Instance-Based Learning Following Physician Reasoning for Assistance during Medical Consultation
This article presents an automatic system for modeling clinical knowledge to follow a physician’s reasoning in medical consultation. Instance-based learning is applied to provide suggestions when recording electronic medical records. The system was validated on a real case study involving advanced m...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2021-06-01
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| Series: | Applied Sciences |
| Subjects: | |
| Online Access: | https://www.mdpi.com/2076-3417/11/13/5886 |
| Summary: | This article presents an automatic system for modeling clinical knowledge to follow a physician’s reasoning in medical consultation. Instance-based learning is applied to provide suggestions when recording electronic medical records. The system was validated on a real case study involving advanced medical students. The proposed system is accurate and efficient: 2.5× more efficient than a baseline empirical tool for suggestions and two orders of magnitude faster than a Bayesian learning method, when processing a testbed of 250 clinical case types. The research provides a framework to implement a real-time system to assist physicians during medical consultations. |
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| ISSN: | 2076-3417 |