Results 21 to 30 of about 59,770 (264)
Automated categorisation of clinical incident reports using statistical text classification [PDF]
To explore the feasibility of using statistical text classification techniques to automatically categorise clinical incident reports.Statistical text classifiers based on Naïve Bayes and Support Vector Machine algorithms were trained and tested on incident reports submitted by public hospitals to identify two classes of clinical incidents: inadequate ...
Mei-Sing, Ong +2 more
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A core task in technology management in biomedical engineering and beyond is the classification of patents into domain-specific categories, increasingly automated by machine learning, with the fuzzy language of patents causing particular problems ...
Kai Frerich +3 more
doaj +1 more source
A Text Classification Methodology to Assist a Large Technical Support System
Text-based tools for reporting technical issues and receiving support are widespread in commercial applications, such as customer services and internal corporate communication.
Elene Firmeza Ohata +4 more
doaj +1 more source
Medical Social Media Text Classification Integrating Consumer Health Terminology
In recent years, advances in technologies, such as machine learning, natural language processing, and automated data processing, have offered potential biomedical and public health applications that use massive data sources, e.g., social media.
Kan Liu, Lu Chen
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Text classification to streamline online wildlife trade analyses.
Automated monitoring of websites that trade wildlife is increasingly necessary to inform conservation and biosecurity efforts. However, e-commerce and wildlife trading websites can contain a vast number of advertisements, an unknown proportion of which ...
Oliver C Stringham +6 more
doaj +1 more source
Least information document representation for automated text classification [PDF]
AbstractWe propose the Least Information theory (LIT) to quantify meaning of information in probability distributions and derive a new document representation model for text classification. By extending Shannon entropy to accommodate a non‐linear relation between information and uncertainty, LIT offers an information‐centric approach to weight terms ...
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Background: Automated supervised text classification methods require preclassified training data. Their application in scenarios that a large amount of preclassified data is not accessible is challenging.
Shayan Eftekhar, Behzad Eftekhar
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Electronic Health Record classification and analysis using NLP Techniques [PDF]
This paper presents an automated system for the classification and analysis of Electronic Health Records (EHRs) using Natural Language Processing (NLP) techniques. The proposed solution integrates text extraction from PDFs and NLP methods to identify and
Himavamshi K. +5 more
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Aldehyde dehydrogenase 1A1 (ALDH1A1) is a cancer stem cell marker in several malignancies. We established a novel epithelial cell line from rectal adenocarcinoma with unique overexpression of this enzyme. Genetic attenuation of ALDH1A1 led to increased invasive capacity and metastatic potential, the inhibition of proliferation activity, and ultimately ...
Martina Poturnajova +25 more
wiley +1 more source
Multi-grained Sentiment Analysis of Comments Based on Text Generation [PDF]
With the rise of social media and online review platforms,automated sentiment analysis has become a key tool for understanding public emotions,consumer preferences,and market trends.Traditional sentiment analysis methods often use classification models ...
ZHANG Jiawei, WANG Zhongqing, CHEN Jiali
doaj +1 more source

