Medical records of 30K Synthea synthetic patients
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'The dataset has 2 populations of Synthea synthetic patients generated by Synthea tool. Each population has 15K patients with original medical records in CSV files. Because the total file size is >3GB in each population, the files are compressed in zip file. Synthea records are in domains similar to those in real EMR, including patients, encounters, conditions (diagnosis), observations, medications, and procedures. The data was first used in building ML models for lung cancer risk prediction. For more information, see the published paper in Nature Scientific Reports (https://www.nature.com/articles/s41598-022-23011-4' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["EHR","EMR","Synthea","Synthetic patient"]} <|eot_id|>
 Here is the Description of a dataset. Description:'The dataset has 2 populations of Synthea synthetic patients generated by Synthea tool. Each population has 15K patients with original medical records in CSV files. Because the total file size is >3GB in each population, the files are compressed in zip file. Synthea records are in domains similar to those in real EMR, including patients, encounters, conditions (diagnosis), observations, medications, and procedures. The data was first used in building ML models for lung cancer risk prediction. For more information, see the published paper in Nature Scientific Reports (https://www.nature.com/articles/s41598-022-23011-4' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
The dataset has 2 populations of Synthea synthetic patients generated by Synthea tool. Each population has 15K patients with original medical records in CSV files. Because the total file size is >3GB in each population, the files are compressed in zip file. Synthea records are in domains similar to those in real EMR, including patients, encounters, conditions (diagnosis), observations, medications, and procedures. The data was first used in building ML models for lung cancer risk prediction. For more information, see the published paper in Nature Scientific Reports (https://www.nature.com/articles/s41598-022-23011-4
EHR; EMR; Synthea; Synthetic patient