| Patent application number | Description | Published |
|---|
| 20080228769 | Medical Entity Extraction From Patient Data - Members of a medical entity class are extracted from patient data. A semi-supervised approach uses one or more initial medical terms such as terms from an ontology, for a given category or medical canonical entity. A larger set of medical terms is extracted from the medical information. In one example, the extraction is performed using lexical surface form features, rather than syntactical parsing. | 09-18-2008 |
| 20080240425 | Data De-Identification By Obfuscation - Medical or other data is de-identified by obfuscation. Located instances are replaced. By replacing with values in a same format and level of generality, multiple possible identifications—the replacement values and the instances not located—are provided in the data, obfuscating the original identification. By replacing as a function of a probability, the resulting data set has different instances distributed in a way making identification of the actual or original instances not located by searching more difficult. | 10-02-2008 |
| 20080288292 | System and Method for Large Scale Code Classification for Medical Patient Records - A method for training classifiers for ICD-9 patient codes includes providing a set of documents regarding patient hospital visits, combining the documents for each patient visit to create a hospital visit profile, defining a feature as an ngram with a frequency of occurrence greater or equal to a predetermined value that does not appear in a standard list of ngrams, processing the profiles to remove redundancy at a paragraph level and perform tokenization and sentence splitting, performing feature selection, randomly dividing the documents into training, validation, and test sets, and training a set of binary classifiers using a weighted ridge regression, each binary classifier targeting a single ICD-9 code using the training set, wherein each classifier is adapted to determining a specific ICD-9 code by analyzing a patient's hospital records. | 11-20-2008 |
| 20090024615 | System and Method for Creating and Searching Medical Ontologies - A method for creating and searching medical ontologies includes providing a semi-structured information source comprising a plurality of articles linked to each other, each article having one or more sections and each article is associated with a concept, creating a directed unlabeled graph representative of the information source, providing a plurality of labels, labeling a subset of edges, and assigning each unlabeled edge an equal probability of being assigned one of the labels. For each node, the probability of each outgoing edge is updated by smoothing each probability by an overall probability distribution of labels over all outgoing edges of each node, and the probability of each incoming edge is updated the same way. A label with a maximum probability is assigned to an edge if said maximum probability is greater than a predetermined threshold to create a labeled graph. | 01-22-2009 |
| 20090055183 | System and Method for Text Tagging and Segmentation Using a Generative/Discriminative Hybrid Hidden Markov Model - A method for sequence tagging medical patient records includes providing a labeled corpus of sentences taken from a set of medical records, initializing generative parameters θ and discriminative parameters {tilde over (θ)}, providing a functional LL−C×Penalty, where LL is a log-likelihood function | 02-26-2009 |
| 20090106238 | Contextual Searching of Electronic Records and Visual Rule Construction - A web-based system for visual construction of logical rules includes a server, a network, and client operatively connected to the server via the network. The server includes a database and a search engine. The client includes a web-based visual rule building application including selectable windows for displaying and visually editing terms, logical operators, logical rules for storage in the database. The logical rules are generated by visually selecting at least one of the terms and logical operators from the windows. The server may further include a search engine configured to perform at least one of a direct search or a contextual search for an entered query string in records stored in the database and the client may include a visual interface for displaying results of the searches. The search results generated by the search engine may be stored as terms in the database for subsequent rule generation. | 04-23-2009 |
| 20090259487 | Patient Data Mining - The present invention provides a data mining framework for mining high-quality structured clinical information. The data mining framework includes a data miner that mines medical information from a computerized patient record (CPR) based on domain-specific knowledge contained in a knowledge base. The data miner includes components for extracting information from the CPR, combining all available evidence in a principled fashion over time, and drawing inferences from this combination process. The mined medical information is stored in a structured CPR which can be a data warehouse. | 10-15-2009 |
