Development of Artificial Neural Network Model for Medical Specialty Recommendation

Author:

Hasuki Winda,Agustriawan David,Parikesit Arli Aditya,Sadrawi Muammar,Firmansyah Moch,Whisnu Andreas,Natasya Jacqulin,Mathew Ryan,Napitupulu Florensia Irena,Ratnasari Nanda Rizqia Pradana

Abstract

Timely diagnosis is crucial for a patient’s future care and treatment. However, inadequate medical service or a global pandemic can limit physical contact between patients and healthcare providers. Combining the available healthcare data and artificial intelligence methods might offer solutions that can support both patients and healthcare providers. This study developed one of the artificial intelligence methods, artificial neural network (ANN), the multilayer perceptron (MLP), for medical specialist recommendation systems. The input of the system is symptoms and comorbidities. Meanwhile, the output is the medical specialist. Leave one out cross-validation technique was used. As a result, this study’s F1 score of the model was about 0.84. In conclusion, the ANN system can be an alternative to the medical specialist recommendation system.

Publisher

Universiti Putra Malaysia

Subject

General Earth and Planetary Sciences,General Environmental Science

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