SS dataset and SS precursors measurements in stacked and individual data

2021 ◽  
Author(s):  
Lauren Waszek ◽  
Jorge Garcia ◽  
Benoit Tauzin ◽  
Nicholas Schmerr
Keyword(s):  
Individual Data ◽  
Ss Precursors

The FATE Landscape of Sign Language AI Datasets

2021 ◽  
Vol 14 (2) ◽  
pp. 1-45
Author(s):  
Danielle Bragg ◽  
Naomi Caselli ◽  
Julie A. Hochgesang ◽  
Matt Huenerfauth ◽  
Leah Katz-Hernandez ◽  
...  
Keyword(s):  
Sign Language ◽  
New Technology ◽  
Individual Data ◽  
Community Members ◽  
Sign Languages ◽  
Language Data ◽  
History Of ◽  
Language Technologies ◽  
And Storage ◽  
Access Mechanisms

Sign language datasets are essential to developing many sign language technologies. In particular, datasets are required for training artificial intelligence (AI) and machine learning (ML) systems. Though the idea of using AI/ML for sign languages is not new, technology has now advanced to a point where developing such sign language technologies is becoming increasingly tractable. This critical juncture provides an opportunity to be thoughtful about an array of Fairness, Accountability, Transparency, and Ethics (FATE) considerations. Sign language datasets typically contain recordings of people signing, which is highly personal. The rights and responsibilities of the parties involved in data collection and storage are also complex and involve individual data contributors, data collectors or owners, and data users who may interact through a variety of exchange and access mechanisms. Deaf community members (and signers, more generally) are also central stakeholders in any end applications of sign language data. The centrality of sign language to deaf culture identity, coupled with a history of oppression, makes usage by technologists particularly sensitive. This piece presents many of these issues that characterize working with sign language AI datasets, based on the authors’ experiences living, working, and studying in this space.

scholarly journals Short-Term Reproducibility of MUC5AC Measurement in Human Tear Fluid

Diagnostics ◽  
2021 ◽  
Vol 11 (1) ◽  
pp. 57
Author(s):  
Ashley M. Woodward ◽  
Michelle Senchyna ◽  
Pablo Argüeso
Keyword(s):  
Statistical Difference ◽  
Tear Film ◽  
Therapeutic Strategies ◽  
Individual Variability ◽  
Tear Fluid ◽  
Individual Data ◽  
Short Term ◽  
Coefficients Of Variation ◽  
Novel Therapeutic Strategies ◽  
Novel Therapeutic

The assessment of tear fluid components is a common and valuable approach to understanding ocular surface disease and testing the efficacy of novel therapeutic strategies. However, the interpretation and utility of the findings can be limited by changes in the composition of the tear film, particularly in studies requiring repetitive patient sampling. Here, tear samples were collected twice within a one-hour interval to evaluate the short-term reproducibility of an immunoassay aimed to measure the amount of MUC5AC mucin. We found no statistical difference in total protein or MUC5AC content between the two consecutive collections of tear fluid, although the inter-individual variability in each group was high, with coefficients of variation exceeding 30% and 50%, respectively. Scatterplots showed a significant correlation in both protein and MUC5AC following collection within a one-hour interval. These data indicate that, regardless of the high inter-individual variability, repeated collection of tear fluid within an hour interval produces reproducible intra-individual data in terms of MUC5AC mucin content, and suggest that the normal mucin composition of the tear fluid can be re-established within an hour of the initial collection.

scholarly journals Characteristics of intracerebral haemorrhage associated with COVID-19: a systematic review and pooled analysis of individual patient and aggregate data

2021 ◽  
Author(s):  
R. Beyrouti ◽  
J. G. Best ◽  
A. Chandratheva ◽  
R. J. Perry ◽  
D. J. Werring
Keyword(s):  
Intracerebral Haemorrhage ◽  
Pooled Analysis ◽  
Aggregate Data ◽  
High Rate ◽  
Individual Data ◽  
Aggregate Level ◽  
Level Data ◽  
Pooled Prevalence ◽  
Underlying Mechanisms ◽  
Different Characteristics

