Koninklijke Philips Corporation N.V.

Cornelis Van Zon

Ali Akbar Ahmad Samadani

Taiyao Wang

Zhun Zhong

Francesco Vicario

Shaomin Peng

Walid S I Ali

Ikaro Garcia Araujo Da Silva

Walid S Ibrahim Ali

Methods and systems for protecting digital client data transmitted to a computing cloud () for data processing ensure privacy of the client data by transmitting only scrambled client data to the computing cloud and never storing descrambled client data in the computing cloud. To the extent that descrambling is necessary for processing the client data with the computing cloud, descrambling is embedded in the processing so that descrambled client data is never output or stored by the computing cloud.

Privacy-safe-cloud-based computer vision

A CDS system including a controller extracting EHRs of an IHG and selecting SMs to form a target patient database, capturing a time interval between each subsequent record for each of the measurements defined by the SMs, computing hospital level features including statistics on the distribution of the captured time intervals for each of the measurements, clustering the plurality of hospitals of the IHG in accordance with the computed hospital level features, determining whether an other hospital is within a threshold distance to a closest one of the plurality of clusters; placing the other hospital in the closest cluster when it is determined that the other hospital is within the threshold distance, and placing the other hospital in a new cluster when it is determined that the other hospital is not within the threshold distance.

Incremental clustering and hierarchy formation system for clinical decision support (CDS) system development and method of operation thereof

Described herein are methods, devices and systems for predicting ventilator associated events (VAEs). In an example, data of a patient including one or more features useful in predicting VAEs is accessed and the features are extracted. The extracted features are evaluated automatically to determine a probability that a VAE will occur. If it is determined, based on the evaluating, that a VAE has a probability of occurring that exceeds a threshold, an indication that the VAE is predicted to occur is provided. Other examples are disclosed and claimed.

Prediction of ventilator-associated events (VAEs)

Described herein are methods, devices and systems for predicting ventilator associated pneumonia (VAP). In an example, data of a patient including one or more features useful in predicting VAPs are accessed and the features are extracted. A model is activated based on a time parameter associated with mechanical ventilation or length of stay in ICU. The extracted features are evaluated automatically by the activated model to determine a probability that a VAP will occur. If it is determined, based on the evaluating, that a VAP has a probability of occurring that exceeds a threshold, an indication that the VAP is predicted to occur may be provided. Other examples are disclosed and claimed.

Prediction of ventilator-associated pneumonia (VAP)

For use in a video processing system that is capable of processing a video stream using a chain of video processing algorithms, there is disclosed a system and method for optimally configuring control parameter settings of each video processing algorithm within the chain of video processing algorithms in order to provide a high quality video image. The video processing system of the present invention comprises a chain of video processing algorithms, an optimization unit, and an objective quality metric unit. An output video stream from the chain of video processing units is fed back to the objective quality metric unit. The objective quality metric unit calculates a fitness value and provides the fitness value to the optimization unit. The optimization unit uses the fitness value to configure the control parameter settings for the video processing algorithms. In one advantageous embodiment of the present invention, the optimization unit uses a genetic algorithm in the optimization process. The video processing system iteratively converges toward control parameter configurations that produce a very high quality video image.

System and method for optimizing control parameter settings in a chain of video processing algorithms

There is disclosed an apparatus for controlling the processing load of a scalable video decoder that decodes an incoming scalable video bit stream and generates a baseband video signal. The apparatus comprises: 1) an analyzer circuit for measuring at least one characteristic of the incoming scalable video bit stream and generating at least one video parameter associated with the at least one characteristic; and 2) a processor load controller for receiving the at least one video parameter and, in response thereto, controlling a level of decoding of the incoming scalable video bit stream performed by the scalable video decoder.

System and method for dynamic adaptive decoding of scalable video to balance CPU load

There is disclosed an improved system and method for providing a scalable objective metric for automatically evaluating the video quality of a video image. The system comprises an objective metric controller that is capable of receiving a plurality of objective metric figures of merit from a plurality of objective metric model units. Some of the objective metric model units are independent and some are interdependent. The system determines a scalable objective metric from the plurality of objective metric figures of merit. The scalable objective metric represents the best correlation of objective metric measurements of the video image with subjective measurements of the video image. The system is capable of continually determining a new value of the scalable objective metric as the plurality of objective metric model units receive new video images.

System and method for providing a scalable objective metric for automatic video quality evaluation employing interdependent objective metrics

There is disclosed an improved system and method for providing a scalable dynamic objective metric for automatically evaluating the video quality of a video image. The system comprises an objective metric controller that is capable of receiving a plurality of objective metric figures of merit from a plurality of objective metric model units. The system determines a scalable dynamic objective metric from a weighted average of the plurality of objective metric figures of merit. The scalable dynamic objective metric represents the best correlation of objective metric measurements of the video image with subjective measurements of the video image. The weight value of individual objective metric figures of merit may be increased or decreased depending upon the type of video image being evaluated. Individual objective metric figures of merit may be added to the system or deleted from the system. The system is capable of continually determining a new value of the scalable dynamic objective metric as the plurality of objective metric model units receive new video images.

System and method for providing a scalable dynamic objective metric for automatic video quality evaluation

A complexity scalable decoder system and method. The system comprises: a decoder having a plurality of functional blocks for decoding compressed video data, the decoder further includes a plurality of scalable functions for selectively reducing a complexity of at least one of the functional blocks; and a local resource controller for generating a scaling strategy for the decoder, wherein the scaling strategy is selected in response to a complexity requirement received from a system resource manager, and wherein the scaling strategy is selected from a plurality of predetermined scaling strategies available to the local resource controller. Each of the predetermined scaling strategies may be selected from a look-up table designed off-line.

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Peekskill, NY, United States of America

Cornelis Van Zon