A fast, resource efficient, and reliable rule-based system for COVID-19 symptom identification.

Objective: With COVID-19, there was a need for a rapidly scalable annotation system that facilitated real-time integration with clinical decision support systems (CDS). Current annotation systems suffer from a high-resource utilization and poor scalability limiting real-world integration with CDS. A potential solution to mitigate these issues is to use the rule-based gazetteer developed at our institution.

Using consumer-wearable technology for remote assessment of physiological response to stress in the naturalistic environment.

Psychosocial stress is a major risk factor for morbidity and mortality related to a wide range of health conditions and has a significant negative impact on public health. Quantifying exposure to stress in the naturalistic environment can help to better understand its health effects and identify strategies for timely intervention. The objective of the current project was to develop and test the infrastructure and methods necessary for using wearable technology to quantify individual response to stressful situations and to determine if popular and accessible fitness trackers such as Fitbit® equipped with an optical heart rate (HR) monitor could be used to detect physiological response to psychosocial stress in everyday life.

Altered verbal fluency processes in older adults with age-related hearing loss.

Epidemiological studies have linked age-related hearing loss (ARHL) with an increased risk of neurocognitive decline. Difficulties in speech perception with subsequent changes in brain morphometry, including regions important for lexical-semantic memory, are thought to be a possible mechanism for this relationship. This study investigated differences in automatic and executive lexical-semantic processes on verbal fluency tasks in individuals with acquired hearing loss.

Recurrent Deep Network Models for Clinical NLP Tasks: Use Case with Sentence Boundary Disambiguation.

Although a number of foundational natural language processing (NLP) tasks like text segmentation are considered a simple problem in the general English domain dominated by well-formed text, complexities of clinical documentation lead to poor performance of existing solutions designed for the general English domain. We present an alternative solution that relies on a convolutional neural network layer followed by a bidirectional long short-term memory layer (CNN-Bi-LSTM) for the task of sentence boundary disambiguation and describe an ensemble approach for domain adaptation using two training corpora. Implementations using the Keras neural-networks API are available at https://github.

An Opportunity for Pharmacists to Help Improve Coordination and Continuity of Patient Health Care.

Pharmacist workforce researchers are predicting a potential surplus of pharmacists in the United States that might result in pharmacists being available for engagement in new roles. The objective for this study was to describe consumer opinions regarding medication use, the health care system, and pharmacists to help identify new roles for pharmacists from the consumer perspective. Data were obtained from the 2015 and 2016 National Consumer Surveys on the Medication Experience and Pharmacist Roles.

Recurrent perseverations on semantic verbal fluency tasks as an early marker of cognitive impairment.

Introduction: Our objective was to examine the association between perseverations produced on the semantic verbal fluency (SVF) task in asymptomatic individuals and the future diagnosis of cognitive impairment (CI).

Method: Participants were individuals participating in the Mayo Clinic Study of Aging (N = 1269, M = 79.3 years, SD = 5.

Classifying Supplement Use Status in Clinical Notes.

Clinical notes contain rich information about supplement use that is critical for detecting adverse interactions between supplements and prescribed medications. It is important to know the context in which supplements are mentioned in clinical notes to be able to correctly identify patients that either currently take the supplement or did so in the past. We applied text mining methods to automatically classify supplement use into four status categories: Continuing (C), Discontinued (D), Started (S), and Unclassified (U).

Detecting clinically relevant new information in clinical notes across specialties and settings.

Background: Automated methods for identifying clinically relevant new versus redundant information in electronic health record (EHR) clinical notes is useful for clinicians and researchers involved in patient care and clinical research, respectively. We evaluated methods to automatically identify clinically relevant new information in clinical notes, and compared the quantity of redundant information across specialties and clinical settings.

Methods: Statistical language models augmented with semantic similarity measures were evaluated as a means to detect and quantify clinically relevant new and redundant information over longitudinal clinical notes for a given patient.

Towards Comprehensive Clinical Abbreviation Disambiguation Using Machine-Labeled Training Data.

Abbreviation disambiguation in clinical texts is a problem handled well by fully supervised machine learning methods. Acquiring training data, however, is expensive and would be impractical for large numbers of abbreviations in specialized corpora. An alternative is a semi-supervised approach, in which training data are automatically generated by substituting long forms in natural text with their corresponding abbreviations.