Abstract Background and purpose There are very few studies of the characteristics and causes of ICH in COVID-19, yet such data are essential to guide clinicians in clinical management, including challenging anticoagulation decisions. We aimed to describe the characteristics of spontaneous symptomatic intracerebral haemorrhage (ICH) associated with COVID-19. Methods We systematically searched PubMed, Embase and the Cochrane Central Database for data from patients with SARS-CoV-2 detected prior to or within 7 days after symptomatic ICH. We did a pooled analysis of individual patient data, then combined data from this pooled analysis with aggregate-level data. Results We included data from 139 patients (98 with individual data and 41 with aggregate-level data). In our pooled individual data analysis, the median age (IQR) was 60 (53–67) years and 64% (95% CI 54–73.7%) were male; 79% (95% CI 70.0–86.9%) had critically severe COVID-19. The pooled prevalence of lobar ICH was 67% (95% CI 56.3–76.0%), and of multifocal ICH was 36% (95% CI 26.4–47.0%). 71% (95% CI 61.0–80.4%) of patients were treated with anticoagulation (58% (95% CI 48–67.8%) therapeutic). The median NIHSS was 28 (IQR 15–28); mortality was 54% (95% CI 43.7–64.2%). Our combined analysis of individual and aggregate data showed similar findings. The pooled incidence of ICH across 12 cohort studies of inpatients with COVID-19 (n = 63,390) was 0.38% (95% CI 0.22–0.58%). Conclusions Our data suggest that ICH associated with COVID-19 has different characteristics compared to ICH not associated with COVID-19, including frequent lobar location and multifocality, a high rate of anticoagulation, and high mortality. These observations suggest different underlying mechanisms of ICH in COVID-19 with potential implications for clinical treatment and trials.

scholarly journals 38 Using pooled data for single-step genomic prediction: Impact of within-pool variance and size

2020 ◽  
Vol 98 (Supplement_4) ◽  
pp. 9-9
Author(s):  
Johnna L Baller ◽  
Stephen D Kachman ◽  
Larry A Kuehn ◽  
Matthew L Spangler
Keyword(s):  
Phenotypic Variation ◽  
Equal Opportunity ◽  
Cost Effective ◽  
Single Step ◽  
Pool Size ◽  
Individual Data ◽  
Phenotypic Data ◽  
Breeding Values ◽  
Mean Values ◽  
Genetic Evaluations

Abstract Economically relevant traits (ERT) are routinely collected within commercial segments of the beef industry but are rarely included in genetic evaluations because of unknown pedigrees. Individual relationships could be resurrected with genomics, which would be costly; pooling DNA and phenotypic data provides a cost-effective solution. A simulated beef cattle population consisting of 15 generations was genotyped with approximately 50k markers (841 quantitative trait loci were located across the genome) and phenotyped for a moderately heritable trait. Individuals from generation 15 were included in pools (observed genotype and phenotype were mean values of a group). Estimated breeding values (EBV) were generated from a single-step GBLUP model. The effects of pooling strategy (random and minimizing or uniformly maximizing phenotypic variation), pool size (1, 2, 10, 20, 50, 100, or no data from generation 15), and generational gaps of genotyping on EBV accuracy (correlation of EBV with true breeding values) were quantified. Greatest EBV accuracies of sires and dams were observed when no gap between genotyped parents and pooled offspring occurred. The EBV accuracies resulting from pools were greater than no data from generation 15 regardless of sire or dam genotyping. Minimizing phenotypic variation increased EBV accuracy by 8% and 9% over random pooling and uniformly maximizing phenotypic variation, respectively. Pool size of 2 was the only scenario that did not significantly decrease EBV accuracy compared to individual data when pools were formed randomly or by uniformly maximizing phenotypic variation (P > 0.05). Pool sizes of 2, 10, 20, or 50 did not generally lead to EBV accuracies that were statistically different than individual data when pools were constructed to minimize phenotypic variation (P > 0.05). Pooled genotyping to garner commercial-level phenotypes for genetic evaluations seems plausible, although differences exist depending on pool size and pool formation strategy. The USDA is an equal opportunity employer.

