iScite by Linguamaticsis our breakthrough innovation in scientific search that puts the precision and power of Linguamatics artificial intelligence (AI) technology directly into the hands of scientists, researchers and other knowledge workers. Bio-IT World Best of Show 2018 award winning product iScite, offers a modern, easy-to-use scientific search engine that provides intuitive access to AI-powered searches across key biomedical data sources and delivers insightful answers to search questions.
The story of Photo 51, Rosalind Franklin and how genotype-phenotype knowledge is being turned into actionable insights for precision medicine with help from Augmented Intelligence using Natural Language Processing.
There’s growing interest in the use of machine learning to solve challenges across the drug-discovery pipeline within the biopharmaceutical community. The availability of high quality data for training algorithms is vital to machine learning success - but much of this information is tied up in unstructured, or semi-structured text sources. Natural language processing (NLP) is the key to extracting the wealth of data hidden in unstructured text, and Linguamatics’ customers have been finding out first-hand what this approach can do for them.
Organizations are embracing the digital revolution, but digital transformation demands data transformation, in order to get the full value from disparate data across the organization. Integrating data from a variety of sources into a data warehouse or other data repository centralizes business-critical data, and speeds up finding and analyzing important data. The Extract, Transform, and Load (ETL) process of extracting data from source systems and bringing it into databases or warehouses is well established. While many ETL tools can handle structured data, very few can reliably process unstructured data and documents.
As healthcare continues to shift to value-based care, the use of big data analytics in healthcare and Artificial Intelligence (AI) techniques like Natural Language Processing (NLP) is essential technology for providers and payers as they work to make sense of the growing volume of unstructured data from EHRs, claims, notes, patient-reported outcomes, and social media.
Roughly 80% of clinical data is estimated to be in an unstructured form. NLP-based text analytics platforms like Linguamatics I2E enable unstructured text to be translated into discrete data fields by identifying the key concepts and their relationships in healthcare documentation.
iScite by Linguamaticsis our breakthrough innovation in scientific search that puts the precision and power of Linguamatics artificial intelligence (AI) technology directly into the hands of scientists, researchers and other knowledge workers. Bio-IT World Best of Show 2018 award winning product iScite, offers a modern, easy-to-use scientific search engine that provides intuitive access to AI-powered searches across key biomedical data sources and delivers insightful answers to search questions.
The story of Photo 51, Rosalind Franklin and how genotype-phenotype knowledge is being turned into actionable insights for precision medicine with help from Augmented Intelligence using Natural Language Processing.
There’s growing interest in the use of machine learning to solve challenges across the drug-discovery pipeline within the biopharmaceutical community. The availability of high quality data for training algorithms is vital to machine learning success - but much of this information is tied up in unstructured, or semi-structured text sources. Natural language processing (NLP) is the key to extracting the wealth of data hidden in unstructured text, and Linguamatics’ customers have been finding out first-hand what this approach can do for them.
Organizations are embracing the digital revolution, but digital transformation demands data transformation, in order to get the full value from disparate data across the organization. Integrating data from a variety of sources into a data warehouse or other data repository centralizes business-critical data, and speeds up finding and analyzing important data. The Extract, Transform, and Load (ETL) process of extracting data from source systems and bringing it into databases or warehouses is well established. While many ETL tools can handle structured data, very few can reliably process unstructured data and documents.
As healthcare continues to shift to value-based care, the use of big data analytics in healthcare and Artificial Intelligence (AI) techniques like Natural Language Processing (NLP) is essential technology for providers and payers as they work to make sense of the growing volume of unstructured data from EHRs, claims, notes, patient-reported outcomes, and social media.
Roughly 80% of clinical data is estimated to be in an unstructured form. NLP-based text analytics platforms like Linguamatics I2E enable unstructured text to be translated into discrete data fields by identifying the key concepts and their relationships in healthcare documentation.
