Siemens Medical Solutions Usa, Inc.

Siemens Corporation

Cerner Innovation, Inc.

Siemens Corporate Research, Inc.

Siemens Medical Soultions Usa, Inc.

Sathyakama Sandilya

R Bharat Rao

Radu Stefan Niculescu

Arun Kumar Goel

Thomas R Warrick

Christopher Jude Amies

William Alexander Landi

Harm Jacob Scherpbier

Phan Hong Giang

Glenn Fung

Bharat R Rao

Brian Berenbach

A method for data sensitive filtering in a patient database searches includes providing a search criteria comprising one or more search locator fields, determining a retrieval formula from the search criteria that maximizes error tolerance in the search criteria while satisfying a predefined response time requirement, and retrieving candidate records from the database. If no retrieval formula can be found that satisfies the response time requirements, the method includes requesting additional search criteria, scoring each candidate record by comparing a search criteria locator field with a corresponding retrieved record field, and determining whether the score of the candidate record exceeds a predefined threshold. If the candidate score does exceed the threshold, the candidate record is added to a list of records to be returned in response to the search criteria.

System and method for data sensitive filtering of patient demographic record queries

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.

Patient data mining

A system and method for lung cancer screening is provided. The system includes a database including structured patient information for a patient population and a domain knowledge base including information about lung cancer; an individual patient record; and a processor for analyzing the patient record with data from the database to determine if a patient has indications of lung cancer. The method includes the steps of inputting patient-specific data into a patient record; performing at least one lung cancer screening procedure on a patient, wherein at least one result from at least one procedure is inputted into the patient record in a structured format; and analyzing the patient record with a domain knowledge base to determine if the patient has indications of lung cancer.

Patient data mining for lung cancer screening

A system and method for analyzing population-based patient information is provided. The method includes the steps of data mining a plurality of patient records using a domain knowledge base relating to a disease of interest; compiling the mined data into a plurality of structured patient records; inputting at least one patient criteria relating to the disease of interest; and extracting at least one structured patient record matching the at least one patient criteria. The system includes a data miner for mining information from the plurality of patient records using a domain knowledge base relating to a disease of interest and for compiling the mined data into a plurality of structured patient records; an interface for inputting at least one patient criteria relating to the disease of interest; and a processor adapted for extracting at least one of the structured patient records matching the at least one patient criteria.

Patient data mining with population-based analysis

The present invention provides systems and methods for automatically ensuring adherence to clinical guidelines during the course of patient treatments. A data source contains patient records, including records for patients being treated; a guidelines knowledge base contains clinical guidelines; and a quality adherence engine is configured to monitor adherence with the clinical guidelines for patients being treated. At least some of the patient records may include information obtained from mining unstructured patient data. The system includes an output component for outputting quality adherence information. The outputted quality adherence information may include reminders, including reminders to take clinical actions in accordance with the clinical guidelines. The outputted quality adherence information may also include warnings that the clinical guidelines have not been observed.

Patient data mining for quality adherence

The present invention provides a graphical user interface for presentation, exploration and verification of patient information. In various embodiments, a method is provided for browsing mined patient information. The method includes selecting patient information to view, at least some of the patient information being probabilistic, presenting the selected patient information on a screen, the selected patient information including links to related information. The selected patient information may include elements, factoids, and/or conclusions. The selected patient information may include an element linked to unstructured information. For example, an element linked to a note with highlighted information may be presented. Additionally, the unstructured information may include medical images and waveform information.

Patient data mining, presentation, exploration, and verification

A technique is provided for automatically generating performance measurement information. At least some of the obtained performance measurement information may be derived from unstructured data sources, such as free text physician notes, medical images, and waveforms. The performance measurement may be sent to a health care accreditation organization. The health care accreditation organization can use the performance measurement to evaluate a health care provider for its quality of patient care. Alternatively, performance measurement information can be provided directly to consumers.

Patient data mining for automated compliance

Systems and methods for automated processing of medical information in electronic patient medical record databases, wherein billing information (e.g., diagnosis codes, procedural codes) is automatically extracted from electronic patient medical records through comprehensive analysis of clinical information included in the patient medical records using a knowledge base of domain-specific criteria. The extracted billing information can be automatically processed for purposes of, e.g., medical claims correction, medical claims billing, quality assurance of recorded billing information, or claim reimbursement tracking.

Systems and methods for automated extraction and processing of billing information in patient records

A system and method for lung cancer screening is provided. The system includes a database including structured patient information for a patient population and a domain knowledge base including information about lung cancer; an individual patient record; and a processor for analyzing the patient record with data from the database to determine if a patient has indications of lung cancer. The method includes the steps of inputting patient-specific data into a patient record; performing at least one lung cancer screening procedure on a patient, wherein at least one result from the at least one procedure is inputted into the patient record in a structured format; and analyzing the patient record with a domain knowledge base to determine if the patient has indications of lung cancer.

A method for classifying features in a digital medical image includes providing a plurality of feature points in an N-dimensional space, wherein each feature point is a member of one of two sets, determining a classifying plane that separates feature points in a first of the two sets from feature points in a second of the two sets, transforming the classifying plane wherein a normal vector to said transformed classifying plane has positive coefficients and a feature domain for one or more feature points of one set is a unit hypercube in a transformed space having n axes, obtaining an upper bound along each of the n-axes of the unit hypercube, inversely transforming said upper bound to obtain a new rule containing one or more feature points of said one set, and removing the feature points contained by said new rule from said one set.

System and method for feature identification in digital images based on rule extraction

A system and method for optimizing database access for record linkage by tiling the space of record pairs are provided, the system including a processor, a segmentation and pairing unit in signal communication with the processor for segmenting database data into data segments and pairing the data segments into data quadrants, and a duplicate detection unit in signal communication with the processor for detecting duplicates for each quadrant; and the method including receiving database data, segmenting the database data into data segments, pairing the data segments into data quadrants, and detecting duplicates for each quadrant.

Optimizing database access for record linkage by tiling the space of record pairs

A method and system for determining patient states is provided. The method includes the steps of data mining a patient record using a domain knowledge base relating to a disease of interest; inputting the mined data into a model of the disease of interest; and determining a state of the patient based on the model. The system includes a data miner for mining information from a patient record using a domain knowledge base relating to a disease of interest; and a processor for creating a patient model of the disease of interest, processing the mined data in the model to determine a current state of the patient and future states for different courses of treatment, and recommending a therapy based on the determined future state.

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Cranbury, NJ, United States of America

Sathyakama Sandilya