Medical diagnosis and treatment system

Abstract

The embodiment of the invention discloses a medical diagnosis and treatment system. The system comprises a diagnosis and treatment data integration module used for obtaining diagnosis and treatment data related to a patient from one or more medical information sources and integrating the diagnosis and treatment data, wherein the diagnosis and treatment data at least comprises medical image data and medical text data; an artificial intelligence image analysis module used for analyzing the medical image data based on an artificial intelligence image analysis technology to generate an image analysis report; and an artificial intelligence text analysis module used for performing information extraction on the medical text data and/or the image analysis report based on an artificial intelligenceinformation extraction technology to obtain structured diagnosis and treatment data related to diseases.

Description

technical field [0001] This application relates to the technical fields of artificial intelligence and medical applications, and in particular to a medical diagnosis and treatment system. Background technique [0002] At present, with the development of Internet technology, the methods of using artificial intelligence (AI) technology to assist medical diagnosis are becoming more and more diverse. For example, in the field of medical imaging, more and more AI-assisted diagnosis systems can automatically complete functions such as segmentation and labeling of organs, location and characterization of lesions through image segmentation and recognition technologies, such as automatic detection of lung nodules, liver Automatic segmentation of tumors, etc. However, the diagnosis and treatment process of actual clinicians is very complicated, and the medical data involved are also multimodal. Taking coronary heart disease as an example, clinicians first make a preliminary possible...

AI Technical Summary

Problems solved by technology

There are still some problems. For example, the EMR system only contains clinical data in text form, such as patient complaints, clinical manifestations, simple descriptions of test / test results, diagnosis and treatment records, etc. For detailed test / test results, the corresponding information system needs to be called. Especially for image data, clinicians need to additionally log in to the PACS system to browse, and the operation is relatively cumbersome, resulting in doctors not observing image performance in detail in pursuit of efficiency, and unable to effectively use image information

For another example, CDSS cannot automatically extract the specific parameter data required by the decision-making system from EMR and other information systems, and needs to manually input all aspects of patient data through the human-computer interaction interface, resulting in low efficiency

For another example, the storage of patient data is a disease-centered diagnosis and treatment process record. Clinicians can only browse the relevant clinical data in the current diagnosis and treatment. It is difficult to synchronize the relevant data in the patient's historical diagnosis and treatment records to analyze the evolution of the disease. , unable to present physicians with a comprehensive view of patient data

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