An original deep learning model using limited data for COVID‐19 discrimination: A multicenter study
Sign Up to like & getrecommendations! Published in 2022 at "Medical Physics"
DOI: 10.1002/mp.15549
Abstract: Abstract Objectives Artificial intelligence (AI) has been proved to be a highly efficient tool for COVID‐19 diagnosis, but the large data size and heavy label force required for algorithm development and the poor generalizability of… read more here.
Keywords: covid discrimination; data covid; using limited; covid ... See more keywords
Learning from Few Samples with Memory Network
Sign Up to like & getrecommendations! Published in 2017 at "Cognitive Computation"
DOI: 10.1007/s12559-017-9507-z
Abstract: Neural networks (NN) have achieved great successes in pattern recognition and machine learning. However, the success of a NN usually relies on the provision of a sufficiently large number of data samples as training data.… read more here.
Keywords: memory network; neural networks; learning samples; limited data ... See more keywords
Developing Surrogate Markers for Predicting Antibiotic Resistance "Hot Spots" in Rivers Where Limited Data Are Available.
Sign Up to like & getrecommendations! Published in 2021 at "Environmental science & technology"
DOI: 10.1021/acs.est.1c00939
Abstract: Pinpointing environmental antibiotic resistance (AR) hot spots in low-and middle-income countries (LMICs) is hindered by a lack of available and comparable AR monitoring data relevant to such settings. Addressing this problem, we performed a comprehensive… read more here.
Keywords: resistance hot; water quality; antibiotic resistance; limited data ... See more keywords
Super-Resolution Residual U-Net Model for the Reconstruction of Limited-Data Tunable Diode Laser Absorption Tomography
Sign Up to like & getrecommendations! Published in 2022 at "ACS Omega"
DOI: 10.1021/acsomega.2c01435
Abstract: Resolution is an important index for evaluating the reconstruction performance of temperature distributions in a combustion environment, and a higher resolution is necessary to obtain more precise combustion diagnoses. Tunable diode laser absorption tomography (TDLAT)… read more here.
Keywords: tunable diode; super resolution; resolution; reconstruction ... See more keywords
Parameter selection in limited data cone-beam CT reconstruction using edge-preserving total variation algorithms.
Sign Up to like & getrecommendations! Published in 2017 at "Physics in medicine and biology"
DOI: 10.1088/1361-6560/aa93d3
Abstract: There are a number of powerful total variation (TV) regularization methods that have great promise in limited data cone-beam CT reconstruction with an enhancement of image quality. These promising TV methods require careful selection of… read more here.
Keywords: reconstruction; selection; total variation; data cone ... See more keywords
An Overview of Parametric Modeling and Methods for Radar Target Detection With Limited Data
Sign Up to like & getrecommendations! Published in 2021 at "IEEE Access"
DOI: 10.1109/access.2021.3074063
Abstract: This article provides a survey of recent results on exploiting parametric auto-regressive (AR) models for adaptive radar target detection. Specifically, three types of radar systems are considered, including phased-array radar with multiple co-located transmitters and… read more here.
Keywords: limited data; radar; target detection; radar target ... See more keywords
Cognition-Enhanced Machine Learning for Better Predictions with Limited Data.
Sign Up to like & getrecommendations! Published in 2021 at "Topics in cognitive science"
DOI: 10.1111/tops.12574
Abstract: The fields of machine learning (ML) and cognitive science have developed complementary approaches to computationally modeling human behavior. ML's primary concern is maximizing prediction accuracy; cognitive science's primary concern is explaining the underlying mechanisms. Cross-talk… read more here.
Keywords: model; cognitive science; machine learning; limited data ... See more keywords
Development of a Parametric Regional Multivariate Statistical Weather Generator for Risk Assessment Studies in Areas with Limited Data Availability
Sign Up to like & getrecommendations! Published in 2020 at "Climate"
DOI: 10.3390/cli8080093
Abstract: Risk analysis of water resources systems can use statistical weather generators coupled with hydrologic models to examine scenarios of extreme events caused by climate change. These require multivariate, multi-site models that mimic the spatial, temporal,… read more here.
Keywords: risk; weather generator; statistical weather; limited data ... See more keywords
Evaluation and management of orthostatic hypotension: Limited data, limitless opportunity
Sign Up to like & getrecommendations! Published in 2022 at "Cleveland Clinic Journal of Medicine"
DOI: 10.3949/ccjm.89gr.22001
Abstract: Although orthostatic hypotension is common and can have serious consequences, recommendations about its evaluation and management are based on limited data. Here, the author outlines a systematic approach, noting the areas that pose an opportunity… read more here.
Keywords: limited data; orthostatic hypotension; evaluation management; opportunity ... See more keywords
Bounded rationality and limited data sets
Sign Up to like & getrecommendations! Published in 2021 at "Theoretical Economics"
DOI: 10.3982/te4070
Abstract: Theories of bounded rationality are typically characterized over an exhaustive data set. How does one tell whether observed choices are consistent with a theory if the data is incomplete? How can out-of-sample predictions be made?… read more here.
Keywords: rationality limited; data sets; rationality; limited data ... See more keywords