International Business Machines Corporation

Patrick W Fink

Philip E Parker

Kristin E McNeil

David Blake Werts

A computer-implemented method includes receiving a rule, wherein the rule includes at least one token, and receiving at least two dictionaries, wherein the at least two dictionaries include at least one general language dictionary and at least one domain-specific dictionary for a domain. The computer-implemented method further includes, for each of the at least one token, selecting at least one word at random from at least one of the at least two dictionaries and adding the at least one word to a test data line, such that the test data line includes a candidate statement conforming to the rule. The computer-implemented method further includes filtering the candidate statement based on a domain-specific model for the domain and including the candidate statement in training data provided to a machine learning model. A corresponding computer program product and computer system are also disclosed.

Generating training data for machine learning

A method, a processing device, and a computer program product are provided. Unstructured text may be analyzed to identify medical condition information of multiple occurrences of a medical condition for at least one subject. Times and geographic locations corresponding to the multiple occurrences of the medical condition may be obtained. Environmental information that corresponds to the times and the geographic locations of the multiple medical condition occurrences, may be retrieved. Correlations between the medical condition information and the retrieved environmental information for the at least one subject may be determined. Environmental factors affecting the medical condition, based on the determined correlations, are identified.

Determining correlation between medical symptoms and environmental factors

Detecting and incorporating formatting characteristics within natural language processing analytics. Source documents are ingested and the markup formatting language is identified by the program. Once identified, the markup language is parsed and examined for formatting characteristics, embedded notes, comments and other metadata. The formatting characteristics of the plain text are extracted, along with the plain text, and converted into a common analysis structure (CAS), or CAS-equivalent structure, which annotates the natural language text together with its respective formatting characteristics. The CAS or CAS-equivalent structures are stored and sent to a natural language processing pipeline for further analysis via complex algorithms and rules. The natural language processing results data are curated to reflect meaningful analysis of the extracted CAS or CAS-equivalent structure.

Natural language processing of formatted documents

A method, a processing device, and a computer program product are provided. At least one processing device correlates textual medical information related to the subject with characteristics of an image of a medical condition of the subject to generate a subject signature. The at least one processing device compares the subject signature with multiple reference signatures to determine at least one reference signature corresponding to the subject signature. Each reference signature is associated with a corresponding medical condition and is generated by correlating textual medical information regarding the corresponding medical condition with characteristics of an image of the corresponding medical condition. The at least one processing device identifies the medical condition of the subject based on the medical conditions associated with the determined at least one reference signature. Information is provided regarding the identified medical condition of the subject.

Image processing and text analysis to determine medical condition

A computer system gleans data from patient records and clinical trial descriptions using NLP techniques. NLP annotation data is used to generate clinical trial feature vectors and patient feature vectors. Clinical trial feature vectors and patient feature vectors are compared to match appropriate patient candidates with clinical trial openings.

Identifying potential patient candidates for clinical trials

Topic summaries related to a selection of text in an electronic document may be generated and presented. A topic summary application receives the user-selected text and identifies entities in the text using natural language processing. Using natural language processing, the summary application also identifies related entities and associated text phrases in a remaining portion of the electronic document. The remaining portion may be a portion of the document that precedes the user-selected text, so that a summary generated therefrom may be used to refresh the memory of the user while not revealing information that the user has not yet encountered. In addition, the summary application determines semantically important text phrases using text analytics and generates a summary, presented to the user in a pop-up window, of most frequently correlated related entities along with text phrases that are semantically important.

Automatic discovery and presentation of topic summaries related to a selection of text

A method for providing annotation summaries for annotations is provided. The method may include receiving annotations associated with analyzed unstructured data. The method may further include sorting the received annotations. Additionally, the method may include receiving focal points on the analyzed unstructured data. The method may also include extracting the sorted annotations associated with the focal points. The method may further include normalizing terms and phrases associated with the extracted annotations. The method may also include determining topics based on the normalized terms and phrases associated with the extracted annotations. The method may further include grouping the extracted annotations based on the determined topics. The method may also include summarizing the grouped annotations to generate a summarized annotation. The method may further include replacing the extracted annotations with the summarized annotation. The method may also include presenting the summarized annotation in place of the extracted annotations.

Weighted annotation evaluation

According to an embodiment of the present invention, a system dynamically produces a document with transformed terms associated with a geographic location, and comprises a computer system including at least one processor. The system analyzes a retrieved document to identify one or more terms with equivalent expressions in the same natural language. Each of the identified terms is transformed into an equivalent expression based on at least a geographic location associated with a user. The system produces a transformed document by replacing the identified one or more terms in the retrieved document with the equivalent expressions associated with the geographic location. Embodiments of the present invention further include a method and computer program product for dynamically producing a document with transformed terms for a geographic location in substantially the same manner described above.

Dynamic token translation for network interfaces

A method, a processing device, and a computer program product are provided. Via at least one processing device, each text file is selected from a collection of text files, wherein the collection of text files has an intensity with respect to negative sentiment toward a common issue. At least one profile algorithm is performed, each calculating a corresponding profile score for that text file. At least one corresponding profile score of the text files of the collection are combined to produce an aggregated profile score for each of at least one profile algorithm. The aggregated profile score of each of the at least one profile algorithm for the collection is stored. A signature for the collection of text files includes the aggregated profile score of each of the at least one profile algorithm for the collection.

Text analysis on unstructured text to identify a high level of intensity of negative thoughts or beliefs

Techniques disclosed herein describe generating annotations for text content rendered on a web browser. The web browser is configured with a content analytics plug-in configured to receive content to render in the web browser. The content itself includes unstructured text. The content analytics plug-in evaluates the unstructured text using content analytics and natural language processing (NLP) techniques to characterize the meaning of one or more passages in the unstructured text. The content analytics plug-in then generates annotations based on the characterizations to display when the web browser renders the content.

Growing community of inventors

Charlotte, NC, United States of America

Patrick W Fink