- Tytuł:
- Applicability of artificial intelligence in smart healthcare systems for automatic detection of Parkinson’s Disease
- Autorzy:
-
Pallathadka, Harikumar
Padminivalli V., S.J.R.K.
Vasavi, M.
Nancy, P.
Naved, Mohd
Kumar, Harish
Ray, Samrat - Powiązania:
- https://bibliotekanauki.pl/articles/38709253.pdf
- Data publikacji:
- 2024
- Wydawca:
- Instytut Podstawowych Problemów Techniki PAN
- Tematy:
-
Parkinson’s disease
detection
machine learning
relief algorithm
LDA algorithm
SVM-RBF
accuracy
sensitivity
specificity
choroba Parkinsona
wykrywanie
nauczanie maszynowe
algorytm ulgi
Algorytm LDA
dokładność
wrażliwość
specyficzność - Opis:
- Parkinson’s disease is associated with memory loss, anxiety, and depression in the brain. Problems such as poor balance and difficulty during walking can be observed in addition to symptoms of impaired posture and rigidity. The field dedicated to making computers capable of learning autonomously, without having to be explicitly programmed, is known as machine learning. An approach to the diagnosis of Parkinson’s disease, which is based on artificial intelligence, is discussed in this article. The input for this system is provided through photographic examples of Parkinson’s disease patient handwriting. Received photos are preprocessed using the relief feature option to begin the process. This is helpful in the process of selecting characteristics for the identification of Parkinson’s disease. After that, the linear discriminant analysis (LDA) algorithm is employed to reduce the dimensions, bringing down the total number of dimensions that are present in the input data. The photos are then classified via radial basis function-support vector machine (SVM-RBF), k-nearest neighbors (KNN), and naive Bayes algorithms, respectively.
- Źródło:
-
Computer Assisted Methods in Engineering and Science; 2024, 31, 2; 175-185
2299-3649 - Pojawia się w:
- Computer Assisted Methods in Engineering and Science
- Dostawca treści:
- Biblioteka Nauki
Artykuł