Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Background: Text-processing of unstructured biomedical text has become crucial to pharma companies, both with regards to legacy as ll as topical documentation. The Apache Unstructured Information Management Applications (UIMA) framework addresses general information extraction requirements.  present in this poster two use cases of using UIMA for specific unstructured biomedical information extraction tasks in pharma companies. The first use case requires extraction of values belonging to specific fields from legacy clinical study documents. These fields could be diverse, examples being study duration, study population, study arm, completion date and co-morbidity. The second use case deals with accurate propagation of drug label information to digital channels such as drug-specific bsites. Due to the increased importance of such bsites and mobile applications, pharma companies are looking at text-processing solutions to keep information in such channels accurate and up-to-date.
['Aditya Rao', 'Thomas Joseph', 'Vangala Govindakrishnan Saipradeep', 'Rajgopal Srinivasan']
I am writing a research paper on a idea UIMA based solution in pharma text
[{"from": "human", "value": "I am writing a research paper on a idea UIMA based solution in pharma text"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: Background: Text-processing of unstructured biomedical text has become crucial to pharma companies, both with regards to legacy as ll as topical documentation. The Apache Unstructured Information Management Applications (UIMA) framework addresses general information extraction requirements.  present in this poster two use cases of using UIMA for specific unstructured biomedical information extraction tasks in pharma companies. The first use case requires extraction of values belonging to specific fields from legacy clinical study documents. These fields could be diverse, examples being study duration, study population, study arm, completion date and co-morbidity. The second use case deals with accurate propagation of drug label information to digital channels such as drug-specific bsites. Due to the increased importance of such bsites and mobile applications, pharma companies are looking at text-processing solutions to keep information in such channels accurate and up-to-date."}]