A systematic review on supervised and unsupervised machine learning algorithms for data science
Abstract Machine learning is as growing as fast as concepts such as Big data and the field of
data science in general. The purpose of the systematic review was to analyze scholarly …
data science in general. The purpose of the systematic review was to analyze scholarly …
Data processing and text mining technologies on electronic medical records: a review
Currently, medical institutes generally use EMR to record patient's condition, including
diagnostic information, procedures performed, and treatment results. EMR has been …
diagnostic information, procedures performed, and treatment results. EMR has been …
[LIVRE][B] Supervised and unsupervised learning for data science
Supervised and unsupervised learning algorithms have shown a great potential in
knowledge acquisition from large data sets. Supervised learning reflects the ability of an …
knowledge acquisition from large data sets. Supervised learning reflects the ability of an …
Real-world data medical knowledge graph: construction and applications
Objective Medical knowledge graph (KG) is attracting attention from both academic and
healthcare industry due to its power in intelligent healthcare applications. In this paper, we …
healthcare industry due to its power in intelligent healthcare applications. In this paper, we …
Evaluating temporal relations in clinical text: 2012 i2b2 challenge
Abstract Background The Sixth Informatics for Integrating Biology and the Bedside (i2b2)
Natural Language Processing Challenge for Clinical Records focused on the temporal …
Natural Language Processing Challenge for Clinical Records focused on the temporal …
Entity recognition from clinical texts via recurrent neural network
Background Entity recognition is one of the most primary steps for text analysis and has long
attracted considerable attention from researchers. In the clinical domain, various types of …
attracted considerable attention from researchers. In the clinical domain, various types of …
Electronic health records-driven phenoty**: challenges, recent advances, and perspectives
With the completion of the Human Genome Project1 as well as recent advances in genomic
science and comparative biological studies, a new era of individualized medicine is evolving …
science and comparative biological studies, a new era of individualized medicine is evolving …
[HTML][HTML] Capturing the patient's perspective: a review of advances in natural language processing of health-related text
Background: Natural Language Processing (NLP) methods are increasingly being utilized to
mine knowledge from unstructured health-related texts. Recent advances in noisy text …
mine knowledge from unstructured health-related texts. Recent advances in noisy text …
Comparison of MetaMap and cTAKES for entity extraction in clinical notes
Background Clinical notes such as discharge summaries have a semi-or unstructured
format. These documents contain information about diseases, treatments, drugs, etc …
format. These documents contain information about diseases, treatments, drugs, etc …
Combining unsupervised, supervised and rule-based learning: the case of detecting patient allergies in electronic health records
Background Data mining of electronic health records (EHRs) has a huge potential for
improving clinical decision support and to help healthcare deliver precision medicine …
improving clinical decision support and to help healthcare deliver precision medicine …