The week's pick
Reseach Article
Cohort Search, Representation and Prediction: Application to Medical Data
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 177 - Number 13 |
| Year of Publication: 2019 |
| Authors: Adebayo Salaudeen, Ahmad Abubakar, Ganiyu Saheed |
10.5120/ijca2019919511
|
Adebayo Salaudeen, Ahmad Abubakar, Ganiyu Saheed . Cohort Search, Representation and Prediction: Application to Medical Data. International Journal of Computer Applications. 177, 13 ( Oct 2019), 1-8. DOI=10.5120/ijca2019919511
Abstract
In this paper, we are interested in cohort search, representation, and prediction. Information retrieval and text mining technique were proposed based on Term Frequency Inverse Document Frequency (TF.IDF) to extract important terms. Also, a formal and algorithmic model was formulated to compute: readable, concise cohorts of patients and find similarities between patient trajectories. Finally, Patient health trajectories were analyzed using a Deep Learning architecture from intensive experimental processes based on two parallel Minimal Gated Recurrent Unit networks, working in a bi-directional manner. The obtained result shows an improvement in the performance of computer-aided medicine and serves as a guide in designing artificial neural networks used in prediction tasks.
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