Machine learning and deep learning approaches for brain disease diagnosis: principles and recent advances
Brain is the controlling center of our body. With the advent of time, newer and newer brain
diseases are being discovered. Thus, because of the variability of brain diseases, existing …
diseases are being discovered. Thus, because of the variability of brain diseases, existing …
A review of deep-learning-based approaches for attenuation correction in positron emission tomography
JS Lee - IEEE Transactions on Radiation and Plasma Medical …, 2020 - ieeexplore.ieee.org
Attenuation correction (AC) is essential for the generation of artifact-free and quantitatively
accurate positron emission tomography (PET) images. PET AC based on computed …
accurate positron emission tomography (PET) images. PET AC based on computed …
[HTML][HTML] Comparison of machine and deep learning for the classification of cervical cancer based on cervicography images
Cervical cancer is the second most common cancer in women worldwide with a mortality
rate of 60%. Cervical cancer begins with no overt signs and has a long latent period, making …
rate of 60%. Cervical cancer begins with no overt signs and has a long latent period, making …
Explainable machine learning models based on multimodal time-series data for the early detection of Parkinson's disease
Background and objectives Parkinson's Disease (PD) is a devastating chronic neurological
condition. Machine learning (ML) techniques have been used in the early prediction of PD …
condition. Machine learning (ML) techniques have been used in the early prediction of PD …
A survey of deep learning techniques based Parkinson's disease recognition methods employing clinical data
Parkinson's disease (PD) is a critical neurological ailment that affects millions of individuals
worldwide. A correct diagnosis of Parkinson's disease is required for effective treatment …
worldwide. A correct diagnosis of Parkinson's disease is required for effective treatment …
[PDF][PDF] Assessing the Increasing Rate of Parkinson's Disease in the US and its Prevention Techniques
R Boina - International Journal of Biotechnology, 2022 - researchgate.net
ABSTRACT Purpose: In the United States, nearly one million people are diagnosed with
Parkinson Disease (PD). The ratio of PD is kept increasing as compared to the combined …
Parkinson Disease (PD). The ratio of PD is kept increasing as compared to the combined …
Efficient detection of Parkinson's disease using deep learning techniques over medical data
Parkinson's disease is a degenerative disease that leads to brain disorder and
nonfunctioning of different body parts. Deep learning tools like artificial neural network …
nonfunctioning of different body parts. Deep learning tools like artificial neural network …
Photoacoustic imaging aided with deep learning: a review
Photoacoustic imaging (PAI) is an emerging hybrid imaging modality integrating the benefits
of both optical and ultrasound imaging. Although PAI exhibits superior imaging capabilities …
of both optical and ultrasound imaging. Although PAI exhibits superior imaging capabilities …
[HTML][HTML] Bayesian optimization with support vector machine model for parkinson disease classification
Parkinson's disease (PD) has become widespread these days all over the world. PD affects
the nervous system of the human and also affects a lot of human body parts that are …
the nervous system of the human and also affects a lot of human body parts that are …
Progress prediction of Parkinson's disease based on graph wavelet transform and attention weighted random forest
Z Xue, T Zhang, L Lin - Expert systems with applications, 2022 - Elsevier
The progress prediction of Parkinson's disease (PD) is one of the most important issues in
early diagnosis of PD. Many researches have been conducted in this field, however, most …
early diagnosis of PD. Many researches have been conducted in this field, however, most …