Early detection of Parkinson's disease using machine learning
A Govindu, S Palwe - Procedia Computer Science, 2023 - Elsevier
Parkinson's disease (PD) is a neurodegenerative disorder affecting 60% of people over the
age of 50 years. Patients with Parkinson's (PWP) face mobility challenges and speech …
age of 50 years. Patients with Parkinson's (PWP) face mobility challenges and speech …
EEG-based emotion classification using stacking ensemble approach
S Chatterjee, YC Byun - Sensors, 2022 - mdpi.com
Rapid advancements in the medical field have drawn much attention to automatic emotion
classification from EEG data. People's emotional states are crucial factors in how they …
classification from EEG data. People's emotional states are crucial factors in how they …
MobiRes-net: a hybrid deep learning model for detecting and classifying olive leaf diseases
The Kingdom of Saudi Arabia is considered to be one of the world leaders in olive
production accounting for about 6% of the global olive production. Given the fact that 94% of …
production accounting for about 6% of the global olive production. Given the fact that 94% of …
Automatic and early detection of Parkinson's disease by analyzing acoustic signals using classification algorithms based on recursive feature elimination method
Parkinson's disease (PD) is a neurodegenerative condition generated by the dysfunction of
brain cells and their 60–80% inability to produce dopamine, an organic chemical …
brain cells and their 60–80% inability to produce dopamine, an organic chemical …
Deep learning‐based microarray cancer classification and ensemble gene selection approach
Malignancies and diseases of various genetic origins can be diagnosed and classified with
microarray data. There are many obstacles to overcome due to the large size of the gene …
microarray data. There are many obstacles to overcome due to the large size of the gene …
Progress and Trends in Neurological Disorders Research Based on Deep Learning
In recent years, deep learning (DL) has emerged as a powerful tool in clinical imaging,
offering unprecedented opportunities for the diagnosis and treatment of neurological …
offering unprecedented opportunities for the diagnosis and treatment of neurological …
[HTML][HTML] An ensemble nearest neighbor boosting technique for prediction of Parkinson's disease
KA Shastry - Healthcare Analytics, 2023 - Elsevier
Parkinson's disease (PD) is a complex condition that affects an individual's motor features
and intensifies over time. Symptoms vary between individuals and can go undetected at an …
and intensifies over time. Symptoms vary between individuals and can go undetected at an …
Enhancing Parkinson's Disease Detection and Diagnosis: A Survey of Integrative Approaches Across Diverse Modalities
Parkinson's disease (PD) is a chronic neurodegenerative illness that affects the brain and
central nervous system, leading to issues with pain, mobility, mood, and sleep. Early and …
central nervous system, leading to issues with pain, mobility, mood, and sleep. Early and …
[HTML][HTML] Early diagnosis of Parkinson's disease using a hybrid method of least squares support vector regression and fuzzy clustering
Parkinson's disease (PD) is a neurodegenerative disorder that influence brain's
neurological, behavioral, and physiological functions and includes motor and nonmotor …
neurological, behavioral, and physiological functions and includes motor and nonmotor …
An adaptive intelligent polar bear (aipb) optimization-quantized contempo neural network (qcnn) model for parkinson's disease diagnosis using speech dataset
S Pragadeeswaran, S Kannimuthu - Biomedical Signal Processing and …, 2024 - Elsevier
The design and development of an automated Parkinson's disease (PD) diagnosis
framework still remains one of the most complex and crucial tasks in the present day. In the …
framework still remains one of the most complex and crucial tasks in the present day. In the …