AIMC Topic: Humans

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The RoScan Thermal 3D Body Scanning System: Medical Applicability and Benefits for Unobtrusive Sensing and Objective Diagnosis.

Sensors (Basel, Switzerland)
The RoScan is a novel, high-accuracy multispectral surface scanning system producing colored 3D models that include a thermal layer. (1) Background: at present, medicine still exhibits a lack of objective diagnostic methods. As many diseases involve ...

The Perceptions of People with Dementia and Key Stakeholders Regarding the Use and Impact of the Social Robot MARIO.

International journal of environmental research and public health
People with dementia often experience loneliness and social isolation. This can result in increased cognitive decline which, in turn, has a negative impact on quality of life. This paper explores the use of the social robot, MARIO, with older people ...

Computer-aided diagnosis of pectus excavatum using CT images and deep learning methods.

Scientific reports
Pectus excavatum (PE) is one of the most common chest wall defects. Accurate assessment of PE deformities is critical for effective surgical intervention. Index-based evaluations have become the standard for objectively estimating PE, however, these ...

Validation of deep learning natural language processing algorithm for keyword extraction from pathology reports in electronic health records.

Scientific reports
Pathology reports contain the essential data for both clinical and research purposes. However, the extraction of meaningful, qualitative data from the original document is difficult due to the narrative and complex nature of such reports. Keyword ext...

Comparing supervised and unsupervised approaches to emotion categorization in the human brain, body, and subjective experience.

Scientific reports
Machine learning methods provide powerful tools to map physical measurements to scientific categories. But are such methods suitable for discovering the ground truth about psychological categories? We use the science of emotion as a test case to expl...

Machine learning to predict early TNF inhibitor users in patients with ankylosing spondylitis.

Scientific reports
We aim to generate an artificial neural network (ANN) model to predict early TNF inhibitor users in patients with ankylosing spondylitis. The baseline demographic and laboratory data of patients who visited Samsung Medical Center rheumatology clinic ...

EventEpi-A natural language processing framework for event-based surveillance.

PLoS computational biology
According to the World Health Organization (WHO), around 60% of all outbreaks are detected using informal sources. In many public health institutes, including the WHO and the Robert Koch Institute (RKI), dedicated groups of public health agents sift ...

PredAmyl-MLP: Prediction of Amyloid Proteins Using Multilayer Perceptron.

Computational and mathematical methods in medicine
Amyloid is generally an aggregate of insoluble fibrin; its abnormal deposition is the pathogenic mechanism of various diseases, such as Alzheimer's disease and type II diabetes. Therefore, accurately identifying amyloid is necessary to understand its...

A neural network for prediction of risk of nosocomial infection at intensive care units: a didactic preliminary model.

Einstein (Sao Paulo, Brazil)
OBJECTIVE: To propose a preliminary artificial intelligence model, based on artificial neural networks, for predicting the risk of nosocomial infection at intensive care units.

A data driven methodology for social science research with left-behind children as a case study.

PloS one
For decades, traditional correlation analysis and regression models have been used in social science research. However, the development of machine learning algorithms makes it possible to apply machine learning techniques for social science research ...