Search results for "lcsh:Computer applications to medicine. Medical informatics"
showing 10 items of 130 documents
A survey dataset to evaluate the changes in mobility and transportation due to COVID-19 travel restrictions in Australia, Brazil, China, Ghana, India…
2020
COVID-19 pandemic has heavily impacted the global community. To curb the viral transmission, travel restrictions have been enforced across the world. The dataset documents the mobility disruptions and the modal shifts that have occurred as a consequence of the restrictive measures implemented in ten countries: Australia, Brazil, China, Ghana, India, Iran, Italy, Norway, South Africa and the United States. An online questionnaire was distributed during the period from the 11st to the 31st of May 2020, with a total of 9 394 respondents. The first part of the survey has characterized the frequency of use of all transport modes before and during the enforcement of the restrictions, while the se…
Outside-host phage therapy as a biological control against environmental infectious diseases
2018
Background Environmentally growing pathogens present an increasing threat for human health, wildlife and food production. Treating the hosts with antibiotics or parasitic bacteriophages fail to eliminate diseases that grow also in the outside-host environment. However, bacteriophages could be utilized to suppress the pathogen population sizes in the outside-host environment in order to prevent disease outbreaks. Here, we introduce a novel epidemiological model to assess how the phage infections of the bacterial pathogens affect epidemiological dynamics of the environmentally growing pathogens. We assess whether the phage therapy in the outside-host environment could be utilized as a biologi…
A general strategy to determine the congruence between a hierarchical and a non-hierarchical classification
2007
This article is available from: http://www.biomedcentral.com/1471-2105/8/442
Characterisation of patients with familial chylomicronaemia syndrome (FCS) and multifactorial chylomicronaemia syndrome (MCS): Establishment of an FC…
2018
Data presented in this article are supplementary material to our article entitled "Identification and diagnosis of patients with familial chylomicronaemia syndrome (FCS): expert panel recom mendations and proposal of an "FCS Score" (Moulin et al., 2018, in press). The data describe the genotypes of patients with familial chylomicronaemia syndrome (FCS) and multifactorial chylomicro naemia syndrome (MCS), from the validation and replication cohorts.
Methods of spatial cluster detection in rare childhood cancers: Benchmarking data and results from a simulation study on nephroblastoma
2021
Abstract The potential existence of spatial clusters in childhood cancer incidence is a debated topic. Identification of rare disease clusters in general may help to better understand disease etiology and develop preventive strategies against such entities. The incidence of newly diagnosed childhood malignancies under 15 years of age is 140/1,000,000. In this context, the subgroup of nephroblastoma represents an extremely rare entity with an annual incidence of 7/1,000,000. We evaluated widely used statistical approaches for spatial cluster detection in childhood cancer (Ref. [22] Schundeln et al., 2021, Cancer Epidemiology). For the simulation study, random high risk clusters of 1 to 50 ad…
proTRAC - a software for probabilistic piRNA cluster detection, visualization and analysis
2012
Abstract Background Throughout the metazoan lineage, typically gonadal expressed Piwi proteins and their guiding piRNAs (~26-32nt in length) form a protective mechanism of RNA interference directed against the propagation of transposable elements (TEs). Most piRNAs are generated from genomic piRNA clusters. Annotation of experimentally obtained piRNAs from small RNA/cDNA-libraries and detection of genomic piRNA clusters are crucial for a thorough understanding of the still enigmatic piRNA pathway, especially in an evolutionary context. Currently, detection of piRNA clusters relies on bioinformatics rather than detection and sequencing of primary piRNA cluster transcripts and the stringency …
Convolutional architectures for virtual screening
2020
Abstract Background A Virtual Screening algorithm has to adapt to the different stages of this process. Early screening needs to ensure that all bioactive compounds are ranked in the first positions despite of the number of false positives, while a second screening round is aimed at increasing the prediction accuracy. Results A novel CNN architecture is presented to this aim, which predicts bioactivity of candidate compounds on CDK1 using a combination of molecular fingerprints as their vector representation, and has been trained suitably to achieve good results as regards both enrichment factor and accuracy in different screening modes (98.55% accuracy in active-only selection, and 98.88% …
Water stable isotope data set in temperate, lowland catchment, two years of monthly observations, River Salaca, Latvia
2020
Highlights • Two years of monthly water stable isotope ratios from temperate lowland catchment. • Hourly water table, temperature and electrical conductivity monitoring. • Distinct isotope ratios for raised bog, groundwater and rivers.
FluDetWeb: an interactive web-based system for the early detection of the onset of influenza epidemics
2009
Abstract Background The early identification of influenza outbreaks has became a priority in public health practice. A large variety of statistical algorithms for the automated monitoring of influenza surveillance have been proposed, but most of them require not only a lot of computational effort but also operation of sometimes not-so-friendly software. Results In this paper, we introduce FluDetWeb, an implementation of a prospective influenza surveillance methodology based on a client-server architecture with a thin (web-based) client application design. Users can introduce and edit their own data consisting of a series of weekly influenza incidence rates. The system returns the probabilit…
Deep learning enables robust assessment and selection of human blastocysts after in vitro fertilization
2019
AbstractVisual morphology assessment is routinely used for evaluating of embryo quality and selecting human blastocysts for transfer after in vitro fertilization (IVF). However, the assessment produces different results between embryologists and as a result, the success rate of IVF remains low. To overcome uncertainties in embryo quality, multiple embryos are often implanted resulting in undesired multiple pregnancies and complications. Unlike in other imaging fields, human embryology and IVF have not yet leveraged artificial intelligence (AI) for unbiased, automated embryo assessment. We postulated that an AI approach trained on thousands of embryos can reliably predict embryo quality with…