Natural Language Processing Accurately Categorizes Indications, Findings and Pathology Reports from Multicenter Colonoscopy

08/25/2021
by   Shashank Reddy Vadyala, et al.
0

Colonoscopy is used for colorectal cancer (CRC) screening. Extracting details of the colonoscopy findings from free text in electronic health records (EHRs) can be used to determine patient risk for CRC and colorectal screening strategies. We developed and evaluated the accuracy of a deep learning model framework to extract information for the clinical decision support system to interpret relevant free-text reports, including indications, pathology, and findings notes. The Bio-Bi-LSTM-CRF framework was developed using Bidirectional Long Short-term Memory (Bi-LSTM) and Conditional Random Fields (CRF) to extract several clinical features from these free-text reports including indications for the colonoscopy, findings during the colonoscopy, and pathology of resected material. We trained the Bio-Bi-LSTM-CRF and existing Bi-LSTM-CRF models on 80 of 4,000 manually annotated notes from 3,867 patients. These clinical notes were from a group of patients over 40 years of age enrolled in four Veterans Affairs Medical Centers. A total of 10 used to train hyperparameter and the remaining 10 accuracy of our model Bio-Bi-LSTM-CRF and compare to Bi-LSTM-CRF.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
08/09/2015

Bidirectional LSTM-CRF Models for Sequence Tagging

In this paper, we propose a variety of Long Short-Term Memory (LSTM) bas...
research
01/09/2018

Probabilistic Prognostic Estimates of Survival in Metastatic Cancer Patients (PPES-Met) Utilizing Free-Text Clinical Narratives

We propose a deep learning model - Probabilistic Prognostic Estimates of...
research
11/26/2022

An Automatic SOAP Classification System Using Weakly Supervision And Transfer Learning

In this paper, we introduce a comprehensive framework for developing a m...
research
10/19/2020

SmartTriage: A system for personalized patient data capture, documentation generation, and decision support

Symptom checkers have emerged as an important tool for collecting sympto...
research
04/12/2023

Landslide Susceptibility Prediction Modeling Based on Self-Screening Deep Learning Model

Landslide susceptibility prediction has always been an important and cha...
research
02/19/2023

Forecasting Pressure Of Ventilator Using A Hybrid Deep Learning Model Built With Bi-LSTM and Bi-GRU To Simulate Ventilation

A ventilator simulation system can make mechanical ventilation easier an...

Please sign up or login with your details

Forgot password? Click here to reset