This study provides an overview of work done by researchers in areas related to Semantic Text Mining (STM). This is particularly important since STM could be considered a generic technique which is applied to signal detection in the work presented and similarly, signal detection could be considered a generic problem which is solved using STM technique in the work presented. A closer look at the evolution and challenges to be addressed provides a good starting point in arriving at the solution framework. In the literature review also cover of NLP and predication diseases for general diseases not particular disease. The detail of Clinical Decision Support System (CDSS) and the research studies in the field converting unstructured medical data...
Medical Decision Support Systems (MDSS) industry collects a huge amount of data, which is not proper...
Electronic health records (EHRs) are rich in data with the potential to leverage applications that p...
AbstractPurposeThis paper reviews the research literature on text mining (TM) with the aim to find o...
In hospitals, clinical cancer staging is an important element for determining the methods for treatm...
Most information in Hospitals is still only available in text format and the amount of this data is ...
Medical diagnosis is considered as an important yet complicated task that needs to be executed accur...
Text is a very important type of data within the biomedical domain. For example, patient records con...
Health care and clinical practice generate large amounts of text detailing symptoms, test results, d...
This dissertation focuses on developing and evaluating hybrid approaches for analyzing free-form tex...
OBJECTIVE: Combining text mining (TM) and clinical decision support (CDS) could improve diagnostic a...
Data Mining; Text Mining; Health Informatics; Health Care Information Systems; Medical Terminolo...
Text mining is one of the technologies designed to improve the quality of clinical medicine servic...
Purpose: This paper reviews the research literature on text mining (TM) with the aim to find out (1)...
Objective: We present a system developed for the Challenge in Natural Language Processing for Clinic...
Objective The authors present a system developed for the Challenge in Natural Language Processing fo...
Medical Decision Support Systems (MDSS) industry collects a huge amount of data, which is not proper...
Electronic health records (EHRs) are rich in data with the potential to leverage applications that p...
AbstractPurposeThis paper reviews the research literature on text mining (TM) with the aim to find o...
In hospitals, clinical cancer staging is an important element for determining the methods for treatm...
Most information in Hospitals is still only available in text format and the amount of this data is ...
Medical diagnosis is considered as an important yet complicated task that needs to be executed accur...
Text is a very important type of data within the biomedical domain. For example, patient records con...
Health care and clinical practice generate large amounts of text detailing symptoms, test results, d...
This dissertation focuses on developing and evaluating hybrid approaches for analyzing free-form tex...
OBJECTIVE: Combining text mining (TM) and clinical decision support (CDS) could improve diagnostic a...
Data Mining; Text Mining; Health Informatics; Health Care Information Systems; Medical Terminolo...
Text mining is one of the technologies designed to improve the quality of clinical medicine servic...
Purpose: This paper reviews the research literature on text mining (TM) with the aim to find out (1)...
Objective: We present a system developed for the Challenge in Natural Language Processing for Clinic...
Objective The authors present a system developed for the Challenge in Natural Language Processing fo...
Medical Decision Support Systems (MDSS) industry collects a huge amount of data, which is not proper...
Electronic health records (EHRs) are rich in data with the potential to leverage applications that p...
AbstractPurposeThis paper reviews the research literature on text mining (TM) with the aim to find o...