Use of an automated mobile application to assess effects of nicotine withdrawal on verbal fluency: A pilot study.

Mild-to-moderate impairment in frontally mediated functions such as sustained attention, working memory, and inhibition have been found to occur during tobacco withdrawal and may present a barrier to successful cessation. These findings have led to studies evaluating cessation treatments that target nicotine withdrawal related cognitive impairment. The instruments currently used to assess cognitive function provide detailed and specific information but have limitations including being time consuming, cumbersome, anxiety provoking, and having poor ecological validity.

Corpus domain effects on distributional semantic modeling of medical terms.

Motivation: Automatically quantifying semantic similarity and relatedness between clinical terms is an important aspect of text mining from electronic health records, which are increasingly recognized as valuable sources of phenotypic information for clinical genomics and bioinformatics research. A key obstacle to development of semantic relatedness measures is the limited availability of large quantities of clinical text to researchers and developers outside of major medical centers. Text from general English and biomedical literature are freely available; however, their validity as a substitute for clinical domain to represent semantics of clinical terms remains to be demonstrated.

Characterizing cognitive performance in a large longitudinal study of aging with computerized semantic indices of verbal fluency.

A computational approach for estimating several indices of performance on the animal category verbal fluency task was validated, and examined in a large longitudinal study of aging. The performance indices included the traditional verbal fluency score, size of semantic clusters, density of repeated words, as well as measures of semantic and lexical diversity. Change over time in these measures was modeled using mixed effects regression in several groups of participants, including those that remained cognitively normal throughout the study (CN) and those that were diagnosed with mild cognitive impairment (MCI) or Alzheimer's disease (AD) dementia at some point subsequent to the baseline visit.

A comparative observational study of inpatient clinical note-entry and reading/retrieval styles adopted by physicians.

Objective: The objective of this study is to understand physicians' usage of inpatient notes by (i) ascertaining different clinical note-entry and reading/retrieval styles in two different and widely used Electronic Health Record (EHR) systems, (ii) extrapolating potential factors leading to adoption of various note-entry and reading/retrieval styles and (iii) determining the amount of time to task associated with documenting different types of clinical notes.

Methods: In order to answer "what" and "why" questions on physicians' adoption of certain-note-entry and reading/retrieval styles, an ethnographic study entailing Internal Medicine residents, with a mixed data analysis approach was performed. Participants were observed interacting with two different EHR systems in inpatient settings.

Using Automatic Speech Recognition to Assess Spoken Responses to Cognitive Tests of Semantic Verbal Fluency.

Cognitive tests of verbal fluency (VF) consist of verbalizing as many words as possible in one minute that either start with a specific letter of the alphabet or belong to a specific semantic category. These tests are widely used in neurological, psychiatric, mental health, and school settings and their validity for clinical applications has been extensively demonstrated. However, VF tests are currently administered and scored manually making them too cumbersome to use, particularly for longitudinal cognitive monitoring in large populations.

Analyzing Operative Note Structure in Development of a Section Header Resource.

Operative notes contain essential details of surgical procedures and are an important form of clinical documentation. Sections within operative notes segment provide high level note structure. We evaluated the HL7 Implementation Guide for Clinical Document Architecture Release 2.

Pharmacokinetic-pharmacodynamic modelling of intravenous and oral topiramate and its effect on phonemic fluency in adult healthy volunteers.

Aims: The aim was to develop a quantitative approach that characterizes the magnitude of and variability in phonemic generative fluency scores as measured by the Controlled Oral Word Association (COWA) test in healthy volunteers after administration of an oral and a novel intravenous (IV) formulation of topiramate (TPM).

Methods: Nonlinear mixed-effects modelling was used to describe the plasma TPM concentrations resulting from oral or IV administration. A pharmacokinetic-pharmacodynamic (PK-PD) model was developed sequentially to characterize the effect of TPM concentrations on COWA with different distributional assumptions.

Language networks associated with computerized semantic indices.

