Parkinson’s Neurodegenerative Disease Prediction with Robust Methods Of Machine Learning

Author(s):  
Anusha Papasani ◽  
Nagaraju Devarakonda ◽  
Zdzislaw Polkowski
Author(s):  
Anantvir Singh Romana

Accurate diagnostic detection of the disease in a patient is critical and may alter the subsequent treatment and increase the chances of survival rate. Machine learning techniques have been instrumental in disease detection and are currently being used in various classification problems due to their accurate prediction performance. Various techniques may provide different desired accuracies and it is therefore imperative to use the most suitable method which provides the best desired results. This research seeks to provide comparative analysis of Support Vector Machine, Naïve bayes, J48 Decision Tree and neural network classifiers breast cancer and diabetes datsets.


Author(s):  
Matthew N. O. Sadiku ◽  
Chandra M. M Kotteti ◽  
Sarhan M. Musa

Machine learning is an emerging field of artificial intelligence which can be applied to the agriculture sector. It refers to the automated detection of meaningful patterns in a given data.  Modern agriculture seeks ways to conserve water, use nutrients and energy more efficiently, and adapt to climate change.  Machine learning in agriculture allows for more accurate disease diagnosis and crop disease prediction. This paper briefly introduces what machine learning can do in the agriculture sector.


2021 ◽  
Vol 1916 (1) ◽  
pp. 012092
Author(s):  
N Karthikeyan ◽  
P Padmanaban ◽  
A Prasanth ◽  
D Ragunath

Author(s):  
Wan Adlina Husna Wan Azizan ◽  
A'zraa Afhzan Ab Rahim ◽  
Siti Lailatul Mohd Hassan ◽  
Ili Shairah Abdul Halim ◽  
Noor Ezan Abdullah

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