AIMC Topic: Adult

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Deep Joint Spatiotemporal Network (DJSTN) for Efficient Facial Expression Recognition.

Sensors (Basel, Switzerland)
Understanding a person's feelings is a very important process for the affective computing. People express their emotions in various ways. Among them, facial expression is the most effective way to present human emotional status. We propose efficient ...

Recognizing states of psychological vulnerability to suicidal behavior: a Bayesian network of artificial intelligence applied to a clinical sample.

BMC psychiatry
BACKGROUND: This study aimed to determine conditional dependence relationships of variables that contribute to psychological vulnerability associated with suicide risk. A Bayesian network (BN) was developed and applied to establish conditional depend...

EEG based Classification of Long-term Stress Using Psychological Labeling.

Sensors (Basel, Switzerland)
Stress research is a rapidly emerging area in the field of electroencephalography (EEG) signal processing. The use of EEG as an objective measure for cost effective and personalized stress management becomes important in situations like the nonavaila...

Classification of pulmonary lesion based on multiparametric MRI: utility of radiomics and comparison of machine learning methods.

European radiology
OBJECTIVES: We develop and validate a radiomics model based on multiparametric magnetic resonance imaging (MRI) in the classification of the pulmonary lesion and identify optimal machine learning methods.

Brain MRI analysis using a deep learning based evolutionary approach.

Neural networks : the official journal of the International Neural Network Society
Convolutional neural network (CNN) models have recently demonstrated impressive performance in medical image analysis. However, there is no clear understanding of why they perform so well, or what they have learned. In this paper, a three-dimensional...

Predicting alcohol dependence treatment outcomes: a prospective comparative study of clinical psychologists versus 'trained' machine learning models.

Addiction (Abingdon, England)
BACKGROUND AND AIMS: Clinical staff are typically poor at predicting alcohol dependence treatment outcomes. Machine learning (ML) offers the potential to model complex clinical data more effectively. This study tested the predictive accuracy of ML al...

Robot-Assisted Radical Prostatectomy Associated with Decreased Persistent Postoperative Opioid Use.

Journal of endourology
Minimally invasive surgery offers reduced pain and opioid use postoperatively compared with open surgery, but large-scale comparative studies are lacking. We assessed the incidence of persistent opioid use after open and robot-assisted radical prost...

Assessing the environmental quality of an adapted, play-based LEGO robotics program to achieve optimal outcomes for children with disabilities.

Disability and rehabilitation
PURPOSE: This study assessed the environmental quality of an adapted, play-based LEGO robotics program for children and youth with disabilities to determine the degree to which the activity setting supports the therapeutic goals of the program.