A Novel Approach for Classification of E-Commerce Data

Author(s):  
K. Chaitanya ◽  
D. V. L. N. Somayajulu ◽  
P. Radha Krishna
Keyword(s):  
Author(s):  
David Lewis-Smith ◽  
Shiva Ganesan ◽  
Peter D. Galer ◽  
Katherine L. Helbig ◽  
Sarah E. McKeown ◽  
...  

AbstractWhile genetic studies of epilepsies can be performed in thousands of individuals, phenotyping remains a manual, non-scalable task. A particular challenge is capturing the evolution of complex phenotypes with age. Here, we present a novel approach, applying phenotypic similarity analysis to a total of 3251 patient-years of longitudinal electronic medical record data from a previously reported cohort of 658 individuals with genetic epilepsies. After mapping clinical data to the Human Phenotype Ontology, we determined the phenotypic similarity of individuals sharing each genetic etiology within each 3-month age interval from birth up to a maximum age of 25 years. 140 of 600 (23%) of all 27 genes and 3-month age intervals with sufficient data for calculation of phenotypic similarity were significantly higher than expect by chance. 11 of 27 genetic etiologies had significant overall phenotypic similarity trajectories. These do not simply reflect strong statistical associations with single phenotypic features but appear to emerge from complex clinical constellations of features that may not be strongly associated individually. As an attempt to reconstruct the cognitive framework of syndrome recognition in clinical practice, longitudinal phenotypic similarity analysis extends the traditional phenotyping approach by utilizing data from electronic medical records at a scale that is far beyond the capabilities of manual phenotyping. Delineation of how the phenotypic homogeneity of genetic epilepsies varies with age could improve the phenotypic classification of these disorders, the accuracy of prognostic counseling, and by providing historical control data, the design and interpretation of precision clinical trials in rare diseases.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Carlo Donadio ◽  
Massimo Brescia ◽  
Alessia Riccardo ◽  
Giuseppe Angora ◽  
Michele Delli Veneri ◽  
...  

AbstractSeveral approaches were proposed to describe the geomorphology of drainage networks and the abiotic/biotic factors determining their morphology. There is an intrinsic complexity of the explicit qualification of the morphological variations in response to various types of control factors and the difficulty of expressing the cause-effect links. Traditional methods of drainage network classification are based on the manual extraction of key characteristics, then applied as pattern recognition schemes. These approaches, however, have low predictive and uniform ability. We present a different approach, based on the data-driven supervised learning by images, extended also to extraterrestrial cases. With deep learning models, the extraction and classification phase is integrated within a more objective, analytical, and automatic framework. Despite the initial difficulties, due to the small number of training images available, and the similarity between the different shapes of the drainage samples, we obtained successful results, concluding that deep learning is a valid way for data exploration in geomorphology and related fields.


2009 ◽  
Vol 133 (2) ◽  
pp. 201-216 ◽  
Author(s):  
Laura Barisoni ◽  
H. William Schnaper ◽  
Jeffrey B. Kopp

AbstractContext.—Etiologic factors and pathways leading to altered podocyte phenotype are clearly numerous and involve the activity of different cellular function.Objective.—To focus on recent discoveries in podocyte biology and genetics and their relevance to these human glomerular diseases, named podocytopathies.Data Sources.—Genetic mutations in genes encoding for proteins in the nucleus, slit diaphragm, podocyte cytoplasm, and cell membrane are responsible for podocyte phenotype and functional abnormalities. Podocyte injury may also derive from secondary stimuli, such as mechanical stress, infections, or use of certain medications. Podocytes can respond to injury in a limited number of ways, which include (1) effacement, (2) apoptosis, (3) arrest of development, and (4) dedifferentiation. Each of these pathways results in a specific glomerular morphology: minimal change nephropathy, focal segmental glomerulosclerosis, diffuse mesangial sclerosis, and collapsing glomerulopathy.Conclusions.—Based on current knowledge of podocyte biology, we organized etiologic factors and morphologic features in a taxonomy of podocytopathies, which provides a novel approach to the classification of these diseases. Current and experimental therapeutic approaches are also discussed.


PEDIATRICS ◽  
1965 ◽  
Vol 35 (4) ◽  
pp. 640-640
Author(s):  
JONATHAN COHEN

With the exception of the skill, the bones have more varieties of lesions about which little or nothing is known than do any other tissues of the body. While mast of these lesions, known largely through their roentgenological appearance and empirical course, are rare, the total group is numerous enough to engage the interest of many. Any approach to useful classification or increased understanding of etiology or pathogenesis would be welcome. Whether Rubin's novel approach fulfils this need in any measure is problematic.


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