Deep learning-based pneumonia joint index analysis method

• Main Authors: FAN ZHU, GE YANLEI, LIU JINGXUAN, CHEN WEIBIN, ZHANG JIABIN, LIU CONGHUI, CHEN QIANCHENG, DONG AIYING, CUI JUNCHANG, FU AISHUANG, SUN YE, BAI JING
• Format: Patent
• Language: Chinese; English
• Published: 29.09.2023
• Subjects: CALCULATING; COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS; COMPUTING; COUNTING; HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATIONTECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING ORPROCESSING OF MEDICAL OR HEALTHCARE DATA; INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS; PHYSICS

The invention discloses a pneumonia joint index analysis method based on deep learning, and the method comprises the steps: obtaining the clinical data of a historical patient, carrying out the processing and standardization of the clinical data of the historical patient, and obtaining a standardized data set; performing joint data weight analysis on the standardized data set to obtain a weight annotation data set; constructing a neural network model, and inputting the weight labeling data set into the neural network model for training to obtain a joint index analysis model; and acquiring clinical data of a patient, and inputting the clinical data of the patient into the combined index analysis model for analysis to obtain the pneumonia combined index. According to the method, the joint indexes among the patients are analyzed, the indexes in the bodies of the patients can be corrected in time, and the method has great significance in early recognition of disease progress risks, reasonable allocation of medica