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US Patent 10499857 Medical protocol change in real-time imaging

Patent 10499857 was granted and assigned to DeepRadiology Corp on December, 2019 by the United States Patent and Trademark Office.

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Patent abstractTimelineTable: Further ResourcesReferences
Is a
Patent
Patent

Patent attributes

Patent Applicant
DeepRadiology Corp
DeepRadiology Corp
Current Assignee
DeepRadiology Corp
DeepRadiology Corp
Patent Jurisdiction
United States Patent and Trademark Office
United States Patent and Trademark Office
Patent Number
10499857
Patent Inventor Names
Kim Nguyen20
Robert Burnham Lufkin20
Jameson Tyler Merkow20
Date of Patent
December 10, 2019
Patent Application Number
15709293
Date Filed
September 19, 2017
Patent Citations
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US Patent 10249042 Method and apparatus for providing medical information service on basis of disease model
1
Patent Citations Received
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US Patent 12136484 Method and apparatus utilizing image-based modeling in healthcare
2
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US Patent 11521716 Computer-implemented detection and statistical analysis of errors by healthcare providers
3
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US Patent 11699236 Systems and methods for the segmentation of multi-modal image data
4
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US Patent 11776130 Progressively-trained scale-invariant and boundary-aware deep neural network for the automatic 3D segmentation of lung lesions
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US Patent 11423284 Subgraph tile fusion in a convolutional neural network
5
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US Patent 11928817 Method for filtering normal medical image, method for interpreting medical image, and computing device implementing the methods
6
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US Patent 12014807 Automated report generation using artificial intelligence algorithms
7
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US Patent 11476004 System capable of establishing model for cardiac ventricular hypertrophy screening
...
Patent Primary Examiner
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Wesley J Tucker
Patent abstract

Methods and systems for medical diagnosis by machine learning are disclosed. Imaging data obtained from different medical techniques can be used as a training set for a machine learning method, to allow diagnosis of medical conditions in a faster a more efficient manner. A three-dimensional convolutional neural network can be employed to interpret volumetric data available from multiple scans of a patient. The imaging data can be analyzed in real-time to prescribe additional testing while the patient is still within the medical facility.

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