"Text Mining and Information Retrieval" and "Biomedical Informatics Standards" courses at ABP
During 2014, we have launched several courses related to Medicine and Research but also related to Biomedical Informatics. Before finishing 2014, we want to launch two short courses more on Biomedical Informatics. In this case we present Text Mining and Information Retrieval and Biomedical Informatics Standards.
Text mining, also referred to as text data mining, roughly equivalent to text analytics, refers to the process of deriving high-quality information from text. High-quality information is typically derived through the devising of patterns and trends through means such as statistical pattern learning.
Text mining usually involves the process of structuring the input text (usually parsing, along with the addition of some derived linguistic features and the removal of others, and subsequent insertion into a database), deriving patterns within the structured data, and finally evaluation and interpretation of the output.
'High quality' in text mining usually refers to some combination of relevance, novelty, and interestingness. Typical text mining tasks include text categorization, text clustering, concept/entity extraction, production of granular taxonomies, sentiment analysis, document summarization, and entity relation modeling (i.e., learning relations between named entities).
This course aims to provide a brief introduction to the basic Text Mining concepts.
On the other hand, the task of transmitting or linking data across multiple biomedical data sources is often difficult because of the multitude of different formats and systems that are available for storing data.
Standard methods are thus needed for both representing and exchanging information across disparate data sources to link potentially related data across the spectrum of translational medicine -from laboratory data at the bench to patient charts at the bedside to linkage and availability of clinical data across a community to the development of aggregate statistics of populations.
These standards need to accommodate the range of heterogeneous data storage systems that may be required for clinical or research purposes, while enabling the data to be accessible for subsequent linkage and retrieval. Standards are thus an essential element in the representation of data in a form that can be readily exchanged with other systems.
This other course presents some of the most used standards in biomedice nowadays as HL7 (Electronic Health Records) and vocabularies as SNOMED or MeSH.
Enrol to these courses to learn a little bit more about Biomedical Informatics!!