Patents by Inventor Uddeshya Upadhyay
Uddeshya Upadhyay 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).
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Patent number: 12367392Abstract: An apparatus (and/or method) for training machine-learning model to make determinations from mismatched channel signals, wherein the apparatus includes a processor and memory communicatively connected to the processor. The memory containing instructions configuring the processor to receive a first set of signals using a first number of channels, process the first set of signals to simulate a second set of signals from a second number of channels, train a signal conversion model using the first set of signals and the second set of signals, and output a set of converted signals having the first number of channels using the third set of signals and the trained signal conversion model.Type: GrantFiled: April 26, 2024Date of Patent: July 22, 2025Assignee: Anumana, Inc.Inventors: Shayan Ghosh, Yash Gupta, Shashi Kant, Rakesh Barve, Uddeshya Upadhyay
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Patent number: 12361327Abstract: A system for training machine learning models with unlabeled electrocardiogram signals, the system including a memory containing instructions configurating a processor to receive a plurality of electrocardiogram (ECG) data in a textual format, create one or more overlapping temporal patches from the plurality of ECG data, mask at least one temporal patch from the one or more overlapping temporal patches, pretrain an ECG machine learning model to predict the at least one masked temporal patch from the one or more overlapping temporal patches, adjust one or more parameter values of the ECG machine learning model as a function of the at least one predicted masked temporal patch and the at least one masked temporal patch and train the ECG machine learning model as a function of the one or more parameter values and a labeled set of ECG training data.Type: GrantFiled: May 16, 2024Date of Patent: July 15, 2025Assignee: Anumana, Inc.Inventors: Uddeshya Upadhyay, Mayank Sharma, Sairam Bade, Ashim Prasad, Rakesh Barve
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Patent number: 12322104Abstract: An apparatus for generating a three-dimensional (3D) model of cardiac anatomy via machine-learning, wherein the apparatus includes a process and a memory containing instructions configuring the processor to receive a set of images of a cardiac anatomy pertaining to a subject, generate an 3D data structure representing the cardiac anatomy as a function of the set of images using a cardiac anatomy modeling model, generate an initial 3D model of the cardiac anatomy, refine the generated initial 3D model of the cardiac anatomy as a function of the 3D data structure representing the cardiac anatomy, and generate a subsequent 3D model of the cardiac anatomy as a function of the refinement.Type: GrantFiled: June 21, 2024Date of Patent: June 3, 2025Assignee: Anumana, Inc.Inventors: Abhijith Chunduru, Uddeshya Upadhyay, Suthirth Vaidya, Sai Saketh Chennamsetty, Arjun Puranik
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Publication number: 20250157632Abstract: An apparatus for synthetizing medical images, wherein the apparatus includes a process and a memory containing instructions configuring the processor to receive a heart model related to a patient's heart, identify a region of interest within the heart model, wherein identifying the region of interest includes locating at least a point of view on the heart model and determining a view angle corresponding to the at least a point of view, wherein the at least a point of view and the corresponding view angle define at least one field of view that include at least a portion of the heart model, and generate at least a medical image as a function of the region of interest using an image generator, wherein the at least a medical image captures an anatomical structure of the at least a portion of the heart model.Type: ApplicationFiled: November 15, 2023Publication date: May 15, 2025Applicant: Anumana, Inc.Inventors: Abhijith Chunduru, Uddeshya Upadhyay, Suthirth Vaidya, Sai Saketh Chennamsetty, Arjun Puranik
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Publication number: 20250157628Abstract: An apparatus for synthetizing medical images, wherein the apparatus includes a process and a memory containing instructions configuring the processor to receive an organ model related to a patient's organ, identify a region of interest within the organ model, wherein identifying the region of interest includes locating at least a point of view on the organ model and determining a view angle corresponding to the at least a point of view, wherein the at least a point of view and the corresponding view angle define at least one field of view that include at least a portion of the organ model, and generate at least a medical image as a function of the region of interest using an image generator, wherein the at least a medical image captures an anatomical structure of the at least a portion of the organ model.Type: ApplicationFiled: August 28, 2024Publication date: May 15, 2025Applicant: Anumana, Inc.Inventors: Rakesh Barve, Abhijith Chunduru, Uddeshya Upadhyay, Suthirth Vaidya, Sai Saketh Chennamsetty, Arjun Puranik
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Publication number: 20250117929Abstract: An apparatus for generating a three-dimensional (3D) model of anatomical object via machine-learning, wherein the apparatus includes a process and a memory containing instructions configuring the processor to receive a set of images of an anatomical object pertaining to a subject, generate an 3D data structure representing the anatomical object as a function of the set of images using an anatomy modeling model, generate an initial 3D model of the anatomical object and refine the generated initial 3D model of the anatomical object as a function of the 3D data structure representing the anatomical object.Type: ApplicationFiled: August 28, 2024Publication date: April 10, 2025Applicant: Anumana, Inc.Inventors: Rakesh Barve, Abhijith Chunduru, Uddeshya Upadhyay, Suthirth Vaidya, Sai Saketh Chennamsetty, Arjun Puranik
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Publication number: 20250117928Abstract: An apparatus for generating a three-dimensional (3D) model of cardiac anatomy via machine-learning, wherein the apparatus includes a process and a memory containing instructions configuring the processor to receive a set of images of a cardiac anatomy pertaining to a subject, generate an 3D data structure representing the cardiac anatomy as a function of the set of images using a cardiac anatomy modeling model, generate an initial 3D model of the cardiac anatomy, refine the generated initial 3D model of the cardiac anatomy as a function of the 3D data structure representing the cardiac anatomy, and generate a subsequent 3D model of the cardiac anatomy as a function of the refinement.Type: ApplicationFiled: June 21, 2024Publication date: April 10, 2025Applicant: Anumana, Inc.Inventors: Abhijith Chunduru, Uddeshya Upadhyay, Suthirth Vaidya, Sai Saketh Chennamsetty, Arjun Puranik
