Abstract: The invention provides a method for evaluating a set of input data, the input data comprising at least one of: clinical data of a subject; genomic data of a subject; clinical data of a plurality of subjects; and genomic data of a plurality of subjects, using a deep learning algorithm. The method includes obtaining a set of input data, wherein the set of input data comprises raw data arranged into a plurality of data clusters and tuning the deep learning algorithm based on the plurality of data clusters. The deep learning algorithm comprises: an input layer; an output layer; and a plurality of hidden layers. The method further includes performing statistical clustering on the raw data using the deep learning algorithm, thereby generating statistical clusters and obtaining a marker from each statistical cluster. Finally, the set of input data is evaluated based on the markers to derive data of medical relevance in respect of the subject or subjects.

Abstract: The invention provides a method for evaluating a set of input data, the input data comprising at least one of: clinical data of a subject; genomic data of a subject; clinical data of a plurality of subjects; and genomic data of a plurality of subjects, using a deep learning algorithm. The method includes obtaining a set of input data, wherein the set of input data comprises raw data arranged into a plurality of data clusters and tuning the deep learning algorithm based on the plurality of data clusters. The deep learning algorithm comprises: an input layer; an output layer; and a plurality of hidden layers. The method further includes performing statistical clustering on the raw data using the deep learning algorithm, thereby generating statistical clusters and obtaining a marker from each statistical cluster. Finally, the set of input data is evaluated based on the markers to derive data of medical relevance in respect of the subject or subjects.

Abstract: A method of clustering or grouping subjects that are similar to one another. A dataset contains, for each subject, a set of quantitative values which each represent a respective clinical or pathological feature of that subject. A principal component analysis, PCA, is performed on the dataset. Loadings of one of the first two principal components identified by the PCA are used to generate a respective dataset of weighting values. These weighting values are used to weigh or modify each set of quantitative values in the dataset. A clustering algorithm is performed on the weighted sets of subject data. The process may be iterated until user-defined stopping conditions are satisfied.

Abstract: The invention relates to a portable device (1100) comprising a bottom surface (BS) intended to be in contact with a textile (TXT). The portable device comprises an image sensor (5) for taking an image of a textile, and an illumination system (6) for illuminating a portion of the textile when said image is being taken. The portable device also comprises a control unit (8a) for executing an algorithm stored in the portable device, using the taken image as an input of said algorithm, to obtain a classification of the textile. The image sensor and the control unit are integrated within the portable device. The image sensor has an active surface sensitive to light, which is oriented compared to said bottom surface (BS), with an absolute value of the orientation angle being in the range 15-70 degrees; and/or the illumination system (6) has a light source oriented compared to the said bottom surface (BS), with an absolute value of the orientation angle being in the range 15-70 degrees.

Abstract: There is provided an apparatus and a method of operating the apparatus for providing feedback to a participant directing a communication to one or more other participants. The apparatus (100) comprises a processor (102) configured to acquire, from one or more physiological characteristic sensors (104), one or more physiological characteristic signals from at least one participant to which the communication is directed as the communication is received by the at least one participant. The processor (102) is also configured to determine a measure of the quality of the communication based on a comparison of the one or more physiological characteristic signals acquired from the at least one participant with one or more expected physiological characteristic signals and control a user interface (108) to provide feedback of the determined quality measure of the communication to the participant directing the communication to the at least one participant.

Abstract: A computerized system (SRS) for radiation therapy support. The system comprises an input interface (IN) for receiving an input image acquired by an imaging apparatus (IA1). The input image represents a region of interest (ROI) internal of a patient (PAT) and acquired before delivery of a dose fraction by a radiation therapy delivery apparatus (RTD). A pre-trained machine learning unit (MLU) of the system is configured to process the input image to detect a medical condition. A communication component (RC) of the system is configured to provide, based on the detected medical condition, an indication for one or more clinical actions to be performed in relation to the patient.

Abstract: A portable textile treatment device includes a heatable soleplate for contacting and treating the textile, an image sensor and an illumination system. The image sensor has an active surface sensitive and takes an image of the textile, and the illumination system has a light source that illuminates a portion of the textile when the image is being taken. The portable device also includes a control unit configured to execute an algorithm stored in the portable device for obtaining a classification of the textile based on taken image, and based on the classification for controlling at least one operating parameter of the portable textile treatment device. The image sensor and/or light source are oriented with respect to the surface of the heatable soleplate, with an absolute value of an orientation angle being in the range from 15 to 70° C.

