5results about How to "Helpful for analysis" patented technology

The invention provides an electrode wire, a stimulator system and a computer readable storage medium, the electrode wire comprises a catheter, at least one electrode contact and a signal processing chip, each electrode contact is attached to the outer wall of the catheter, and each electrode contact is used for collecting a bio-electricity signal of a patient, and / or collecting the bio-electricity signal of the patient. Delivering electrical stimulation to the in vivo tissue of the patient according to the stimulation pulse signal; and the signal processing chip is arranged in the conduit. According to the invention, the signal processing chip is integrated in the electrode wire, so that the interference of external interference and stimulation pulse signals on bio-electricity signals is reduced.

The application discloses a kind of three-dimensional full-automatic human body composition analysis method, system and medium based on CT image, method includes: acquisition CT image data and mark;Spine segmentation model is constructed and is trained, the spine segmentation model is in the jump connection part of pre-set U-Net network joins attention module and learns the overall information of spine, to make that spine segmentation model obtains better segmentation effect;Construct body composition segmentation model, and the same loss function and depth supervision method as spine segmentation model is used to train the body composition segmentation model;Based on the spine positioning result and body composition segmentation result obtained in well-trained spine segmentation model and body composition segmentation model, calculate human body composition related index and mutual relationship based on spine positioning result and body composition segmentation result.The application realizes full-automatic process by intelligent positioning to spine, simultaneously provides selectable interface, and it is convenient for user to carry out the analysis of specific organ or tissue.

The invention discloses a marker and a system for predicting the effect of tumor immunotherapy, and relates to the field of tumor immunotherapy, the marker is expressed in various immune cells, participates in activation of the immune cells, is an important effector protein of a human innate immune system, namely LCP2, and can be detected in a tissue sample from a tumor patient. The clinical effect of tumor immunotherapy is predicted by detecting the infiltration level of killer immune cells in tumors.

The embodiments of the present invention relate to the field of computer technology, and disclose a document information integration method, device, system, equipment, medium and program product, wherein the method comprises: obtaining a list of objects to be evaluated, obtaining corresponding unstructured information source documents according to the list of objects to be evaluated, matching content extraction rules corresponding to each document according to the document number of each document in the information source document corresponding to the object to be evaluated, extracting target key information from the unstructured information source document based on the content extraction rule, and then obtaining a target structured document according to a preset information integration template and the target key information integration, thereby realizing information extraction and information integration of multi-source unstructured documents, without the need to separately configure an integration template for each type of source document, solving the technical problem of relying on complex template configuration for information extraction in the prior art, and improving the efficiency of information extraction and integration of multi-source unstructured documents.

The application discloses a time anomaly detection method, device, medium and product, comprising: acquiring a reference time of a current sampling moment as a time observation value of the current sampling moment; determining a local time of the current sampling moment based on a local time counter; determining a time prediction value of the current sampling moment based on a linear time relationship model and the local time of the current sampling moment, wherein the linear time relationship model is a relationship model between the local time and the reference time; determining a difference value between the time prediction value of the current sampling moment and the time observation value, obtaining a prediction residual of the current sampling moment; adding the prediction residual of the current sampling moment to a prediction residual sequence, and performing time anomaly detection based on the prediction residual sequence. In this way, the sensitivity of time anomaly detection can be improved, and the type of anomaly can be identified.