Lig-Doctor: real-world clinical prognosis using a bi-directional neural network

Author(s)

Rodrigues-Jr, Jose F. ; Spadon, Gabriel ; Brandoli, Bruno ; Amer-Yahia, Sihem ; DeHerrera, AGS ; Gonzalez, AR ; Santosh, KC ; Temesgen, Z ; Kane, B ; Soda, P

• Document type: Journal article
• Source: 2020 IEEE 33RD INTERNATIONAL SYMPOSIUM ON COMPUTER-BASED MEDICAL SYSTEMS(CBMS 2020); v. N/A, p. 4-pg., 2020-01-01.

Abstract

Automated medical prognosis has gained interest as artificial intelligence evolves and the potential for computer-aided medicine becomes evident. Nevertheless, it is challenging to design an effective system that, given a patient's medical history, can predict probable future conditions. Previous works have tackled the problem by using artificial neural network architectures that do not benefit from bi-directional temporal processing, or by utilizing non-generalizable inference approaches. Differently, we introduce a Deep Learning architecture whose design results from an intensive experimental process; our final architecture is based on two parallel Minimal Gated Recurrent Unit networks working in bi-directional manner, which was extensively tested with two real-world datasets. Our results demonstrate significant improvements in automated medical prognosis, as measured with metrics Precision@, Recall@, F1-Score, and AUC-ROC. We contribute with an architecture and with insights for the design of Deep Learning architectures. (AU)

• FAPESP's process: 16/17078-0 - Mining, indexing and visualizing Big Data in clinical decision support systems (MIVisBD)
• Grantee: Agma Juci Machado Traina
• Support Opportunities: Research Projects - Thematic Grants
• FAPESP's process: 18/17620-5 - Preventive medicine by means of deep learning techniques applied in healthcare prognosis
• Grantee: José Fernando Rodrigues Júnior
• Support Opportunities: Scholarships abroad - Research
• FAPESP's process: 17/08376-0 - Analysis and improvement of urban systems using digital maps in the form of complex networks
• Grantee: Gabriel Spadon de Souza
• Support Opportunities: Scholarships in Brazil - Doctorate