Tests of generative semantic verbal fluency are widely used to study organization and representation of concepts in the human brain. Previous studies demonstrated that clustering and switching behavior during verbal fluency tasks is supported by multiple brain mechanisms associated with semantic memory and executive control. Previous work relied on manual assessments of semantic relatedness between words and grouping of words into semantic clusters.

A computational linguistic measure of clustering behavior on semantic verbal fluency task predicts risk of future dementia in the nun study.

Generative semantic verbal fluency (SVF) tests show early and disproportionate decline relative to other abilities in individuals developing Alzheimer's disease. Optimal performance on SVF tests depends on the efficiency of using clustered organization of semantically related items and the ability to switch between clusters. Traditional approaches to clustering and switching have relied on manual determination of clusters.

Quantification of Speech Disfluency as a Marker of Medication-Induced Cognitive Impairment: An Application of Computerized Speech Analysis in Neuropharmacology.

We present the results of a study investigating the use of speech and language characteristics extracted from spontaneous spoken discourse to assess changes in cognitive function. Specifically, we investigated the use of automatic speech recognition technology to characterize spontaneous speech disfluency induced by topiramate, an anti-epileptic medication with language-related side-effects. We audio recorded spontaneous speech samples from 20 participants during several picture description tasks and analyzed the recordings automatically and manually to extract a range of spoken fluency measurements including speech discontinuities (e.

Automated semantic indices related to cognitive function and rate of cognitive decline.

The objective of our study is to introduce a fully automated, computational linguistic technique to quantify semantic relations between words generated on a standard semantic verbal fluency test and to determine its cognitive and clinical correlates. Cognitive differences between patients with Alzheimer's disease and mild cognitive impairment are evident in their performance on the semantic verbal fluency test. In addition to the semantic verbal fluency test score, several other performance characteristics sensitive to disease status and predictive of future cognitive decline have been defined in terms of words generated from semantically related categories (clustering) and shifting between categories (switching).

The role of the electronic medical record in the assessment of health related quality of life.

We applied a hybrid Natural Language Processing (NLP) and machine learning (ML) approach (NLP-ML) to assessment of health related quality of life (HRQOL). The approach uses text patterns extracted from HRQOL inventories and electronic medical records (EMR) as predictive features for training ML classifiers. On a cohort of 200 patients, our approach agreed with patient self-report (EQ5D) and manual audit of the EMR 65-74% of the time.

Effects of age and dementia on temporal cycles in spontaneous speech fluency.

Spontaneous speech of healthy adults consists of alternating periods of fluent and hesitant segments, forming temporal cycles in speech fluency. The regularity of these cycles may be related to the functioning of brain networks during speech planning and execution. This paper investigates the theoretical link between human cognitive functioning and temporal cycles in speech production using a quantitative time series analysis to characterize the regularity and frequency of temporal cycles in adults with differing levels and etiology of cognitive decline.

Towards a framework for developing semantic relatedness reference standards.

Our objective is to develop a framework for creating reference standards for functional testing of computerized measures of semantic relatedness. Currently, research on computerized approaches to semantic relatedness between biomedical concepts relies on reference standards created for specific purposes using a variety of methods for their analysis. In most cases, these reference standards are not publicly available and the published information provided in manuscripts that evaluate computerized semantic relatedness measurement approaches is not sufficient to reproduce the results.

Computerized analysis of speech and language to identify psycholinguistic correlates of frontotemporal lobar degeneration.

Objective: To evaluate the use of a semiautomated computerized system for measuring speech and language characteristics in patients with frontotemporal lobar degeneration (FTLD).

Background: FTLD is a heterogeneous disorder comprising at least 3 variants. Computerized assessment of spontaneous verbal descriptions by patients with FTLD offers a detailed and reproducible view of the underlying cognitive deficits.

A thematic analysis for how patients, prescribers, experts, and patient advocates view the prescription choice process.

Background: Typically, patients are unaware of the cost consequences regarding prescribing decisions during their clinical encounter and rarely talk with their physicians about costs of prescription drugs. Prescription medications that are deemed by patients to be too costly when the costs become known after purchase are discontinued or used at suboptimal doses compared to prescription medications that are deemed to be worth the cost.

Objectives: To learn more about the prescription choice process from several viewpoints, the purpose of this study was to uncover and describe how patients, prescribers, experts, and patient advocates view the prescription choice process.