Results 11 to 20 of about 37,658,670 (280)
Addressing delayed case reporting in infectious disease forecast modeling [PDF]
, 2021 Infectious disease forecasting is of great interest to the public health community and policymakers, since forecasts can provide insight into disease dynamics in the near future and inform interventions. Due to delays in case reporting, however, forecasting models may often underestimate the current and future disease burden.
arxiv +1 more source
Quantifying Spatial Under-reporting Disparities in Resident Crowdsourcing [PDF]
, 2022 Modern city governance relies heavily on crowdsourcing to identify problems such as downed trees and power lines. A major concern is that residents do not report problems at the same rates, with heterogeneous reporting delays directly translating to downstream disparities in how quickly incidents can be addressed.
arxiv +1 more source
Auto-labelling of Bug Report using Natural Language Processing [PDF]
2023 IEEE 8th International Conference for Convergence in
Technology (I2CT), 2022 The exercise of detecting similar bug reports in bug tracking systems is known as duplicate bug report detection. Having prior knowledge of a bug report's existence reduces efforts put into debugging problems and identifying the root cause. Rule and Query-based solutions recommend a long list of potential similar bug reports with no clear ranking.
arxiv +1 more source
Supervised Machine Learning Algorithm for Detecting Consistency between Reported Findings and the Conclusions of Mammography Reports [PDF]
arXiv, 2022 Objective. Mammography reports document the diagnosis of patients' conditions. However, many reports contain non-standard terms (non-BI-RADS descriptors) and incomplete statements, which can lead to conclusions that are not well-supported by the reported findings.
arxiv
PLoS Medicine, 2015 Routinely collected health data, obtained for administrative and clinical purposes without specific a priori research goals, are increasingly used for research.
E. Benchimol +8 more
semanticscholar +1 more source
, 2015 type="main"> We construct a new, parsimonious, measure of disclosure quality—disaggregation quality (DQ)—and offer validation tests. DQ captures the level of disaggregation of accounting data through a count of nonmissing Compustat line items, and ...
Shuping Chen, Bin Miao, T. Shevlin
semanticscholar +1 more source
Epidemiological data from the COVID-19 outbreak, real-time case information
Scientific Data, 2020 Cases of a novel coronavirus were first reported in Wuhan, Hubei province, China, in December 2019 and have since spread across the world. Epidemiological studies have indicated human-to-human transmission in China and elsewhere.
Bo Xu +21 more
semanticscholar +1 more source
A reference set of curated biomedical data and metadata from clinical case reports
Scientific Data, 2018 Clinical case reports (CCRs) provide an important means of sharing clinical experiences about atypical disease phenotypes and new therapies. However, published case reports contain largely unstructured and heterogeneous clinical data, posing a challenge ...
J. Caufield +15 more
semanticscholar +1 more source
CirculationBACKGROUND: The American Heart Association (AHA), in conjunction with the National Institutes of Health, annually reports the most up-to-date statistics related to heart disease, stroke, and cardiovascular risk factors, including core health behaviors ...
Seth S. Martin +42 more
semanticscholar +1 more source
Too Few Bug Reports? Exploring Data Augmentation for Improved Changeset-based Bug Localization [PDF]
arXiv, 2023 Modern Deep Learning (DL) architectures based on transformers (e.g., BERT, RoBERTa) are exhibiting performance improvements across a number of natural language tasks. While such DL models have shown tremendous potential for use in software engineering applications, they are often hampered by insufficient training data.
arxiv