General Electric Company

Michigan State University

Amazon Technologies, Inc.

Gokul Swamy

Ramakrishna Mukkamala

Sahika Genc

Tongtong Li

Qi Ling

Rui Li

Hariharan Ravishankar

Cynthia Elizabeth Landberg Davis

Ying Fan

Manoharan Venugopal

Abhijit Vishwas Patil

Megha Navalgund

Hae Won Lim

Rajashekar Venkatachalam

Ashish Rao

Navneeth Subramanian

Avik Ghosh

Nitya Subramaniam

Amod Jai Ganesh Anandkumar

Nicholas Bari Olivier

Aditya Saha

Systems, methods, and computer-readable media are disclosed for determining product attribute sequences using quantitative values and predicting product performance. In one embodiment, an example method may include determining, by one or more computer processors coupled to at least one memory, a first textual product attribute value for a first product for which to predict product performance, the first product associated with a first product category, determining a first product demand model for the first product category, the first product demand model including at least one algorithm configured to output predicted product performance, determining a first numeric product attribute sequence for the first product using the first textual product attribute value and the first product demand model, the first numeric product attribute sequence including a first numeric product attribute value and a second numeric product attribute value, and determining a first textual product attribute sequence for the first product.

Determining product attribute sequences using quantitative values

A method for determining a respiration rate of a subject, includes receiving a first signal and a second signal, each signal being representative of a physiological parameter of the subject. The method includes removing a cardiac artifact signal from the first signal and the second signal to generate a first processed signal and a second processed signal respectively. The method includes removing a motion artifact signal from the first processed signal and the second processed signal to generate a first periodic signal and the second processed signal respectively. The method further includes removing a residual noise signal from the first periodic signal and the second periodic signal to generate a first noise free signal and the second noise free signal respectively. The method includes generating a combined value from a first value and a second value based on the first noise free signal and the second noise free signal respectively.

Method and system for determining respiration rate

A method is provided for determining a central aortic pressure (AP) wave-form for a subject. The method includes measuring a peripheral artery pressure (PAP) waveform from the subject, employing a distributed model to define a pressure-to-pressure transfer function relating PAP to AP and a pressure-to-flow transfer function relating PAP to a central arterial flow in terms of the same unknown parameters, estimating the unknown parameters by finding the pressure-to-flow transfer function, which when applied to the measured PAP waveform, minimizes the magnitude of the central arterial flow waveform during diastole, and applying the pressure-to-pressure transfer function with the estimated parameters to determine an AP waveform for the subject.

Methods and apparatus for determining a central aortic pressure waveform from a peripheral artery pressure waveform

A method is provided for determining a central aortic pressure waveform. The method includes: measuring two or more peripheral artery pressure waveforms; analyzing the signals so as to extract common features in the measured waveforms; and determining an absolute central aortic pressure waveform based on the common features.

Method and apparatus for determining a central aortic pressure waveform

Embodiments of the disclosure are directed to a system for analysis of respiratory distress in hospitalized patients. The system performs multi-parametric simultaneous analysis of respiration rate (RR) and pulse oximetry (SpO) data trends in order to gauge patterns of patient instability pertaining to respiratory distress. Three patterns in SpOand RR are used along with LOWESS algorithm and Chauvenets criteria for outlier rejection to obtain robust short term and long term trends in RR and SpO. Pattern analysis detects the presence of any one of three pattern types proposed. Further, a learning paradigm is introduced to find unknown instances of respiratory distress. This algorithm in conjunction with the learning model allows early detection of respiratory distress in hospital ward and ICU patients.

Respiratory stress detection

A computer-implemented method for analyzing a fetal ultrasound image includes accessing a first statistical model calculated from training data representing shapes of conforming fetal abdominal tissue exemplars and accessing image data representing a scan plane in an ultrasound image. The method further includes identifying a region of interest including an abdomen in the scan plane using the first statistical model, accessing a second statistical model calculated from training data representing shapes of conforming fetal anatomical structure exemplars, determining whether one or more anatomical structures are present within the region of interest using the second statistical model, and assigning a rating to the scan plane based on the presence of the one or more anatomical structures in the region of interest. The anatomical structures may include a stomach and/or a portal vein. The method may include calculating an estimated circumference of the abdomen.

Methods and systems for automated soft tissue segmentation, circumference estimation and plane guidance in fetal abdominal ultrasound images

A system for providing non-invasive ultrasound based treatment to a region of interest is provided. The system comprises an imaging unit for imaging one or more tissue types in the region of interest, an image processing unit that is configured to identify the one or more tissue types in the region of interest, an ultrasound transducer that is configured to focus an ultrasound beam to ablate at least a portion of the identified tissues, and a controller unit that controls a delivery of the ultrasound beam to the region of interest.

Systems and methods for automatically identifying and segmenting different tissue types in ultrasound images

Method and apparatus for determining central aortic pressure waveform

A method for processing a radiographic image of a scanned object is provided. The method comprises acquiring radiographic image data corresponding to a scanned object and identifying one or more regions of interest in the radiographic image data corresponding to the scanned object. The method further comprises performing an image-contrast comparison of the radiographic image data corresponding to the scanned object and one or more reference radiographic images, to identify one or more defects in the radiographic image data corresponding to the scanned object.

Method and system for identifying defects in a radiographic image of a scanned object

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Bengaluru, India

Gokul Swamy