http://rdf.ncbi.nlm.nih.gov/pubchem/patent/CN-113782197-B
Outgoing Links
| Predicate | Object |
|---|---|
| classificationCPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H10-40 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H10-60 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H10-20 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-30 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G16H50-80 http://rdf.ncbi.nlm.nih.gov/pubchem/patentcpc/G06N20-20 |
| classificationIPCInventive | http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G06N20-20 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H10-60 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H10-20 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H10-40 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H50-30 http://rdf.ncbi.nlm.nih.gov/pubchem/patentipc/G16H50-80 |
| filingDate | 2021-08-03-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| grantDate | 2022-11-04-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationDate | 2022-11-04-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| publicationNumber | CN-113782197-B |
| titleOfInvention | Outcome prediction method for patients with new coronary pneumonia based on interpretable machine learning algorithm |
| abstract | The present invention proposes a method for predicting the outcome of patients with new coronary pneumonia based on an interpretable machine learning algorithm, which includes: extracting patient data of COVID-19 from a database, and dividing the patient data into an experimental group and a control group according to the patient's condition conversion group; impute the missing values of each index through random forest regression; screen the indicators input into the model, and use the screened indicators as the key risk factors for identifying the deterioration of the patient’s condition; input the key risk factors of the patient into the XGBoost model and logic Regression model; select the XGBoost model with better predictive performance, generate a combination of indicators, then use the XGBoost model to make predictions, and record the prediction results; define the early warning range of key indicators; when the patient's key risk indicators enter the early warning range, medical staff An alarm prompt is issued; the calculation results of the algorithm and the clinical experience of doctors are combined, and a combination of two indicators consisting of 15 first-group indicators and 5 second-group indicators is proposed to predict the condition of patients with new coronary pneumonia. |
| priorityDate | 2021-08-03-04:00^^<http://www.w3.org/2001/XMLSchema#date> |
| type | http://data.epo.org/linked-data/def/patent/Publication |
Incoming Links
Total number of triples: 185.