Abstract: Systems and methods are provided for analyzing electrocardiogram (ECG) data of a patient using a substantial amount of ECG data. The systems receive ECG data from a sensing device positioned on a patient such as one or more ECG leads. The system may include an application that communicates with an ECG platform running on a server(s) that processes and analyzes the ECG data, e.g., using neural networks for delineation of the cardiac signal and classification of various abnormalities, conditions and/or descriptors. The ECG platform may further process and analyze the ECG data using neural networks and/or algorithms for embedding and grouping. The processed ECG data is used to generate a graphic user interface that is communicated from the server(s) to a computer for display in a user-friendly and interactive manner with enhanced accuracy.

Abstract: The present invention relates to a computer-implemented method for electrocardiogram analysis, the method comprising the steps of receiving at least one ECG signal; analyzing the ECG signal to provide features and/or identify at least one episode and/or event, wherein an episode is a segment of the ECG signal defined by a starting time, a duration and a label obtained during the analysis of the ECG signal and an event is a strip of the ECG signal of predefined duration defined by a starting time and a label obtained during the analysis of the ECG signal; and displaying a multiple field display (1) which includes at least a main plot (42), being a global view of a graphic representation of the ECG signal in a first time window; a local view of a graphic representation of the ECG signal in a second time window (51), where the first time window comprises the second time window; an intermediate view of a graphic representation of the ECG signal in a third time window (52), wherein the third time window comprises

Abstract: Systems and methods are provided for analyzing electrocardiogram (ECG) data of a patient using a substantial amount of ECG data. The systems receive ECG data from a sensing device positioned on a patient such as one or more ECG leads. The system may include an application that communicates with an ECG platform running on a server(s) that processes and analyzes the ECG data, e.g., using neural networks for delineation of the cardiac signal and classification of various abnormalities, conditions and/or descriptors. The processed ECG data is communicated from the server(s) for display in a user-friendly and interactive manner with enhanced accuracy.

Abstract: Systems and methods are provided for analyzing electrocardiogram (ECG) data of a patient using a substantial amount of ECG data. The systems receive ECG data from a sensing device positioned on a patient such as one or more ECG leads/electrodes that may be integrated in a smart device. The system may include an application that communicates with an ECG platform running on a server(s) that processes and analyzes the ECG data, e.g., using neural networks, to detect and/or predict various abnormalities, conditions and/or descriptors. The processed ECG data is used to generate a graphic user interface that is communicated from the server(s) to a computer for display in a user-friendly and interactive manner with enhanced accuracy. The systems may restrict access to certain ECG data, analyses, reports, and/or functionality to different entities, devices and/or users.

Abstract: Systems and methods are provided for analyzing electrocardiogram (ECG) data of a patient using a substantial amount of ECG data. The systems receive ECG data from a sensing device positioned on a patient such as one or more ECG leads. The system may include an application that communicates with an ECG platform running on a server(s) that processes and analyzes the ECG data, e.g., using neural networks for delineation of the cardiac signal and classification of various abnormalities, conditions and/or descriptors. The processed ECG data is communicated from the server(s) for display in a user-friendly and interactive manner with enhanced accuracy.

Abstract: Systems and methods are provided for analyzing electrocardiogram (ECG) data of a patient using a substantial amount of ECG data. The systems receive ECG data from a sensing device positioned on a patient such as one or more ECG leads/electrodes that may be integrated in a smart device. The system may include an application that communicates with an ECG platform running on a server(s) that processes and analyzes the ECG data, e.g., using neural networks, to detect and/or predict various abnormalities, conditions and/or descriptors. The system may also determine a confidence score corresponding to the abnormalities, conditions and/or descriptors. The processed ECG data is used to generate a graphic user interface that is communicated from the server(s) to a computer for display in a user-friendly and interactive manner with enhanced accuracy.

Abstract: Systems and methods are provided for analyzing electrocardiogram (ECG) data of a patient using a substantial amount of ECG data. The systems receive ECG data from a sensing device positioned on a patient such as one or more ECG leads. The system may include an application that communicates with an ECG platform running on a server(s) that processes and analyzes the ECG data, e.g., using neural networks for delineation of the cardiac signal and classification of various abnormalities, conditions and/or descriptors. The ECG platform may further process and analyze the ECG data using neural networks and/or algorithms for embedding and grouping. The processed ECG data is used to generate a graphic user interface that is communicated from the server(s) to a computer for display in a user-friendly and interactive manner with enhanced accuracy.

Abstract: Systems and methods are provided for analyzing electrocardiogram (ECG) data of a patient using a substantial amount of ECG data. The systems receive ECG data from a sensing device positioned on a patient such as one or more ECG leads. The system may include an application that communicates with an ECG platform running on a server(s) that processes and analyzes the ECG data, e.g., using neural networks for delineation of the cardiac signal and classification of various abnormalities, conditions and/or descriptors. The processed ECG data is communicated from the server(s) for display in a user-friendly and interactive manner with enhanced accuracy.

