New era of artificial intelligence and machine learning-based detection, diagnosis, and therapeutics in Parkinson's disease
Parkinson's disease (PD) is characterized by the loss of neuronal cells, which leads to
synaptic dysfunction and cognitive defects. Despite the advancements in treatment …
synaptic dysfunction and cognitive defects. Despite the advancements in treatment …
The emerging role of furin in neurodegenerative and neuropsychiatric diseases
Y Zhang, X Gao, X Bai, S Yao, YZ Chang… - Translational …, 2022 - Springer
Furin is an important mammalian proprotein convertase that catalyzes the proteolytic
maturation of a variety of prohormones and proproteins in the secretory pathway. In the …
maturation of a variety of prohormones and proproteins in the secretory pathway. In the …
Diagnosis and classification of Parkinson's disease using ensemble learning and 1D-PDCovNN
In this paper, we proposed a novel approach to diagnose and classify Parkinson's Disease
(PD) using ensemble learning and 1D-PDCovNN, a novel deep learning technique. PD is a …
(PD) using ensemble learning and 1D-PDCovNN, a novel deep learning technique. PD is a …
MNC-Net: Multi-task graph structure learning based on node clustering for early Parkinson's disease diagnosis
L Huang, X Ye, M Yang, L Pan, S hua Zheng - Computers in Biology and …, 2023 - Elsevier
Purpose: The identification of early-stage Parkinson's disease (PD) is important for the
effective management of patients, affecting their treatment and prognosis. Recently …
effective management of patients, affecting their treatment and prognosis. Recently …
[HTML][HTML] Applications of machine learning and deep learning in SPECT and PET imaging: General overview, challenges and future prospects
The integration of positron emission tomography (PET) and single-photon emission
computed tomography (SPECT) imaging techniques with machine learning (ML) algorithms …
computed tomography (SPECT) imaging techniques with machine learning (ML) algorithms …
Mmgk: Multimodality multiview graph representations and knowledge embedding for mild cognitive impairment diagnosis
The diagnosis of mild cognitive impairment (MCI), which is an early stage of Alzheimer's
disease (AD), has great clinical significance. Medical imaging and gene sequencing …
disease (AD), has great clinical significance. Medical imaging and gene sequencing …
Exploiting macro-and micro-structural brain changes for improved Parkinson's disease classification from MRI data
Parkinson's disease (PD) is the second most common neurodegenerative disease. Accurate
PD diagnosis is crucial for effective treatment and prognosis but can be challenging …
PD diagnosis is crucial for effective treatment and prognosis but can be challenging …
Understanding the lived experiences of family caregivers of individuals with dementia in Soweto, a South African Township
A Mahomed, C Pretorius - Dementia, 2022 - journals.sagepub.com
This study was undertaken to understand South African family caregivers' lived experiences
of individuals living with dementia in a predominantly Black African township. A …
of individuals living with dementia in a predominantly Black African township. A …
The differential diagnosis value of radiomics-based machine learning in Parkinson's disease: a systematic review and meta-analysis
J Bian, X Wang, W Hao, G Zhang… - Frontiers in Aging …, 2023 - frontiersin.org
Background In recent years, radiomics has been increasingly utilized for the differential
diagnosis of Parkinson's disease (PD). However, the application of radiomics in PD …
diagnosis of Parkinson's disease (PD). However, the application of radiomics in PD …
The application of risk models based on machine learning to predict endometriosis‐associated ovarian cancer in patients with endometriosis
X Chao, S Wang, J Lang, J Leng… - Acta Obstetricia et …, 2022 - Wiley Online Library
Introduction There is currently no satisfactory model for predicting malignant transformation
of endometriosis. The aim of this study was to construct and evaluate a risk model …
of endometriosis. The aim of this study was to construct and evaluate a risk model …