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Publication number: 20250045129Abstract: An apparatus and method for unpaired time series to time series translation is disclosed. The apparatus comprises at least a processor configured to receive an automated analysis of a time series, convert that time series from its initial domain to a usable time series within another user-selected domain, then to validate the conversion against a confidence threshold.Type: ApplicationFiled: August 4, 2023Publication date: February 6, 2025Applicant: Anumana, Inc.Inventors: Uddeshya Upadhyay, Rakesh Barve, Shashi Kant, Sairam Bade, Ashim PRASAD, Shayan Ghosh
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Patent number: 12213774Abstract: An apparatus and method for locating a position of an electrode on an organ model. The apparatus includes a memory communicatively connected to at least a processor, wherein the memory contains instructions configuring the at least a processor to receive an organ model configured to digitally represent an organ, receive a set of sensor data from at least a sensor including an ultrasound sensor, determine an electrode position within the organ model as a function of the set of sensor data using a position machine-learning module, wherein determining the electrode position includes determining a model position within the organ model as a function of the set of sensor data and determining the electrode position within the model position of the organ model as a function of the set of sensor data and add a visual marker onto the electrode position in the model position of the organ model.Type: GrantFiled: January 2, 2024Date of Patent: February 4, 2025Assignee: nference, Inc.Inventors: Murali Aravamudan, Rakesh Barve, Suthirth Vaidya, Uddeshya Upadhyay, Abhijith Chunduru, Arjun Puranik, Sai Saketh Chennamsetty
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Patent number: 12217361Abstract: An apparatus and method for generating a three-dimensional (3D) model of cardiac anatomy including an overlay. The apparatus includes at least a processor configured receive a set of images of a cardiac anatomy pertaining to a subject, generate a set of shape parameters based on the set of images, wherein generating the set of shape parameters includes receiving cardiac geometry training data including a plurality of image sets as input correlated to a plurality of shape parameter sets as output, training a shape identification model using the cardiac geometry training data, and generating the set of shape parameters using the shape identification model, generate a 3D model of the cardiac anatomy based on the set of shape parameters, generate a map by determine a level of uncertainty at each location of a plurality of locations on the generated 3D model, and overlay the map onto the 3D model.Type: GrantFiled: January 30, 2024Date of Patent: February 4, 2025Assignee: Anumana, Inc.Inventors: Abhijith Chunduru, Uddeshya Upadhyay, Suthirth Vaidya, Sai Saketh Chennamsetty, Arjun Puranik
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Patent number: 12154245Abstract: Apparatus for visualization within a three-dimensional (3D) model and methods used therein are described, wherein the apparatus includes a processor and a memory communicatively connected to the processor, wherein the memory includes instructions configuring the processor to receive a query image, extract neural network encodings from the received query image, query a synthetic image repository for at least a matching synthetic image, and display an estimated region of interest within the 3D model, wherein the synthetic image repository includes a plurality of synthetic images and their extracted neural network encodings, each synthetic image therein corresponds to a region of interest in the 3D model, and querying the synthetic image repository includes comparing the extracted neural network encodings between the query image and synthetic images.Type: GrantFiled: April 26, 2024Date of Patent: November 26, 2024Assignee: Anumana, Inc.Inventors: Rakesh Barve, Uddeshya Upadhyay, Abhijith Chunduru, Suthirth Vaidya, Arjun Puranik, Sai Saketh Chennamsetty
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Patent number: 12154273Abstract: An apparatus for generating a three-dimensional (3D) model of cardiac anatomy via machine-learning, wherein the apparatus includes a process and a memory containing instructions configuring the processor to receive a set of images of a cardiac anatomy pertaining to a subject, generate an 3D data structure representing the cardiac anatomy as a function of the set of images using a cardiac anatomy modeling model, generate an initial 3D model of the cardiac anatomy, refine the generated initial 3D model of the cardiac anatomy as a function of the 3D data structure representing the cardiac anatomy, and generate a subsequent 3D model of the cardiac anatomy as a function of the refinement.Type: GrantFiled: October 4, 2023Date of Patent: November 26, 2024Assignee: Anumana, Inc.Inventors: Uddeshya Upadhyay, Suthirth Vaidya, Sai Saketh Chennamsetty, Arjun Puranik, Abhijith Chunduru
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Publication number: 20240206821Abstract: An apparatus for predicting a physiological indicator is disclosed. The apparatus comprises a processor and a memory communicatively connected to the at least a processor. The memory instructs the processor to receive a time series input from a user. The memory instructs the processor to predict a physiological indicator as a function of the time series input using a prediction machine learning model. The memory instructs the processor to generate an uncertainty metric as a function of the physiological indicator. Wherein determining the physiological indicator includes receiving a plurality of prediction training data. Determining the physiological indicator includes fitting the plurality of prediction training data with a kernel density estimate. Determining the physiological indicator additionally includes training the prediction machine learning model using a plurality of prediction training data.Type: ApplicationFiled: November 27, 2023Publication date: June 27, 2024Applicant: nference, Inc.Inventors: Uddeshya Upadhyay, Sairam Bade, Melwin Babu, Ashim Prasad, Arjun Puranik, Rakesh Barve, Murali Aravmudan