EWA - Early Warning of Alzheimer

Včasné zistenie príznakov Alzheimerovej choroby a iných neurodegeneratívnych ochorení

12-item version of Boston Naming Test: usefulness in the diagnosis of primary progressive aphasia, frontotemporal dementia, and Alzheimer's disease
The 12-item version of the Boston Naming Test (BNT) was adapted to Argentina for the detection of dementia due to Alzheimer's disease (AD), with scores similar to the original 60-item version (sensitivity and specificity of 85 and 94%, respectively) without demographic influence (age and educational level). To date, no publications on the use of abbreviated BNT in other degenerative pathologies with language impairment have been reported...



Surfboard: Audio Feature Extraction for Modern Machine Learning
We introduce Surfboard, an open-source Python library for extracting audio features with application to the medical do-main. Surfboard is written with the aim of addressing pain points of existing libraries and facilitating joint use with modern machine learning frameworks. The package can be accessed both programmatically in Python and via its command line interface, allowing it to be easily integrated within machine learning workflows. It builds on state-of-the-art audio analysis packages and offers multiprocessing support for processing large workloads...







Linguistic markers predict onset of Alzheimer’s disease
To study linguistic performance as an early biomarker of AD, we performed predictive modeling of future diagnosis of AD from a cognitively normal baseline of Framingham Heart Study participants. The linguistic variables were derived from written responses to the cookie-theft picture-description task. We compared the predictive performance of linguistic variables with clinical and neuropsychological variables...





Artificial Intelligence Techniques for Automated Diagnosis of Neurological Disorders
Authors have been advocating the research ideology that a computer-aided diagnosis (CAD) system trained using lots of patient data and physiological signals and images based on adroit integration of advanced signal processing and artificial intelligence (AI)/machine learning techniques in an automated fashion can assist neurologists, neurosurgeons, radiologists, and other medical providers to make better clinical decisions...



Usefulness of a 15-Item Version of the Boston Naming Test in Neuropsychological Assessment of Low-Educational Elders With Dementia
The purpose of this study was to validate a reduced version (15 items) of the Boston Naming Test (BNT) in a sample of 78 low-educational elderly persons with or without dementia, as determined by independent assessment with a battery of cognitive tests. The reduced version was found to be equivalent to the complete BNT, and to have criterion validity with respect to other measures of dementia. We conclude that the reduced version is a useful instrument for assessing patients who require shorter testing methods because of severe cognitive deterioration or their low level of education...



Cognitive Interventions in Parkinson’s Disease: Where We Want to Go within 20 Years
Today, meta-analyses demonstrate that cognitive training is safe and effective to enhance vulnerable cognitive functions in patients with Parkinson’s disease (PD), so that cognitive interventions can be regarded as a promising approach to treat or even prevent cognitive dysfunction in PD. However, many research gaps exist. Thus, this article aims to identify relevant research topics with regard to cognitive interventions in PD patients for the next 20 years...



Common Sense Reasoning – From Cyc to Intelligent Assistant
Semi-formally represented knowledge, such as the use of standardized keywords, is a traditional and valuable mechanism for helping people to access information. Extending that mechanism to include formally represented knowledge (based on a shared ontology) presents a more effective way of sharing large bodies of knowledge between groups; reasoning systems that draw on that knowledge are the logical counterparts to tools that perform well on a single, rigidly defined task...





Automatic Feature Extraction for Classifying Audio Data
Today, many private households as well as broadcasting or film companies own large collections of digital music plays. These are time series that differ from, e.g., weather reports or stocks market data. The task is normally that of classification, not prediction of the next value or recognizing a shape or motif. New methods for extracting features that allow to classify audio data have been developed. However, the development of appropriate feature extraction methods is a tedious effort, particularly because every new classification task requires tailoring the feature set anew...



Speech Analysis by Natural Language Processing Techniques: A Possible Tool for Very Early Detection of Cognitive Decline?
The discovery of early, non-invasive biomarkers for the identification of “preclinical” or “pre-symptomatic” Alzheimer’s disease and other dementias is a key issue in the field, especially for research purposes, the design of preventive clinical trials, and drafting population-based health care policies. Complex behaviors are natural candidates for this. In particular, recent studies have suggested that speech alterations might be one of the earliest signs of cognitive decline, frequently noticeable years before other cognitive deficits become apparent...