Social network analysis of Iranian researchers on medical parasitology: A 41 year co-authorship survey

Background: The aim of this study was to survey the Iranian Parasitology researchers� performance, and analyse and visualize the scientific outputs of their co-authorship network. Methods: This study was conducted using scientometric method and social network analysis (SNA). The data extracted from the Web of Science (WoS) databases in July 10th 2014. Totally, 1048documents of all types in research area of Parasitology during 1972-2013 by Iranian researches retrieved. The coauthorship map was drawn utilizing NETDRAW, Coauthor.exe, and UCINET softwares and was analysed based on SNA measures. Results: The researchers� co-authorship network consisted of 78 authors and its density degree is 0.57. �Mohebali� ranked top in all of centrality measures.The most of the publications were related to 2012, �Mohebali� with about 9 of all documents was the Iranian most prolific author in Parasitology field. The Iranian researches have published mostly (266 documents) in �Iranian Journal of Parasitology�, and the most of the documents belong to �Tropical Medicine� subject field. The most of Iranian researchers� scientific cooperation was performed with England and United States. Conclusion: Bringing forth density degree (is 0.57) showed that this network has an almost medium density. Indeed, the authors have had relations in moderate level with each other in the network. The findings of this study can be identified aspects of scientific collaboration, and help policy makers of Parasitology field research. © 2016, Tehran University of Medical Sciences (TUMS). All rights reserved

Effect of Intensity Standardization on Deep Learning for WML Segmentation in Multi-Centre FLAIR MRI

Deep learning (DL) methods for white matter lesion (WML) segmentation in MRI suffer a reduction in performance when applied on data from a scanner or centre that is out-of-distribution (OOD) from the training data. This is critical for translation and widescale adoption, since current models cannot be readily applied to data from new institutions. In this work, we evaluate several intensity standardization methods for MRI as a preprocessing step for WML segmentation in multi-centre Fluid-Attenuated Inversion Recovery (FLAIR) MRI. We evaluate a method specifically developed for FLAIR MRI called IAMLAB along with other popular normalization techniques such as White-strip, Nyul and Z-score. We proposed an Ensemble model that combines predictions from each of these models. A skip-connection UNet (SC UNet) was trained on the standardized images, as well as the original data and segmentation performance was evaluated over several dimensions. The training (in-distribution) data consists of a single study, of 60 volumes, and the test (OOD) data is 128 unseen volumes from three clinical cohorts. Results show IAMLAB and Ensemble provide higher WML segmentation performance compared to models from original data or other normalization methods. IAMLAB & Ensemble have the highest dice similarity coefficient (DSC) on the in-distribution data (0.78 & 0.80) and on clinical OOD data. DSC was significantly higher for IAMLAB compared to the original data (p25mL: 0.77 vs. 0.71; 10mL<= LL<25mL: 0.66 vs. 0.61; LL<10mL: 0.53 vs. 0.52). The IAMLAB and Ensemble normalization methods are mitigating MRI domain shift and are optimal for DL-based WML segmentation in unseen FLAIR data

Historiographical Map of Petroleum Scientific Outputs in Science Citation Index (SCI) through 1990-2011

The purpose of this study was to map the structure of scientific outputs of petroleum field in Science Citation Index (SCI) accessible via Web of Science (WOS) during 1990 to 2011 and determine the position of Iran. The used research methods were citation analysis and historiography. The results showed that there were totally 26859 records indexed in the petroleum discipline during 1990-2011 in SCI. USA, 7237 documents (27.28%), was the most collaborative country in this research. Iran with 321 documents ranked 21th country among all countries. The American author, Marshall A.G., with 85 documents ranked top among the most productive authors. In Iran, Kharrat from Petroleum University of Technology with 8 documents was the most productive Iranian author in petroleum field. Among the institutes and universities, Chinese Academy of Science was the most productive with 530 documents. Among the institutes and universities at national level, Tehran University has the first place with 53 documents. Energy &amp; Fuels, Organic Geochemistry, and Abstracts of Papers of the American Chemical Society were the most important journals in terms of production and citation (both LCS and GCS) in petroleum field. The scientific map of petroleum field was drawn using HistCiteTM software. The analysis of the map revealed six thematic clusters including “Analysis and evaluation of compounds and elements of molecular structure of petroleum”, “Analysis and evaluation of compounds and elements of molecular structure of petroleum using mass spectrometry”, “reviewing and modeling of conditions of production and formation of source rock”, “survey of petroleum and its compounds biodegradation by bacteria and algae”, “survey of characteristics and history of petroleum reservoir”, and “survey of polycyclic aromatic hydrocarbons (PAHs)”

Visualizing the Intellectual Structure of Iranian Physicists in Scisearch during 1990-2009: An Author Co-Citation Analysis (ACA)

The purpose of this paper was to study and map the intellectual structure of Iranian physicists using author co-citation technique during 1990-2009. The results of the study showed that Iranian physicists have produced 6290 documents indexed in Science Citation Index (SciSearch) during the studied period. Publication counts have grown at an approximate rate of 24/70 % per year. Setare M.R. with 121 documents was the most productive Iranian author in this study. Applied Physics, with1564 documents was the most interesting subject area for the Iranian physicists. We identified 42 Iranian and international physicists who were highly co-cited in 6290 documents during the studied period. Using principal components analysis, 8 subject factors were extracted. The subject areas of factors were in: "Physics, Particles &amp; Fields", "Astronomy &amp; Astrophysics", “Physics, Mathematical", “Physics, Multidisciplinary", "Physics, Nuclear", "Cosmology", "Physics, Atomic, Molecular &amp; Chemical", and "Physics, Fluids &amp; Plasmas". The PFNet map of the intellectual structure of Iranian physicists in SciSearch during 1990-2009 showed a central subject area in "Physics, Particles &amp; Field" with Witten E. as its focal author. The other clusters were rooted in this essential cluster