scholarly journals P1490MONTHLY TREND AND SEASONALITY IN ACUTE AND CHRONIC HEMODIALYSIS; RESULT FROM NATIONWIDE DATABASE OF MEDICAL BILLS OF UNIVERSAL HEALTH CARE INSURANCE SYSTEM IN JAPAN

2020 ◽  
Vol 35 (Supplement_3) ◽  
Author(s):  
Ryoya Tsunoda ◽  
Hirayasu Kai ◽  
Masahide Kondo ◽  
Naohiro Mitsutake ◽  
Kunihiro Yamagata
Keyword(s):  
Health Care ◽  
Seasonal Variation ◽  
Chronic Hemodialysis ◽  
Universal Health Care ◽  
Health Care Insurance ◽  
Individual Data ◽  
Insurance System ◽  
Number Of Patients ◽  
Medical Bills ◽  
Universal Health

Abstract Background and Aims Although knowing the accurate number of patients of hemodialysis important, data collection is a hard task. Establishing a simplified and prompt method of data collection for perspective hemodialysis is strongly needed. In Japan, there is a universal health care insurance system that covers almost all population. This study aimed to know a seasonal variation of hemodialysis patients using the big database of medical bills in Japan. Method Japanese Ministry of Health, Labour and Welfare established a big database named National Database (NDB), that consists of medical bills data in Japan. All bills data were sent to the data server from The Examination and Payment Agency, the organization that receives all medical bills from each medical institution and judge validity for payment. Each record of the database consists of bill data of one patient of a month for each medical institution. All data were anonymized before saved in the server and gave virtual patient identification number (VPID) that is unique for each patient. VPID is a hash value calculated by patient’s individual data such as name, date of birth, so that the value cannot be duplicate. Calculation of VPID is executed by an irreversible way to make it difficult to decrypt VPID into patient’s individual data. This database includes all information about medical care of whole population in Japan except for patients not under the insurance system (patients under public assistance system, victims of the war, or any other specified people under the public medical expense). Using this database, we investigated monthly number of patients who were recorded to be undergone hemodialysis (HD, includes hemodiafiltration). We searched chronic HD patients who have undergone HD on the month and continued it for 3 months, and acute HD patients who have discontinued HD within 3 months. Results In NDB, the number of chronic HD patients under public insurance system who confirmed to have undergone HD in December 2014 was 284 433. In contrast, the number of HD patients identified from the year-end survey by Japanese Society of Dialysis Therapy in the same year was of 311 193, but this number includes patients not under insurance system. Incidence rate of acute HD in Japan was persisted at 30-39 per million per month. There is a reproducible seasonal variation in number of acute HD patients, that increases in every winter and decreasing in every summer. The significantly highest frequency was observed in February(38.5/million/month) compared with September(30.6/million/month), the lowest month of the year (p<0.01). Conclusion We could show the trend in number of HD patients using nationwide bills data. Seasonality in some clinical factors in patients under chronic hemodialysis such as blood pressure, intradialytic body weight gain, morbidity of congestive heart failure, and, mortality, has been reported in many observational studies. Also, there are a few former reports about seasonality in AKI. However, a report about acute RRT is few. From our knowledge, this is the first report that revealed monthly dynamics of HD in a whole nation and rising risk of acute HD in winter. The true mechanism of this seasonality remains unclear. We have to establish a method to collect clinical data such as prevalence of CKD, causative diseases of AKI, kinds of precedent operations, and medications in connection with billing data.

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