AIMC Topic: Prodromal Symptoms

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A review on neuroimaging-based classification studies and associated feature extraction methods for Alzheimer's disease and its prodromal stages.

NeuroImage Apr 13, 2017
Neuroimaging has made it possible to measure pathological brain changes associated with Alzheimer's disease (AD) in vivo. Over the past decade, these measures have been increasingly integrated into imaging signatures of AD by means of classification ...
Neuroimaging Humans Prodromal Symptoms Machine Learning Cognitive Dysfunction Alzheimer Disease
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Early identification of mild cognitive impairment using incomplete random forest-robust support vector machine and FDG-PET imaging.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Feb 7, 2017
Alzheimer's disease (AD) is the most common type of dementia and will be an increasing health problem in society as the population ages. Mild cognitive impairment (MCI) is considered to be a prodromal stage of AD. The ability to identify subjects wit...
Aged Male Cognitive Dysfunction Humans Female Fluorodeoxyglucose F18 Prodromal Symptoms Support Vector Machine Uncertainty Alzheimer Disease Positron-Emission Tomography
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Predicting Prodromal Alzheimer's Disease in Subjects with Mild Cognitive Impairment Using Machine Learning Classification of Multimodal Multicenter Diffusion-Tensor and Magnetic Resonance Imaging Data.

Journal of neuroimaging : official journal of the American Society of Neuroimaging Jan 28, 2015
BACKGROUND: Alzheimer's disease (AD) patients show early changes in white matter (WM) structural integrity. We studied the use of diffusion tensor imaging (DTI) in assessing WM alterations in the predementia stage of mild cognitive impairment (MCI).
Male Reproducibility of Results Prodromal Symptoms Image Enhancement Aged Alzheimer Disease Humans Diffusion Tensor Imaging Machine Learning Image Interpretation, Computer-Assisted Sensitivity and Specificity Algorithms Cognitive Dysfunction Multimodal Imaging
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Eye Movement Characteristics for Predicting a Transition to Psychosis: Longitudinal Changes and Implications.

Schizophrenia bulletin Mar 14, 2025
BACKGROUND AND HYPOTHESIS: Substantive inquiry into the predictive power of eye movement (EM) features for clinical high-risk (CHR) conversion and their longitudinal trajectories is currently sparse. This study aimed to investigate the efficiency of ...
Disease Progression Adolescent Eye Movements Machine Learning Humans Young Adult Female Longitudinal Studies Adult Follow-Up Studies Pursuit, Smooth Male Schizophrenia Eye Movement Measurements Psychotic Disorders Prodromal Symptoms
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EEG-based machine learning models for the prediction of phenoconversion time and subtype in isolated rapid eye movement sleep behavior disorder.

Sleep May 10, 2024
STUDY OBJECTIVES: Isolated rapid eye movement sleep behavior disorder (iRBD) is a prodromal stage of α-synucleinopathies and eventually phenoconverts to overt neurodegenerative diseases including Parkinson's disease (PD), dementia with Lewy bodies (D...
Humans Machine Learning Lewy Body Disease Prodromal Symptoms Synucleinopathies Middle Aged REM Sleep Behavior Disorder Female Disease Progression Aged Electroencephalography Male
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Automatic substantia nigra segmentation in neuromelanin-sensitive MRI by deep neural network in patients with prodromal and manifest synucleinopathy.

Physiological research Dec 30, 2019
Neuromelanin (NM) is a black pigment located in the brain in substantia nigra pars compacta (SN) and locus coeruleus. Its loss is directly connected to the loss of nerve cells in this part of the brain, which plays a role in Parkinson's Disease. Magn...
Case-Control Studies Deep Learning Image Processing, Computer-Assisted Aged Male Middle Aged Prodromal Symptoms Synucleinopathies Magnetic Resonance Imaging Substantia Nigra Melanins Humans Female
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Machine Learning Algorithm Helps Identify Non-Diagnosed Prodromal Alzheimer's Disease Patients in the General Population.

The journal of prevention of Alzheimer's disease Jan 1, 2019
BACKGROUND: Recruiting patients for clinical trials of potential therapies for Alzheimer's disease (AD) remains a major challenge, with demand for trial participants at an all-time high. The AD treatment R and D pipeline includes around 112 agents. I...
Diagnosis, Computer-Assisted Patient Selection Alzheimer Disease Early Diagnosis Prodromal Symptoms Aged, 80 and over Male Humans Middle Aged Machine Learning Algorithms Female Aged
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Use of Machine Learning to Determine Deviance in Neuroanatomical Maturity Associated With Future Psychosis in Youths at Clinically High Risk.

JAMA psychiatry Sep 1, 2018
IMPORTANCE: Altered neurodevelopmental trajectories are thought to reflect heterogeneity in the pathophysiologic characteristics of schizophrenia, but whether neural indicators of these trajectories are associated with future psychosis is unclear.
Machine Learning Prospective Studies Brain Young Adult Male Prognosis Female Humans Predictive Value of Tests Child Risk Assessment Prodromal Symptoms Psychotic Disorders Longitudinal Studies Adolescent Social Skills Neuropsychological Tests Magnetic Resonance Imaging Child, Preschool
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