MLP-SRGAN: A Single-Dimension Super Resolution GAN using MLP-Mixer

We propose a novel architecture called MLP-SRGAN, which is a single-dimension Super Resolution Generative Adversarial Network (SRGAN) that utilizes Multi-Layer Perceptron Mixers (MLP-Mixers) along with convolutional layers to upsample in the slice direction. MLP-SRGAN is trained and validated using high resolution (HR) FLAIR MRI from the MSSEG2 challenge dataset. The method was applied to three multicentre FLAIR datasets (CAIN, ADNI, CCNA) of images with low spatial resolution in the slice dimension to examine performance on held-out (unseen) clinical data. Upsampled results are compared to several state-of-the-art SR networks. For images with high resolution (HR) ground truths, peak-signal-to-noise-ratio (PSNR) and structural similarity index (SSIM) are used to measure upsampling performance. Several new structural, no-reference image quality metrics were proposed to quantify sharpness (edge strength), noise (entropy), and blurriness (low frequency information) in the absence of ground truths. Results show MLP-SRGAN results in sharper edges, less blurring, preserves more texture and fine-anatomical detail, with fewer parameters, faster training/evaluation time, and smaller model size than existing methods. Code for MLP-SRGAN training and inference, data generators, models and no-reference image quality metrics will be available at https://github.com/IAMLAB-Ryerson/MLP-SRGAN.Comment: 14 pages, 10 figure

Averting HIV Infections in New York City: A Modeling Approach Estimating the Future Impact of Additional Behavioral and Biomedical HIV Prevention Strategies

Background:New York City (NYC) remains an epicenter of the HIV epidemic in the United States. Given the variety of evidence-based HIV prevention strategies available and the significant resources required to implement each of them, comparative studies are needed to identify how to maximize the number of HIV cases prevented most economically.Methods:A new model of HIV disease transmission was developed integrating information from a previously validated micro-simulation HIV disease progression model. Specification and parameterization of the model and its inputs, including the intervention portfolio, intervention effects and costs were conducted through a collaborative process between the academic modeling team and the NYC Department of Health and Mental Hygiene. The model projects the impact of different prevention strategies, or portfolios of prevention strategies, on the HIV epidemic in NYC.Results:Ten unique interventions were able to provide a prevention benefit at an annual program cost of less than $360,000, the threshold for consideration as a cost-saving intervention (because of offsets by future HIV treatment costs averted). An optimized portfolio of these specific interventions could result in up to a 34$106,378; the total cost was in excess of $2 billion (over the 20 year period, or approximately$100 million per year, on average). The cost-savings of prevented infections was estimated at more than $5 billion (or approximately$250 million per year, on average).Conclusions:Optimal implementation of a portfolio of evidence-based interventions can have a substantial, favorable impact on the ongoing HIV epidemic in NYC and provide future cost-saving despite significant initial costs. © 2013 Kessler et al

Psychometrics properties of the Iranian version of fertility quality of life tool: a cross- sectional study

Background: Clinical measurement of quality of life for assessing reproductive problems should be considered as a standard investigation at the initial and continuing medical consultations with infertile people. Objective: The purpose of this study was comprehensive testing the psychometric properties of the Iranian version of fertility quality of life (FertiQol) as its use could be considerable due to the prevalence of infertility in Iran and the importance of evaluation of QoL in patients with infertility. Method and material: This was a psychometric properties study of 300 women referred to infertility clinic, Hormozgan, Iran. After linguistic validation of the Iranian version of MPCOSQ, a semi-structured interview was conducted to assess face validity. Consequently exploratory factor analysis (EFA) and confirmatory factor analysis (CFA) were performed to indicate the scale constructs. Discriminant validity was assessed using the known groups comparison. Convergent validity was evaluated by assessing the correlation between similar content on the 12-Item Short Form Health Survey, Hospital Anxiety and Depression Scale and FertiQol. In addition, reliability analysis was carried out with internal consistency. Results: The reliability of the Iranian version of the FertiQol questionnaire was satisfactory in all dimensions (Cronbach’s alpha ranging from 0.77 to 0.83 ). Six factors (emotional, mind/body, relational, social, environmental and tolerability) were extracted from the results of EFA with factor loading of the more than 0.3. Discrimination validity showed that FertiQol can differentiate between female patients with differing duration of infertility and number of children; this indicates favorable discrimination validity. Moreover, the results of convergent validity showed a favorable correlation between the related dimensions of 12-Item Short Form Health Survey (correlation ranging from 0.43 to 0.68 ), Hospital Anxiety and Depression Scale(correlation ranging from 0.47 to 0.52 ) and FertiQol. Conclusion: The Iranian version of FertiQol is valid and reliable for assessing infertility problems and the effects of treatment on quality of life of infertile patients referred for diagnosis and treatment at an Iranian infertility clinic. The clinical use of this measure is recommended for Iranian infertility clinics