Abstract: The invention relates to a method of operating a textile treatment device comprising a heatable soleplate intended to be in contact with a textile for treating the textile. The method comprises a first step (1001) of setting a first temperature target for the heatable soleplate, and a step (1002) of detecting movement of said textile treatment device. If the step (1002) of 5 detecting movement did not detect any movement of said textile treatment device during more than a given first time duration, a step (1004) of actively decreasing the temperature of the heatable soleplate (4) up to reaching a first given temperature having a value below said first temperature target.

Abstract: The invention relates to a portable textile treatment device (1) comprising a heatable sole plate (4) intended to be in contact with a textile (TXT) for treating the textile. The portable textile treatment device also comprises an image sensor (5) for taking an image of the textile to be treated, an illumination system (6) for illuminating a portion of the textile when said image is being taken. The portable device also comprises a control unit (8) configured for executing an algorithm stored in said portable textile treatment device, using the taken image as an input of said algorithm, to obtain a classification of the textile; and controlling, based on said classification, at least one operating parameter of the portable textile treatment device. The image sensor and the control unit are integrated within the portable textile treatment device.

Abstract: The invention relates to a method of operating a textile treatment device comprising a heatable soleplate intended to be in contact with a textile for treating the textile. The method comprises a first step (1001) of setting a first temperature target for the heatable soleplate, and a step (1002) of detecting movement of said textile treatment device. If the step (1002) of 5 detecting movement did not detect any movement of said textile treatment device during more than a given first time duration, a step (1004) of actively decreasing the temperature of the heatable soleplate (4) up to reaching a first given temperature having a value below said first temperature target.

Abstract: The invention provides a method for evaluating a set of input data, the input data comprising at least one of: clinical data of a subject; genomic data of a subject; clinical data of a plurality of subjects; and genomic data of a plurality of subjects, using a deep learning algorithm. The method includes obtaining a set of input data, wherein the set of input data comprises raw data arranged into a plurality of data clusters and tuning the deep learning algorithm based on the plurality of data clusters. The deep learning algorithm comprises: an input layer; an output layer; and a plurality of hidden layers. The method further includes performing stabstical clustering on the raw data using the deep learning algorithm, thereby generating statistical clusters and obtaining a marker from each statistical cluster. Finally, the set of input data is evaluated based on the markers to derive data of medical relevance in respect of the subject or subjects.

Abstract: A method of clustering or grouping subjects that are similar to one another. A dataset contains, for each subject, a set of quantitative values which each represent a respective clinical or pathological feature of that subject. A principle component analysis, PCA, is performed on the dataset. Loadings of one of the first two principle components identified by the PCA are used to generate a respective dataset of weighting values. These weighting values are used to weigh or modify each set of quantitative values in the dataset. A clustering algorithm is performed on the weighted sets of subject data. The process may be iterated until user-defined stopping conditions are satisfied.

Abstract: There is provided an apparatus and a method of operating the apparatus for providing feedback to a participant directing a communication to one or more other participants. The apparatus (100) comprises a processor (102) configured to acquire, from one or more physiological characteristic sensors (104), one or more physiological characteristic signals from at least one participant to which the communication is directed as the communication is received by the at least one participant. The processor (102) is also configured to determine a measure of the quality of the communication based on a comparison of the one or more physiological characteristic signals acquired from the at least one participant with one or more expected physiological characteristic signals and control a user interface (108) to provide feedback of the determined quality measure of the communication to the participant directing the communication to the at least one participant.

Abstract: The invention relates to a portable device (1100) comprising a bottom surface (BS) intended to be in contact with a textile (TXT). The portable device comprises an image sensor (5) for taking an image of a textile, and an illumination system (6) for illuminating a portion of the textile when said image is being taken. The portable device also comprises a control unit (8a) for executing an algorithm stored in the portable device, using the taken image as an input of said algorithm, to obtain a classification of the textile. The image sensor and the control unit are integrated within the portable device. The image sensor has an active surface sensitive to light, which is oriented compared to said bottom surface (BS), with an absolute value of the orientation angle being in the range 15-70 degrees; and/or the illumination system (6) has a light source oriented compared to the said bottom surface (BS), with an absolute value of the orientation angle being in the range 15-70 degrees.