Patent application number | Description | Published |
20080286273 | Knowledge-Based Proliferation Signatures and Methods of Use - The present invention provides methods and compositions for predicting patient responses to cancer treatment using a proliferation gene signature. These methods can comprise measuring in a biological sample from a patient the levels of gene expression of a group of the genes designated herein. The present invention also provides for microarrays that can detect expression from a group of genes. | 11-20-2008 |
20090080731 | System and Method for Multiple-Instance Learning for Computer Aided Diagnosis - A method for training a classifier for classifying candidate regions in computer aided diagnosis of digital medical images includes providing a training set of images, each image including one or more candidate regions that have been identified as suspicious by a computer aided diagnosis system. Each image has been manually annotated to identify malignant regions. Multiple instance learning is applied to train a classifier to classify suspicious regions in a new image as malignant or benign by identifying those candidate regions that overlap a same identified malignant region, grouping each candidate region that overlaps the same identified malignant region into a same bag, and maximizing a probability | 03-26-2009 |
20090130096 | Gene Signature of Early Hypoxia to Predict Patient Survival - The present invention provides methods and compositions for predicting patient responses to cancer treatment using hypoxia gene signatures. These methods can comprise measuring in a biological sample from a patient the levels of gene expression of a group of the genes designated herein. The present invention also provides for microarrays that can detect expression from a group of genes. | 05-21-2009 |
20100174557 | System and Method for Ranking Quality Improvement Factors in Patient Care - Quality improvement factors in patient care are ranked. Hospital performance is measured, such as a CMS measure. The variables and/or values relative contribution to quality of care is determined using medical records of the hospital. The variables and/or values are ranked according influence of the quality of care result. The ranking is performed by a given medical institution at a desired time rather than based on a broad study. The medical institution may regularly determine variables (e.g., admitting doctor) and/or values (e.g., doctor X) that are relevant to a decreased quality of care. Quality may be regularly improved using a software product. | 07-08-2010 |
20110059074 | Knowledge-Based Proliferation Signatures and Methods of Use - The present invention provides methods and compositions for predicting patient responses to cancer treatment using a proliferation gene signature. These methods can comprise measuring in a biological sample from a patient the levels of gene expression of a group of the genes designated herein. The present invention also provides for microarrays that can detect expression from a group of genes. | 03-10-2011 |
20110078145 | Automated Patient/Document Identification and Categorization For Medical Data - A method, including receiving a data source selection from a user or software application, the data source including medical information of a plurality of patients, receiving, from the user or software application, a data pattern that is related to a concept to be explored in the data source, querying the data source to find information that approximately matches the data pattern; and receiving the information from the data source, wherein the information includes unstructured data, assigning a classification to individual parts of the information based on the part's relationship to the data pattern, and outputting the classified information to the user or software application. | 03-31-2011 |
20110184761 | Method and Apparatus for Estimating Patient Populations - The methods and apparatuses of the present invention provide for a continuous abstraction of randomly sampled patient data and shortened data processing cycle times when an accurate sample population size is unknown at the beginning of the sampling process. The present invention estimates an initial medical patient population size for the purpose of randomly sampling that population. The estimated population size is calculated based on historical patient population data and is corrected at the end of the sample time period. Under-sampling is remediated at the end of the sample time period, during which continuous sampling of the patient data is carried out to provide interim and immediately available sampled patient data. Criteria for medical patient population sizing and sampling are provided by health care organizations responsible for administrating health care quality improvement standards. | 07-28-2011 |
20110295621 | Healthcare Information Technology System for Predicting and Preventing Adverse Events - An adverse event may be prevented by predicting the probability of a given patient to have or undergo the adverse event. The probability alone may prevent the adverse event by educating the patient or medical professional. The probability may be predicted at any time, such as upon entry of information for the patient, periodic analysis, or at the time of admission. The probability may be used to generate a workflow action item to reduce the probability, to warn, to output appropriate instructions, and/or assist in avoiding adverse event. The probability may be specific to a hospital, physician group, or other medical entity, allowing prevention to focus on past adverse event causes for the given entity. | 12-01-2011 |
