Results 81 to 90 of about 82,469 (304)
ABSTRACT The detection and classification of diseases have become a field of interest for artificial intelligence in recent years, where the development of methods and models that allow support for specialists in different health fields has allowed early detection of diseases and the provision of timely treatment to patients.
Rodrigo Cordero‐Martínez +2 more
wiley +1 more source
Multivariate noises in the learning process are most of the time supposed to follow a standard multivariate normal distribution. This hypothesis does not often hold in many real-world situations.
Castro Gbêmêmali Hounmenou +2 more
doaj +1 more source
Spreadsheet Computation with imprecise and uncertain Data
We consider universal relations as flat tables having numeric data types which can be simply viewed as spreadsheets.
openaire +4 more sources
Abstract Our general interest is in global trade loss from livestock pathogens, specifically exports. We adopt a causal inference approach that considers animal disease outbreaks over time as non‐staggered binary treatments with the potential for switching in (infection) and out of treatment (recovery) within the sample period. The outcome evolution of
Mohammad Maksudur Rahman +1 more
wiley +1 more source
Nonparametric Predictive Inference for Ordinal Data and Accuracy of Diagnostic Tests [PDF]
This thesis considers Nonparametric Predictive Inference (NPI) for ordinal data and accuracy of diagnostic tests. We introduce NPI for ordinal data, which are categor- ical data with an ordering of the categories.
ALI, FAIZA,FARAG
core
Abstract While multiple factors explain low adoption rates of improved varieties by small‐scale farmers in sub‐Saharan Africa, a key supply‐side constraint is the limited availability of seed embodying new traits in the volume, quality, price, and timeliness required by farmers. This constraint is partly attributable to classical failures in the market
Dawit Mekonnen +5 more
wiley +1 more source
Data generation and application using the neutrosophic Erlang distribution
The Erlang distribution in classical statistics has traditionally been used for reliability analysis when there is no uncertainty in the underlying data. However, this classical framework cannot be applied in environments with inherent uncertainty.
Faten S. Alamri, Muhammad Aslam
doaj +1 more source
Comparison of different classifiers with varying amounts of imprecise data.
This table compares the performance of different classifiers for the original MIMIC II data and a version of the MIMIC II data where 50% of observations were randomly perturbed by a value ϵ, distributed normally with mean zero and the empirical variance ...
Roy Welsch (6590723) +3 more
core +1 more source
Cumulative Antigen Suppression Reduces Clonal Plasma Cell Evolution in Gaucher Disease
ABSTRACT Chronic antigenic stimulation is implicated in the pathogenesis of monoclonal gammopathy and multiple myeloma, yet longitudinal human evidence linking sustained antigen exposure to modifiable clonal plasma cell evolution remains limited. Gaucher disease (GD), caused by biallelic GBA1 pathogenic variants, is characterized by accumulation of ...
Noor Ul Ain +10 more
wiley +1 more source
Fabrication of a graphene-based sensor to detect the humidity and the temperature of a metal body with imprecise data analysis. [PDF]
Afzal U +6 more
europepmc +1 more source

