AIMC Topic: Happiness

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Machine learning-based prediction of disability risk in geriatric patients with hypertension for different time intervals.

Archives of gerontology and geriatrics
BACKGROUND: The risk of disability in older adults with hypertension is substantially high, and prediction of disability risk is crucial for subsequent management. This study aimed to construct prediction models of disability risk for geriatric patie...

Music Emotion Classification Method Based on Deep Learning and Explicit Sparse Attention Network.

Computational intelligence and neuroscience
In order to improve the accuracy of music emotion recognition and classification, this study combines an explicit sparse attention network with deep learning and proposes an effective emotion recognition and classification method for complex music da...

Enhanced facial expression recognition using 3D point sets and geometric deep learning.

Medical & biological engineering & computing
Facial expression recognition plays an essential role in human conversation and human-computer interaction. Previous research studies have recognized facial expressions mainly based on 2D image processing requiring sensitive feature engineering and c...

(Not) hearing happiness: Predicting fluctuations in happy mood from acoustic cues using machine learning.

Emotion (Washington, D.C.)
Recent popular claims surrounding virtual assistants suggest that computers will soon be able to hear our emotions. Supporting this possibility, promising work has harnessed big data and emergent technologies to automatically predict stable levels of...

Activities suggestion based on emotions in AAL environments.

Artificial intelligence in medicine
The elderly population is increasing and the response of the society was to provide them with services directed to them to cope with their needs. One of the oldest solutions is the retirement home, providing housing and permanent assistance for the e...

A happiness degree predictor using the conceptual data structure for deep learning architectures.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Happiness is a universal fundamental human goal. Since the emergence of Positive Psychology, a major focus in psychological research has been to study the role of certain factors in the prediction of happiness. The conventio...

Do positive psychosocial factors contribute to the prediction of coronary artery disease? A UK Biobank-based machine learning approach.

European journal of preventive cardiology
AIMS: Most prediction models for coronary artery disease (CAD) compile biomedical and behavioural risk factors using linear multivariate models. This study explores the potential of integrating positive psychosocial factors (PPFs), including happines...

Artificial neural networks-based classification of emotions using wristband heart rate monitor data.

Medicine
Heart rate variability (HRV) is an objective measure of emotional regulation. This study aimed to estimate the accuracy with which an artificial neural network (ANN) algorithm could classify emotions using HRV data that were obtained using wristband ...

Daytime Data and LSTM can Forecast Tomorrow's Stress, Health, and Happiness.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Accurately forecasting well-being may enable people to make desirable behavioral changes that could improve their future well-being. In this paper, we evaluate how well an automated model can forecast the next-day's well-being (specifically focusing ...