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...
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...
Commonsense reasoning at scale is a critical problem for modern cognitive systems. Large theories have millions of axioms, but only a handful are relevant for answering a giv-
en goal query. Irrelevant axioms increase the search space, overwhelming unoptimized inference engines in large theories...
We used databases Scopus, Web of Science and Google Scholar to create the report. Inclusion criteria have been
created from key words - voice, speech, Alzheimer detection and natural language processing. We have focused on articles from
the beginning of 2019 until now. Articles that did not contain full-text in English were excluded...
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, specifically machine learning, has found numerous applications in computer-aided diagnostics, monitoring and management of neurodegenerative movement disorders of parkinsonian type. These tasks are not trivial due to high inter-subject variability and similarity of clinical presentations of different neurodegenerative disorders in the early stages...
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...
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...
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...
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...
Although memory impairment is the main symptom of Alzheimer’s disease (AD), language impairment can be an important marker. Relatively few studies of language in AD quantify the impairments in connected speech using computational techniques...
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...
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...
Dementia is an umbrella term—caused by a large number of specific diagnoses, including several neurodegenerative disorders. Alzheimer’s disease (AD) is now the most common cause of dementia in advanced countries, while dementia due to neurosyphilis was the leading cause a century ago...