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Identification of Aging Faces using A-stack Classification Model

Publications associées (31)

Machine learning-derived gut microbiome signature predicts fatty liver disease in the presence of insulin resistance

A simple predictive biomarker for fatty liver disease is required for individuals with insulin resistance. Here, we developed a supervised machine learning-based classifier for fatty liver disease using fecal 16S rDNA sequencing data. Based on the Kangbuk ...

Nature Portfolio2022

Evaluation of a shortened version of the Action Research Arm Test (ARAT) for upper extremity function after stroke: The Mini-ARAT

Friedhelm Christoph Hummel, Lisa Aïcha Mireille Julie Fleury

Objectives (i) to create a shortened version of the Action Research Arm Test scale, (ii) to investigate its psychometric properties compared to the original scale and (iii) to externally validate it within an independent cohort. Design Prospective longitud ...

SAGE PUBLICATIONS LTD2022

The competent Computational Thinking Test: Development and Validation of an Unplugged Computational Thinking Test for Upper Primary School

Francesco Mondada, Laila Abdelsalam El-Hamamsy, Jessica Elke Dehler Zufferey, Barbara Bruno

With the increasing importance of Computational Thinking (CT) at all levels of education, it is essential to have valid and reliable assessments. Currently, there is a lack of such assessments in upper primary school. That is why we present the development ...

2022

Using Machine Learning to Predict Mortality for COVID-19 Patients on Day 0 in the ICU

Sahand Jamal Rahi, Nahal Mansouri

Rationale: Given the expanding number of COVID-19 cases and the potential for new waves of infection, there is an urgent need for early prediction of the severity of the disease in intensive care unit (ICU) patients to optimize treatment strategies.Objecti ...

FRONTIERS MEDIA SA2022

A framework for occupancy detection and tracking using floor-vibration signals

Ian Smith, Slah Drira

In sensed buildings, information related to occupant movement helps optimize important func-tionalities such as caregiving, energy management, and security enhancement. Typical sensing approaches for occupant tracking rely on mobile devices and cameras. Th ...

2022

Kernel Density Estimation of Electromyographic Signals and Ensemble Learning for Highly Accurate Classification of a Large Set of Hand/Wrist Motions

Parviz Ghaderi

The performance of myoelectric control highly depends on the features extracted from surface electromyographic (sEMG) signals. We propose three new sEMG features based on the kernel density estimation. The trimmed mean of density (TMD), the entropy of dens ...

FRONTIERS MEDIA SA2022

Are GAN-based Morphs Threatening Face Recognition?

Sébastien Marcel, Eklavya Sarkar, Laurent Colbois

Morphing attacks are a threat to biometric systems where the biometric reference in an identity document can be altered. This form of attack presents an important issue in applications relying on identity documents such as border security or access control ...

IEEE2022

All you need is time to generalise the Goman-Khrabrov dynamic stall model

Fatma Ayancik Cinoglu, Karen Ann J Mulleners

Dynamic stall on airfoils negatively impacts their aerodynamic performance and can lead to structural damage. Accurate prediction and modelling of the dynamic stall loads are crucial for a more robust design of wings and blades that operate under unsteady ...

Cambridge University Press2022

Predicting Superagers by Machine Learning Classification Based on the Functional Brain Connectome Using Resting-State Functional Magnetic Resonance Imaging

Chang-Hyun Park

Superagers are defined as older adults who have youthful memory performance comparable to that of middle-aged adults. Classifying superagers based on the brain connectome using machine learning modeling can provide important insights on the physiology unde ...

OXFORD UNIV PRESS INC2021

Wearable and Continuous Prediction of Passage of Time Perception for Monitoring Mental Health

David Atienza Alonso, Adriana Arza Valdes, Lara Orlandic

A person’s passage of time perception (POTP) is strongly linked to their mental state and stress response, and can therefore provide an easily quantifiable means of continuous mental health monitoring. In this work, we develop a custom experiment and Machi ...

2021

Ecological momentary assessment of emotional processing: An exploratory analysis comparing daily life and a psychotherapy analogue session

Mehdi Gholam, Hélène Beuchat, Loris Grandjean

Background: Emotional processing has been studied in psychotherapy as a state-dependent, sequential process of change. So far, no studies have applied this conceptualisation of emotional processing to the assessments of emotion in daily life. This is parti ...

WILEY2022