Abstract: Systems and methods are provided for analyzing electrocardiogram (ECG) data of a patient using a substantial amount of ECG data. The systems receive ECG data from a sensing device positioned on a patient such as one or more ECG leads. The system may include an application that communicates with an ECG platform running on a server(s) that processes and analyzes the ECG data, e.g., using neural networks for delineation of the cardiac signal and classification of various abnormalities, conditions and/or descriptors. The processed ECG data is communicated from the server(s) for display in a user-friendly and interactive manner with enhanced accuracy.

Abstract: Systems and methods are provided for analyzing electrocardiogram (ECG) data of a patient using a substantial amount of ECG data. The systems receive ECG data from a sensing device positioned on a patient such as one or more ECG leads. The system may include an application that communicates with an ECG platform running on a server(s) that processes and analyzes the ECG data, e.g., using neural networks for delineation of the cardiac signal and classification of various abnormalities, conditions and/or descriptors. The processed ECG data is communicated from the server(s) for display in a user-friendly and interactive manner with enhanced accuracy.

Abstract: The present invention is in the technical field of breast cancer management, and more particularly relates to the diagnosis and/or prognosing of triple-negative breast cancer (TNBC). The invention is more particularly based on the finding that specific biomarkers are abberantly expressed in patients suffering from a triple-negative breast cancer recurrence, and are highly related to the aggressiveness of this disease, and thus to survival of said patient.

Abstract: The present invention relates to a computer-implemented method for electrocardiogram analysis, the method comprising the steps of receiving at least one ECG signal; analyzing the ECG signal to provide features and/or identify at least one episode and/or event, wherein an episode is a segment of the ECG signal defined by a starting time, a duration and a label obtained during the analysis of the ECG signal and an event is a strip of the ECG signal of predefined duration defined by a starting time and a label obtained during the analysis of the ECG signal; and displaying a multiple field display (1) which includes at least a main plot (42), being a global view of a graphic representation of the ECG signal in a first time window; a local view of a graphic representation of the ECG signal in a second time window (51), where the first time window comprises the second time window; an intermediate view of a graphic representation of the ECG signal in a third time window (52), wherein the third time window comprises

Abstract: The present invention is in the technical field of breast cancer management, and more particularly relates to the diagnosis of breast cancer. The invention is more particularly based on the finding that specific biomarkers (olfactomedin-4, neudesin and desmoplakin) are abberantly expressed in the blood of breast cancer patients.

Abstract: Systems and methods are provided for analyzing electrocardiogram (ECG) data of a patient using a substantial amount of ECG data. The systems receive ECG data from a sensing device positioned on a patient such as one or more ECG leads. The system may include an application that communicates with an ECG platform running on a server(s) that processes and analyzes the ECG data, e.g., using neural networks for delineation of the cardiac signal and classification of various abnormalities, conditions and/or descriptors. The processed ECG data is communicated from the server(s) for display in a user-friendly and interactive manner with enhanced accuracy.

Abstract: A computer-implemented method implemented between a server and a user device for performing an image-based search in a database comprising unique entries to which are respectively associated a unique key, the unique entries having associated thereto images which each have a tag representative of a category related to the unique entries. The method comprises the user device displaying a search GUI comprising a graphic query field; receiving from the user a graphic query object (GQO); and transmitting to the server the GQO. The method comprises the server searching the database for a tag matching to the GQO and selecting only matching images; and transmitting to the user device interface code comprising the selected images. The method comprises the user device displaying an image GUI comprising a mosaic of the selected images. Accordingly, each image comprises a hyperlink to a unique entry from the database.

Abstract: The present invention provides a method for diagnosing KRAS mutations in colorectal cancers by measuring the level of OLFM4. In another aspect, the present invention relates a method of predicting the responds to a chemotherapeutic agent of a subject suffering from a colorectal cancer: according to the present invention, the by determining the OLFM4 levels. According to the present invention, the response can be predicted by determining the OLFM4 levels. This result in turn permits the design or the adaptation of a treatment of the said subject with the said chemotherapeutic agent.

Abstract: The present invention is in the technical field of breast cancer management, and more particularly relates to the diagnosis of breast cancer. The invention is more particularly based on the finding that specific biomarkers (olfactomedin-4, neudesin and desmoplakin) are abberantly expressed in the blood of breast cancer patients.

Abstract: The present invention is in the technical field of breast cancer management, and more particularly relates to the diagnosis and/or prognosing of triple-negative breast cancer (TNBC). The invention is more particularly based on the finding that specific biomarkers are abberantly expressed in patients suffering from a triple-negative breast cancer recurrence, and are highly related to the aggressiveness of this disease, and thus to survival of said patient.

Abstract: Soluble proteins, e.g. Hevin, can trigger synapse formation; and other soluble proteins, e.g. SPARC antagonize this activity. Such proteins are synthesized in vitro and in vivo by astrocytes. Methods are provided for protecting or treating an individual suffering from adverse effects of deficits in synaptogenesis, or from undesirably active synaptogenesis.

Abstract: The present invention provides a method for diagnosing KRAS mutations in colorectal cancers by measuring the level of OLFM4. In another aspect, the present invention relates a method of predicting the responds to a chemotherapeutic agent of a subject suffering from a colorectal cancer: according to the present invention, the by determining the OLFM4 levels. According to the present invention, the response can be predicted by determining the OLFM4 levels. This result in turn permits the design or the adaptation of a treatment of the said subject with the said chemotherapeutic agent.