20110295622 | Healthcare Information Technology System for Predicting or Preventing Readmissions - Hospital readmissions may be prevented. Readmission is prevented by predicting the probability of a given patient to be readmitted. The probability alone may prevent readmission by educating the patient or medical professional. The probability may be predicted during a patient stay and used to generate a workflow action item to reduce the probability, to warn, to output appropriate instructions, and/or assist in avoiding readmission. The probability may be specific to a hospital, physician group, or other entity, allowing prevention to focus on past readmission causes for the given entity. | 12-01-2011 |
20120041784 | Computerized Surveillance of Medical Treatment - Medical treatment is automatically surveyed. Drugs or other treatments may be monitored post-market. This surveillance may be accomplished in two ways: (1) Identify patients that potentially match templates consistent with possible adverse reactions, possibly including adverse reactions not associated with the treatment. Potentially, if the match is good enough, a single patient may be sufficient to raise an alert. Alternately, multiple patients partially matching a template may cause an alert. (2) Identify patient clusters with unusual patterns. Multiple patients associated with greater rates of adverse events or event severity not expected with the treatment are identified. The data for surveillance is acquired from multiple sources, so may be more comprehensive for early recognition of adverse effects. Data gathering and surveillance are computerized, so early, cost effective recognition may be more likely. | 02-16-2012 |
20120065987 | Computer-Based Patient Management for Healthcare - Computer-based patient management is provided for healthcare. Patient data is used to determine a severity, assign a patient to a corresponding diagnosis-related group, and provide a timeline for care at a medical facility. Reminders or alerts are sent to maintain the timeline for more cost effective care. Reminders, suggestions, transitions between care givers, scheduling and other risk management actions are performed. As more data becomes available as part of the care, the care and timeline may be adjusted automatically for more efficient utilization of resources. Accountable care optimization is provided as part of case management. Automated care before any injury or illness and automated care after discharge is provided to optimize the health and costs for a patient. The patient is assigned to the cohort based on the patient data. | 03-15-2012 |
20120065997 | Automatic Processing of Handwritten Physician Orders - Physician orders are automatically processed. Rather than requiring entry with a user interface in a computerized order entry system, physician orders may be handwritten on a piece of paper or entered on another handwriting device. The orders are scanned or transmitted. Using a lexicon limited to the vocabulary of possible orders, handwriting recognition is applied to the scanned order. By limiting the lexicon, the accuracy of the optical character recognition may be increased. The lexicon may be further limited by determining a diagnosis and/or treatment or imaging modality for the patient and selecting a lexicon limited to orders associated with the diagnosis or modality. The recognized order is then implemented by the computerized order entry system. | 03-15-2012 |
20140088989 | Rapid Learning Community for Predictive Models of Medical Knowledge - A predictive model of medical knowledge is trained from patient data of multiple different medical centers. The predictive model is machine learnt from routine patient data from multiple medical centers. Distributed learning avoids transfer of the patient data from any of the medical centers. Each medical center trains the predictive model from the local patient data. The learned statistics, and not patient data, are transmitted to a central server. The central server reconciles the statistics and proposes new statistics to each of the local medical centers. In an iterative approach, the predictive model is developed without transfer of patient data but with statistics responsive to patient data available from multiple medical centers. To assure comfort with the process, the transmitted statistics may be in a human readable format. | 03-27-2014 |
20140095201 | Leveraging Public Health Data for Prediction and Prevention of Adverse Events - An adverse event may be prevented by predicting the probability of a given patient to have or undergo the adverse event. The ability to predict the probability of the adverse event may be enhanced when a model is derived from public health data to categorize and propose values for medical record fields. The probability alone may prevent the adverse event by educating the patient or medical professional. The probability may be predicted at any time, such as upon entry of information for the patient, periodic analysis, or at the time of admission. The probability may be used to generate a workflow action item to reduce the probability, to warn, to output appropriate instructions, and/or assist in avoiding adverse event. The probability may be specific to a hospital, physician group, or other medical entity, allowing prevention to focus on past adverse event causes for the given entity. | 04-03-2014 |
