AIMC Topic: Self Report

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Naturalistic acute pain states decoded from neural and facial dynamics.

Nature communications
Pain remains poorly understood in task-free contexts, limiting our understanding of its neurobehavioral basis in naturalistic settings. Here, we use a multimodal, data-driven approach with intracranial electroencephalography, pain self-reports, and f...

Neural Network-Based Prediction of Perceived Sleep Quality Through Wearable Device Data.

Studies in health technology and informatics
BACKGROUND: This study focuses on the development of a neural network model to predict perceived sleep quality using data from wearable devices. We collected various physiological metrics from 18 participants over four weeks, including heart rate, ph...

Separable amygdala activation patterns in the evaluations of robots.

Cerebral cortex (New York, N.Y. : 1991)
Given the increasing presence of robots in everyday environments and the significant challenge posed by social interactions with robots, it is crucial to gain a deeper understanding into the social evaluations of robots. One potentially effective app...

A comparative study of the 2D- and 3D-based skeleton avatar technology for assessing physical activity and functioning among healthy older adults.

Health informatics journal
Maintaining physical activity (PA) and functioning (mobility, balance) is essential for older adults' well-being and quality of life. However, current methods (functional tests, self-reports) and available techniques (accelerometers, sensors, advanc...

A UK-Wide Study Employing Natural Language Processing to Determine What Matters to People about Brain Health to Improve Drug Development: The Electronic Person-Specific Outcome Measure (ePSOM) Programme.

The journal of prevention of Alzheimer's disease
BACKGROUND: It is important to use outcome measures for novel interventions in Alzheimer's disease (AD) that capture the research participants' views of effectiveness. The electronic Person-Specific Outcome Measure (ePSOM) development programme is un...

What health records data are required for accurate prediction of suicidal behavior?

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: The study sought to evaluate how availability of different types of health records data affect the accuracy of machine learning models predicting suicidal behavior.

Multidimensional Sleep and Mortality in Older Adults: A Machine-Learning Comparison With Other Risk Factors.

The journals of gerontology. Series A, Biological sciences and medical sciences
BACKGROUND: Sleep characteristics related to duration, timing, continuity, and sleepiness are associated with mortality in older adults, but rarely considered in health recommendations. We applied machine learning to: (i) establish the predictive abi...

Measuring Exposure to Incarceration Using the Electronic Health Record.

Medical care
BACKGROUND: Electronic health records (EHRs) are a rich source of health information; however social determinants of health, including incarceration, and how they impact health and health care disparities can be hard to extract.

Physical Activity Change in an RCT: Comparison of Measurement Methods.

American journal of health behavior
We aimed to quantify the agreement between self-report, standard cut-point accelerometer, and machine learning accelerometer estimates of physical activity (PA), and exam- ine how agreement changes over time among older adults in an intervention set...