◽  
pp. 552-555
Author(s):  
Conly L. Rieder ◽  
S. Bowser ◽  
R. Nowogrodzki ◽  
K. Ross ◽  
G. Sluder
Keyword(s):  
Small Sample Size ◽  
Small Sample ◽  
Meiotic Spindle ◽  
Serial Sections ◽  
Mitotic Apparatus ◽  
Thin Sections ◽  
Cell Cycles ◽  
Ultrastructural Studies

Eggs have long been a favorite material for studying the mechanism of karyokinesis in-vivo and in-vitro. They can be obtained in great numbers and, when fertilized, divide synchronously over many cell cycles. However, they are not considered to be a practical system for ultrastructural studies on the mitotic apparatus (MA) for several reasons, the most obvious of which is that sectioning them is a formidable task: over 1000 ultra-thin sections need to be cut from a single 80-100 μm diameter egg and of these sections only a small percentage will contain the area or structure of interest. Thus it is difficult and time consuming to obtain reliable ultrastructural data concerning the MA of eggs; and when it is obtained it is necessarily based on a small sample size.We have recently developed a procedure which will facilitate many studies concerned with the ultrastructure of the MA in eggs. It is based on the availability of biological HVEM's and on the observation that 0.25 μm thick serial sections can be screened at high resolution for content (after mounting on slot grids and staining with uranyl and lead) by phase contrast light microscopy (LM; Figs 1-2).

Validating the Factor Structure of the Stigma of Suicide Scale–Short Form Spanish Version Among Healthcare Students

Crisis ◽  
2020 ◽  
pp. 1-5
Author(s):  
Ruthmarie Hernández-Torres ◽  
Paola Carminelli-Corretjer ◽  
Nelmit Tollinchi-Natali ◽  
Ernesto Rosario-Hernández ◽  
Yovanska Duarté-Vélez ◽  
...  
Keyword(s):  
Factor Structure ◽  
Structural Equation ◽  
Short Form ◽  
Small Sample Size ◽  
Small Sample ◽  
Spanish Version ◽  
Equation Modeling ◽  
Cross Sectional ◽  
Healthcare Students ◽  
Spanish Speaking

Abstract. Background: Suicide is a leading cause of death among Spanish-speaking individuals. Suicide stigma can be a risk factor for suicide. A widely used measure is the Stigma of Suicide Scale-Short Form (SOSS-SF; Batterham, Calear, & Christensen, 2013 ). Although the SOSS-SF has established psychometric properties and factor structure in other languages and cultural contexts, no evidence is available from Spanish-speaking populations. Aim: This study aims to validate a Spanish translation of the SOSS-SF among a sample of Spanish-speaking healthcare students ( N = 277). Method: We implemented a cross-sectional design with quantitative techniques. Results: Following a structural equation modeling approach, a confirmatory factor analysis (CFA) supported the three-factor model proposed by Batterham and colleagues (2013) . Limitations: The study was limited by the small sample size and recruitment by availability. Conclusion: Findings suggest that the Spanish version of the SOSS-SF is a valid and reliable tool with which to examine suicide stigma among Spanish-speaking populations.

An Initial Investigation of Suicide Attempt Disclosures Among US Veterans

Crisis ◽  
2020 ◽  
pp. 1-7
Author(s):  
Brooke A. Ammerman ◽  
Sarah P. Carter ◽  
Heather M. Gebhardt ◽  
Jonathan Buchholz ◽  
Mark A. Reger
Keyword(s):  
Suicide Attempt ◽  
Mental Health Professionals ◽  
Help Seeking ◽  
Psychiatric Treatment ◽  
Small Sample Size ◽  
Romantic Partners ◽  
Small Sample ◽  
Professional Care ◽  
Patient Disclosure ◽  
Previous Suicide Attempt

Abstract. Background: Patient disclosure of prior suicidal behaviors is critical for effectively managing suicide risk; however, many attempts go undisclosed. Aims: The current study explored how responses following a suicide attempt disclosure may relate to help-seeking outcomes. Method: Participants included 37 veterans with a previous suicide attempt receiving inpatient psychiatric treatment. Veterans reported on their most and least helpful experiences disclosing their suicide attempt to others. Results: Veterans disclosed their suicide attempt to approximately eight individuals. Mental health professionals were the most cited recipient of their most helpful disclosure; romantic partners were the most common recipient of their least helpful disclosures. Positive reactions within the context of the least helpful disclosure experience were positively associated with a sense of connection with the disclosure recipient. Positive reactions within the most helpful disclosure experience were positively associated with the likelihood of future disclosure. No reactions were associated with having sought professional care or likelihood of seeking professional care. Limitations: The results are considered preliminary due to the small sample size. Conclusion: Findings suggest that while positive reactions may influence suicide attempt disclosure experiences broadly, additional research is needed to clarify factors that drive the decision to disclose a suicide attempt to a professional.

Investigating the Dynamics of Suicidal Ideation

Crisis ◽  
2018 ◽  
Vol 39 (1) ◽  
pp. 65-69 ◽  
Author(s):  
Nina Hallensleben ◽  
Lena Spangenberg ◽  
Thomas Forkmann ◽  
Dajana Rath ◽  
Ulrich Hegerl ◽  
...  
Keyword(s):  
Suicidal Ideation ◽  
Small Sample Size ◽  
Unipolar Depression ◽  
Small Sample ◽  
History Of ◽  
Severity Of Depression ◽  
Ecological Momentary ◽  
Depressive Episodes ◽  
Ema Method ◽  
Shed Light

Abstract. Background: Although the fluctuating nature of suicidal ideation (SI) has been described previously, longitudinal studies investigating the dynamics of SI are scarce. Aim: To demonstrate the fluctuation of SI across 6 days and up to 60 measurement points using smartphone-based ecological momentary assessments (EMA). Method: Twenty inpatients with unipolar depression and current and/or lifetime suicidal ideation rated their momentary SI 10 times per day over a 6-day period. Mean squared successive difference (MSSD) was calculated as a measure of variability. Correlations of MSSD with severity of depression, number of previous depressive episodes, and history of suicidal behavior were examined. Results: Individual trajectories of SI are shown to illustrate fluctuation. MSSD values ranged from 0.2 to 21.7. No significant correlations of MSSD with several clinical parameters were found, but there are hints of associations between fluctuation of SI and severity of depression and suicidality. Limitations: Main limitation of this study is the small sample size leading to low power and probably missing potential effects. Further research with larger samples is necessary to shed light on the dynamics of SI. Conclusion: The results illustrate the dynamic nature and the diversity of trajectories of SI across 6 days in psychiatric inpatients with unipolar depression. Prediction of the fluctuation of SI might be of high clinical relevance. Further research using EMA and sophisticated analyses with larger samples is necessary to shed light on the dynamics of SI.

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