scholarly journals A Lexical Approach for Text Categorization of Medical Documents

2015 ◽  
Vol 46 ◽  
pp. 314-320 ◽  
Author(s):  
Rajni Jindal ◽  
Shweta Taneja
Keyword(s):  
Text Categorization ◽  
Medical Documents ◽  
Lexical Approach

Influence of feature weight on text categorization performance of Bayesian classifier

2009 ◽  
Vol 28 (12) ◽  
pp. 3080-3083 ◽  
Author(s):  
Xiu-mei GAO ◽  
Fang CHEN ◽  
Feng-xi SONG ◽  
Zhong JIN
Keyword(s):  
Text Categorization ◽  
Bayesian Classifier ◽  
Feature Weight

Medicine between Cultures in the Hellenistic Fayum

2017 ◽  
Author(s):  
Daniel King
Keyword(s):  
Local Community ◽  
Religious Practice ◽  
Local Health ◽  
Medical Culture ◽  
Greek Culture ◽  
The Status ◽  
Local Health Care ◽  
Egyptian Culture ◽  
Medical Documents ◽  
Medical Treatises

This paper looks into the relationship between Greek medicine and Egyptian culture in Tebtynis. Cultural interaction in this context has often been interpreted from a perspective that privileges the status of Greek culture: Hellenistic medical treatises (and other texts) were imported to Tebtynis to ‘improve’ the local community and local health-care. This paper looks at two aspects of Greek medical culture at the site: theoretical Hippokratic treatises and pharmaceutical recipes. These medical documents were associated with the Egyptian community in the village, especially the famous sanctuary of Soknebtynis. Analysis suggests that these documents were part of a medical culture that transcended cultural or ethnic divides; there is, this paper argues, considerable evidence for the co-existence of Greek medicine and Egyptian religious practice and ritual life.

A lazy feature selection method for multi-label classification

2021 ◽  
Vol 25 (1) ◽  
pp. 21-34
Author(s):  
Rafael B. Pereira ◽  
Alexandre Plastino ◽  
Bianca Zadrozny ◽  
Luiz H.C. Merschmann
Keyword(s):  
Feature Selection ◽  
Text Categorization ◽  
Feature Selection Method ◽  
Selection Method ◽  
Video Classification ◽  
Classification Problems ◽  
Class Label ◽  
New Feature ◽  
Feature Selection Techniques ◽  
Biomolecular Analysis

In many important application domains, such as text categorization, biomolecular analysis, scene or video classification and medical diagnosis, instances are naturally associated with more than one class label, giving rise to multi-label classification problems. This has led, in recent years, to a substantial amount of research in multi-label classification. More specifically, feature selection methods have been developed to allow the identification of relevant and informative features for multi-label classification. This work presents a new feature selection method based on the lazy feature selection paradigm and specific for the multi-label context. Experimental results show that the proposed technique is competitive when compared to multi-label feature selection techniques currently used in the literature, and is clearly more scalable, in a scenario where there is an increasing amount of data.

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