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norskBlar i forfatter "Chandler, Chelsea"
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Acceptability of collecting speech samples from the elderly via the telephone
(Journal article; Tidsskriftartikkel; Peer reviewed, 2021-04-17)<i>Objective</i> - There is a critical need to develop rapid, inexpensive and easily accessible screening tools for mild cognitive impairment (MCI) and Alzheimer’s disease (AD). We report on the efficacy of collecting speech via the telephone to subsequently develop sensitive metrics that may be used as potential biomarkers by leveraging natural language processing methods.<br><br> <i>Methods</i> ... -
Applying speech technologies to assess verbal memory in patients with serious mental illness
(Journal article; Tidsskriftartikkel; Peer reviewed, 2020-03-11)Verbal memory deficits are some of the most profound neurocognitive deficits associated with schizophrenia and serious mental illness in general. As yet, their measurement in clinical settings is limited to traditional tests that allow for limited administrations and require substantial resources to deploy and score. Therefore, we developed a digital ambulatory verbal memory test with automated ... -
Extending the usefulness of the verbal memory test: The promise of machine learning
(Journal article; Tidsskriftartikkel; Peer reviewed, 2021-01-19)The evaluation of verbal memory is a core component of neuropsychological assessment in a wide range of clinical and research settings. Leveraging story recall to assay neurocognitive function could be made more useful if it were possible to administer frequently (i.e., would allow for the collection of more patient data over time) and automatically assess the recalls with machine learning methods. ... -
Improving the Applicability of AI for Psychiatric Applications through Human-in-the-loop Methodologies
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-05-26)Objectives: Machine learning (ML) and natural language processing have great potential to improve effciency and accuracy in diagnosis, treatment recommendations, predictive interventions, and scarce resource allocation within psychiatry. Researchers often conceptualize such an approach as operating in isolation without much need for human involvement, yet it remains crucial to harness human-inthe-loop ... -
Increasing access to cognitive screening in the elderly: Applying natural language processing methods to speech collected over the telephone
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-08-30)Barriers to healthcare access are widespread in elderly populations, with a major consequence that older people are not benefiting from the latest technologies to diagnose disease. Recent advances in the automated analysis of speech show promising results in the identification of cognitive decline associated with Alzheimer's disease (AD), as well as its purported pre-clinical stage. We utilized ... -
Natural Language Processing and Psychosis: On the Need for Comprehensive Psychometric Evaluation
(Journal article; Tidsskriftartikkel, 2022-06-23)<p><i>Background and Hypothesis:</i> Despite decades of “proof of concept” findings supporting the use of Natural Language Processing (NLP) in psychosis research, clinical implementation has been slow. One obstacle reflects the lack of comprehensive psychometric evaluation of these measures. There is overwhelming evidence that criterion and content validity can be achieved for many purposes, ... -
Reflections on the nature of measurement in language-based automated assessments of patients' mental state and cognitive function
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-09-22)Modern advances in computational language processing methods have enabled new approaches to the measurement of mental processes. However, the field has primarily focused on model accuracy in predicting performance on a task or a diagnostic category. Instead the field should be more focused on determining which computational analyses align best with the targeted neurocognitive/psychological functions ... -
Reflections on the nature of measurement in language-based automated assessments of patients' mental state and cognitive function
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-09-22)Modern advances in computational language processing methods have enabled new approaches to the measurement of mental processes. However, the field has primarily focused on model accuracy in predicting performance on a task or a diagnostic category. Instead the field should be more focused on determining which computational analyses align best with the targeted neurocognitive/psychological functions ... -
Reflections on the nature of measurement in language-based automated assessments of patients' mental state and cognitive function
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-09-22)Modern advances in computational language processing methods have enabled new approaches to the measurement of mental processes. However, the field has primarily focused on model accuracy in predicting performance on a task or a diagnostic category. Instead the field should be more focused on determining which computational analyses align best with the targeted neurocognitive/psychological functions ... -
Towards a temporospatial framework for measurements of disorganization in speech using semantic vectors
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-11-10)Incoherent speech in schizophrenia has long been described as the mind making “leaps” of large distances between thoughts and ideas. Such a view seems intuitive, and for almost two decades, attempts to operationalize these conceptual “leaps” in spoken word meanings have used language-based embedding spaces. An embedding space represents meaning of words as numerical vectors where a greater proximity ... -
Using automated syllable counting to detect missing information in speech transcripts from clinical settings
(Journal article; Tidsskriftartikkel; Peer reviewed, 2022-07-05)Speech rate and quantity reflect clinical state; thus automated transcription holds potential clinical applications. We describe two datasets where recording quality and speaker characteristics affected transcription accuracy. Transcripts of low-quality recordings omitted significant portions of speech. An automated syllable counter estimated actual speech output and quantified the amount of ... -
Using machine learning in psychiatry: The need to establish a framework that nurtures trustworthiness
(Journal article; Tidsskriftartikkel; Peer reviewed, 2019-11-01)The rapid embracing of artificial intelligence in psychiatry has a flavor of being the current “wild west”; a multidisciplinary approach that is very technical and complex, yet seems to produce findings that resonate. These studies are hard to review as the methods are often opaque and it is tricky to find the suitable combination of reviewers. This issue will only get more complex in the absence ...
