• TADEPALLY SANTOSHINI
• B. Sunil Srinivas

Usage of strong historical data in electronic health record (EHR), it is an Integrated Disease Recommendation Framework for Multi-label Unstructured Data Sources, a generalized model that covers the conditions that have been observed and medication uses. An Integrated Disease Recommendation Framework is a period model that uses Recurrent Neural Network (RNN) was developed and stamped at longitudinal time to EHR data from 260K patients over 8 years. The patient history to make multi - label forecasts The Framework assesses the patient history yet another label for each diagnosis or prescription type. Based on an assessment of the entire lab test collection, the system will conduct diagnostic differentials with up to 79% recall, substantially above several baselines. They also demonstrate great generalizability of Framework by acclimating the resulting models from one organization to another without losing significant accuracy.

Electronic Health Record (EHR), Recurrent Neural Network (RNN)

"An Integrated Disease Recommendation Framework for Multi-label Unstructured Data Sources", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.7, Issue 6, page no.14-18, June-2020, Available :http://www.jetir.org/papers/JETIR2006342.pdf

"An Integrated Disease Recommendation Framework for Multi-label Unstructured Data Sources", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.7, Issue 6, page no. pp14-18, June-2020, Available at : http://www.jetir.org/papers/JETIR2006342.pdf