IANN is a deep-learning based natural language processing
(DL.NLP) platform that leverages transfer learning and a
distinctive pre-trained healthcare neural network
infrastructure for healthcare language generation as well as
information extraction and classification.
Clinical Notes Structuring
Complying with industry-standard ontologies, IANN is able to apply transfer learning and deep learning-based natural language processing and generation techniques for information extraction and classification on SOAP Notes, Discharge Notes, Surgical Notes as a result physician productivity has shown to improve by at least 20% while unstructured narratives in notes are structured giving 360 degree views along many dimensions of the patient.
Risk Assessment and Compliance
IANN is able to dynamically assess risk by applying its transfer learning and neural network architecture on unstructured notes, as an example IANN’s readmission risk prediction algorithms are showing greater than 80% accuracy. IANN is also able to extract key follow up insights from notes ensuring compliance to regulatory mandates for essential diagnosis captured in notes.
CDI and Revenue Cycle Management
IANN is able to automatically determine clinical documentation improvement opportunities, applying the correct ICD-10 codes to the specific document ensuring that there will be appropriate and prompt reimbursement eliminating the need for manual coding processes.
Key Impact
Productivity - physicians should be able to reduce time spent by at least 20% on each report
IANN at work in Radiology
Radiologists write as many as 1 Billion reports in the US . IANN has been trained to understand radiology reports
IANN can highlight errors like laterality errors
IANN can suggest diagnostics impressions based on the physician’s findings
IANN integrates directly into the workflow of radiologists
