AIMC Topic: Neuropsychological Tests
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Decoding IBS: a machine learning approach to psychological distress and gut-brain interaction.
BMC gastroenterology
Aug 15, 2024
PURPOSE: Irritable bowel syndrome (IBS) is a diagnosis defined by gastrointestinal (GI) symptoms like abdominal pain and changes associated with defecation. The condition is classified as a disorder of the gut-brain interaction (DGBI), and patients w...
Identifying neuroimaging biomarkers in major depressive disorder using machine learning algorithms and functional near-infrared spectroscopy (fNIRS) during verbal fluency task.
Journal of affective disorders
Aug 14, 2024
One of the most prevalent psychiatric disorders is major depressive disorder (MDD), which increases the probability of suicidal ideation or untimely demise. Abnormal frontal hemodynamic changes detected by functional near-infrared spectroscopy (fNIRS...
Development of an eye-tracking system based on a deep learning model to assess executive function in patients with mental illnesses.
Scientific reports
Aug 6, 2024
Patients with mental illnesses, particularly psychosis and obsessive‒compulsive disorder (OCD), frequently exhibit deficits in executive function and visuospatial memory. Traditional assessments, such as the Rey‒Osterrieth Complex Figure Test (RCFT),...
The minimal computational substrate of fluid intelligence.
Cortex; a journal devoted to the study of the nervous system and behavior
Aug 3, 2024
The quantification of cognitive powers rests on identifying a behavioural task that depends on them. Such dependence cannot be assured, for the powers a task invokes cannot be experimentally controlled or constrained a priori, resulting in unknown vu...
Identification of profiles associated with conversions between the Alzheimer's disease stages, using a machine learning approach.
Alzheimer's research & therapy
Jul 26, 2024
BACKGROUND: The identification of factors involved in the conversion across the different Alzheimer's disease (AD) stages is crucial to prevent or slow the disease progression. We aimed to assess the factors and their combination associated with the ...
Neuropsychological and electrophysiological measurements for diagnosis and prediction of dementia: a review on Machine Learning approach.
Ageing research reviews
Jul 14, 2024
INTRODUCTION: Emerging and advanced technologies in the field of Artificial Intelligence (AI) represent promising methods to predict and diagnose neurodegenerative diseases, such as dementia. By using multimodal approaches, Machine Learning (ML) seem...
AI-based differential diagnosis of dementia etiologies on multimodal data.
Nature medicine
Jul 4, 2024
Differential diagnosis of dementia remains a challenge in neurology due to symptom overlap across etiologies, yet it is crucial for formulating early, personalized management strategies. Here, we present an artificial intelligence (AI) model that har...
Prediction of Alzheimer's disease progression within 6 years using speech: A novel approach leveraging language models.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Jun 25, 2024
INTRODUCTION: Identification of individuals with mild cognitive impairment (MCI) who are at risk of developing Alzheimer's disease (AD) is crucial for early intervention and selection of clinical trials.
Prediction of Cognitive Impairment Risk among Older Adults: A Machine Learning-Based Comparative Study and Model Development.
Dementia and geriatric cognitive disorders
May 22, 2024
INTRODUCTION: The prevalence of cognitive impairment and dementia in the older population is increasing, and thereby, early detection of cognitive decline is essential for effective intervention.
Machine learning for predicting cognitive deficits using auditory and demographic factors.
PloS one
May 14, 2024
IMPORTANCE: Predicting neurocognitive deficits using complex auditory assessments could change how cognitive dysfunction is identified, and monitored over time. Detecting cognitive impairment in people living with HIV (PLWH) is important for early in...
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