Investigation on the capabilities of ANFIS for the detection of Ischemic Stroke
| Autor: | R Chethana, Adarsh S, Srinidhi R, Sri Lakshmi S, Yamini G |
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| Rok vydání: | 2021 |
| Předmět: |
medicine.medical_specialty
Adaptive neuro fuzzy inference system Learning classifier system Internal bleeding business.industry Deep learning Feature selection medicine.disease Support vector machine Feature (computer vision) Internal medicine medicine Cardiology cardiovascular diseases Artificial intelligence medicine.symptom business Stroke |
| Zdroj: | 2021 IEEE 4th International Conference on Computing, Power and Communication Technologies (GUCON). |
| Popis: | Stroke is a serious health problem. Ischemic and Hemorrhage are its two types. Ischemic stroke is caused due to the blockage of blood vessels in the brain whereas hemorrhage stroke is caused due to the internal bleeding in the brain tissue. Such strokes need immediate medical attention. This paper focuses on Ischemic stroke where various medical attributes of patients will be analyzed using Adaptive Neuro Fuzzy Inference System (ANFIS) to predict the occurrence of Ischemic stroke. The dataset will undergo pre-processing followed by feature selection along with Principal Component Analysis (PCA) which is a feature reduction technique. The comparison between the predicted and the actual output gives us the accuracy. Finally, the functionality of the model is also compared with a machine learning classifier such as SVM using various performance metrics. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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