Patents by Inventor Rabe'e Cheheltani

Rabe'e Cheheltani has filed for patents to protect the following inventions. This listing includes patent applications that are pending as well as patents that have already been granted by the United States Patent and Trademark Office (USPTO).

  • Patent number: 11960456
    Abstract: A graph-based clinical concept mapping algorithm maps ICD-9 (International Classification of Disease, Revision 9) and ICD-10 (International Classification of Disease, Revision 10) codes to unified Systematized Nomenclature of Medicine (SNOMED) clinical concepts to normalize longitudinal healthcare data to thereby improve tracking and the use of such data for research and commercial purposes. The graph-based clinical concept mapping algorithm advantageously combines a novel graph-based search algorithm and natural language processing to map orphan ICD codes (those without equivalents across codebases) by finding optimally relevant shared SNOMED concepts. The graph-based clinical concept mapping algorithm is further advantageously utilized to group ICD-9/10 codes into higher order, more prevalent SNOMED concepts to support clinical interpretation.
    Type: Grant
    Filed: February 25, 2020
    Date of Patent: April 16, 2024
    Assignee: IQVIA Inc.
    Inventors: Shaun Gupta, Frederik B. C. Dieleman, Daniel Homola, Adam Webber, Orla M. Doyle, Nadejda Leavitt, John Rigg, Patrick Long, Rabe'e Cheheltani
  • Publication number: 20210090745
    Abstract: An unbiased ETL (extract, transform, load) system for timed medical event prediction utilizes a rolling series of time-bound cross-sections of patient healthcare data. Patients may be labelled as belonging to one or more classes (e.g. positive or negative) for each cross-section in the series depending on current healthcare status. Rather than using a single snapshot, the unbiased ETL system employs multiple snapshots of patient medical histories to provide a capability to classify a patient at different points in time, as appropriate. Supervised learning for the system is thereby enabled over multiple different periods of a patient's medical journey which advantageously supports a more statistically robust medical event prediction model and eliminates several classes of bias. Additionally, the unbiased ETL system enables customization of a prediction window to account for lags in data collection, data processing, and length of use of the medical event predictions.
    Type: Application
    Filed: June 18, 2020
    Publication date: March 25, 2021
    Inventors: Nadejda Leavitt, John Rigg, Orla Doyle, Benjamin North, Adam Webber, Emin Ozkan, Suyin Lee, Valentina Salvatelli, Lachlan McLachlan, Patrick Long, Rabe'e Cheheltani
  • Patent number: 10940217
    Abstract: Nanoclusters comprising inorganic nanocrystals and a biodegradable polymer are disclosed. The inorganic nanocrystals have a mean particle size of 1 to 500 nm. The inorganic nanocrystals are contained within a core of the nanoclusters, on the surface of the nanoclusters, contained within a core of the nanoclusters, dispersed throughout the nanoclusters, or a combination thereof. The biodegradable polymer allows the inorganic nanocrystals to be excreted renally over a period of time. The nanoclusters can be used for medical imaging or other biomedical applications.
    Type: Grant
    Filed: March 18, 2015
    Date of Patent: March 9, 2021
    Assignees: The Trustees Of The University Of Pennsylvania, The Penn State Research Foundation
    Inventors: David Peter Cormode, Peter Chhour, Andrew Tsourkas, Harry Allcock, Rabe'e Cheheltani