The Clinical NLP Accelerator aims to provide ecosystem of tools, algorithms, and processes to convert unstructured text to structured form. It will help customers to improve healthcare workflows. The model takes unstructured text as input and generates output highlighting values like medications, diseases, vitals and clinical codes such as ICD, CPD, etc., This can help in quick summarization and faster diagnosis from EHR data.
Input variables : Unstructured clinical text
Output Variables : Structured output(clinical entities such as diagnosis ,observation, medication, procedures, lab values, vital signs, co-reference resolution along with medical codes such as CPT, ICD, LOINC, etc., ) in JSON format
| Statistical | : | Somers D | Accuracy | Precision and Recall | Confusion Matrix | F1 Score | Roc and Auc | Prevalence | Detection Rate | Balanced Accuracy | Cohen's Kappa | Concordance | Gini Coefficent | KS Statistic | Youden's J Index |
| Infrastructure | : | Log Bytes | Logging/User/IAMPolicy | Logging/User/VPN | CPU Utilization | Memory Usage | Error Count | Prediction Count | Prediction Latencies | Private Endpoint Prediction Latencies | Private Endpoint Response Count |
Visit Model : medictiv.citiustech.com
Additional links : f.hubspotusercontent30.net | f.hubspotusercontent30.net | f.hubspotusercontent30.net
| Model Category | : | Commercial |
| Date Published | : | October, 2019 |
| Healthcare Domain | : |
Payer
Provider |
| Code | : | Not available |
| Clinical Information Extraction |