Koninklijke Philips Corporation N.v.

Litecontrol Corporation

Xin Wang

Reza Sharifi Sedeh

Eran Simhon

Prescott Peter Klassen

Amir Abdolahi

Cecilia Meijer

A method () of training a machine-learned (ML) image classifier () to classify images () respective to a set of labels includes: generating image-based labels for the images from the set of labels and image-based label confidence values for the image-based labels by applying the ML image classifier to the images; generating report-based labels for the images from the set of labels and report-based label confidence values for the report-based labels by applying a report classifier () to corresponding radiology reports; selecting a training subset of the set of images based on the image-based labels, the report-based labels, the image-based label confidence values, and the report-based label confidence values; assigning a pseudo-label for each image of the training subset which is one of the image-based label or the report-based label for the image; and training the ML image classifier using at least the selected training subset and the assigned pseudo-labels.

Semi-supervised learning using co-training of radiology report and medical images

The present disclosure pertains to a system configured to prepare and use prediction models for socioeconomic data and missing value prediction. Some embodiments may: extract, from received population segment data, a training set of socioeconomic parameter values for each population segment; provide, to a prediction model as input, first parameter values of the respective training set for the prediction of additional parameter values of the training set such that the prediction of the additional parameter values is performed without reliance on the additional parameter values; provide, for each of the training sets, the additional parameter values to the prediction model as reference feedback for the prediction model's prediction of the additional parameter values to train the prediction model; and predict, based on a working set of parameter values for a population segment, additional values for the working set using the prediction model subsequent to its training.

Prediction model preparation and use for socioeconomic data and missing value prediction

Lighting fixture

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Cambridge, MA, United States of America

Xin Wang