20140095203 | MEDICAL WORKFLOW DETERMINATION AND OPTIMIZATION - Workflows for medical entities are determined and evaluated by determining a plurality of medical tasks based on an analysis of a plurality of electronic medical records of a medical entity. A workflow of the medical entity is determined based on a sequence of medical tasks, the sequence determined based on the analysis of the plurality of electronic medical records, and an evaluation of the workflow is performed based on a predefined criterion. | 04-03-2014 |
20140095204 | AUTOMATED MEDICAL COHORT DETERMINATION - Inclusion of a patient in a medical category is determined by triggering an analysis of an electronic medical record of the patient in response to an input of data into the electronic medical record. Identifying characteristics that indicate inclusion in the medical category with the analysis, and determining a probability the patient belongs to the medical category based on the identified characteristics. | 04-03-2014 |
20140095205 | AUTOMATED MAPPING OF SERVICE CODES IN HEALTHCARE SYSTEMS - Automatic mapping of semantics in healthcare is provided. Data sets have different semantics (e.g., Gender designated with M and F in one system and Sex designated with 1 or 2 in another system). For semantic interoperability, the semantic links between the semantic systems of different healthcare entities are created (e.g., Gender=Sex and/or 1=F and 2=M) by a processor from statistics of the data itself. The distribution of variables, values, or variables and values, with or without other information and/or logic, is used to create a map from one semantic system to another. Similar distributions of other variable and/or values are likely to be for variables and/or values with the same meaning. | 04-03-2014 |
20140095206 | ADAPTIVE MEDICAL DOCUMENTATION SYSTEM - Adaptive medical data collection for medical entities may involve triggering an analysis of electronic records in response to information input into an Electronic Medical Record (EMR) of a patient. Determining a potential condition for the patient based on the analysis. Identifying additional information indicated as relevant to the potential condition of the patient, and generating a request for the identified additional information. | 04-03-2014 |
20140207492 | Healthcare Information Technology System for Predicting or Preventing Readmissions - Hospital readmissions may be prevented. Readmission is prevented by predicting the probability of a given patient to be readmitted. The probability alone may prevent readmission by educating the patient or medical professional. The probability may be predicted during a patient stay and used to generate a workflow action item to reduce the probability, to warn, to output appropriate instructions, and/or assist in avoiding readmission. The probability may be specific to a hospital, physician group, or other entity, allowing prevention to focus on past readmission causes for the given entity. | 07-24-2014 |
20140214451 | Adaptive Medical Documentation System - Adaptive medical data collection for medical entities may involve managing content by receiving data indicating a context, identifying at least one application or knowledge base associated with the context, designating the identified application or knowledge base as active, and accessing the active application or knowledge base to provide information at an interface point for a medical professionals and a patient. | 07-31-2014 |
20150081326 | Healthcare Process Management Using Context - Rather than modify or create, by programmers, a new workflow specifically for each healthcare provider, a workflow provider creates an abstract workflow appropriate for any or many healthcare providers. Using context about a specific healthcare provider, a computer automatically adapts the abstract workflow to the healthcare provider. Using patient context, the computer may automatically schedule tasks of the adapted workflow appropriate for the specific patient and the specific healthcare provider. The patient and healthcare provider context may be monitored for any changes that alter the workflow, and the system may reschedule the tasks as appropriate. | 03-19-2015 |
20150106125 | Automated Mapping of Service Codes in Healthcare Systems - Mapping of semantics in healthcare may involve accessing first transaction data of a first healthcare entity in a first database, the first transaction data corresponding to a collection of a first number of fields defined for a condition using a first semantic system to store information and calculating a first distribution of information in the first transaction data. Mapping may also involve accessing second transaction data of a second healthcare entity in a second database, the second transaction data corresponding to a second semantic system different than the first semantic system and the second database comprising a second number of fields using the second semantic system to store information, the second number of fields larger than the first number of fields and calculating a second distribution of information in the second transaction data. The distributions may then be compared and a map relating the semantic systems may be generated. | 04-16-2015 |
20150294088 | Patient Summary Generation - Patient summary generation may involve receiving a request for summary data relating to treatment of a patient over a period of time and accessing a medical record of the patient to determine at least one condition of the patient for the period of time. Summary generation may also involve determining reporting categories relating to the at least one condition, identifying elements of the medical records associated with the reporting categories, determining data of the identified elements indicative of the summary data for the at least one condition, and compiling the summary data into a summary report. | 10-15-2015 |