Publications associées à Classification internationale des maladies

Machine learning and its impact on psychiatric nosology: Findings from a qualitative study among German and Swiss experts

The increasing integration of Machine Learning (ML) techniques into clinical care, driven in particular by Deep Learning (DL) using Artificial Neural Nets (ANNs), promises to reshape medical practice on various levels and across multiple medical fields. Mu ...

2023

Antibody-Coated Wearable Organic Electrochemical Transistors for Cortisol Detection in Human Sweat

Danick Briand, Silvia Demuru, Marwan El Chazli, Jaemin Kim

The dysregulation of the hormone cortisol is related to several pathological states, and its monitoring could help prevent severe stress, fatigue, and mental diseases. While wearable antibody-based biosensors could allow real-time and simple monitoring of ...

AMER CHEMICAL SOC2022

Late Fusion of the Available Lexicon and Raw Waveform-based Acoustic Modeling for Depression and Dementia Recognition

Petr Motlicek, Mathew Magimai Doss, Julian David Fritsch, Subrahmanya Pavankumar Dubagunta

Mental disorders, e.g. depression and dementia, are categorized as priority conditions according to the World Health Organization (WHO). When diagnosing, psychologists employ structured questionnaires/interviews, and different cognitive tests. Although acc ...

ISCA-INT SPEECH COMMUNICATION ASSOC2021

Study of brain metabolic dysfunctions in animal models of mood disorder using magnetic resonance spectroscopy

Antoine Timothée Cherix

Mood disorders, in particular depression, are a major burden of our society. Due to the poor knowledge of the biological basis of these diseases, classification remains based on arbitrary symptomatic parameters. As a result, the existing pharmacological tr ...

EPFL2020

A Brain-Controlled Exoskeleton with Cascaded Event-Related Desynchronization Classifiers

José del Rocio Millán Ruiz, Kyuhwa Lee, Ricardo Andres Chavarriaga Lozano, Dong Liu, Dong Liu

This paper describes a brain-machine interface for the online control of a powered lower-limb exoskeleton based on electroencephalogram (EEG) signals recorded over the user’s sensorimotor cortical areas. We train a binary decoder that can distinguish two d ...

Elsevier2017

Brain metabolic alterations in mice subjected to postnatal traumatic stress and in their offspring

João Miguel das Neves Duarte, Alberto Corcoba

Adverse environmental and social conditions early in life have a strong impact on health. They are major risk factors for mental diseases in adulthood and, in some cases, their effects can be transmitted across generations. The consequences of detrimental ...

Sage Publications Inc2017

A New Outlook on Mental Illnesses: Glial Involvement Beyond the Glue

Pierre Magistretti, Maha Elsayed

Mental illnesses have long been perceived as the exclusive consequence of abnormalities in neuronal functioning. Until recently, the role of glial cells in the pathophysiology of mental diseases has largely been overlooked. However recently, multiple lines ...

Frontiers Media Sa2015

Volume-based vs. voxel-based brain morphometry in Alzheimer's disease prediction

Meritxell Bach Cuadra, Bénédicte Marie Maréchal, Delphine Ribes Lemay, Reto Meuli, Alessandro Daducci, Cristina Granziera, Daniel Andreas Schmitter, Gunnar Krüger, Alexis Roche, Ahmed Abdulkadir

Voxel-based morphometry from conventional T1-weighted images has proved effective to quantify Alzheimer's disease (AD) related brain atrophy and to enable accurate automated classification of AD patients, mild cognitive impaired (MCI) patients and elderly ...

Proceedings of 23rd International Society for Magnetic Resonance in Medicine (ISMRM) Conference2014

Development of a Small D-Enantiomeric Alzheimer's Amyloid-beta Binding Peptide Ligand for Future In Vivo Imaging Applications

Andrea Pfeifer, Andreas Muhs

Alzheimer's disease (AD) is a devastating disease affecting predominantly the aging population. One of the characteristic pathological hallmarks of AD are neuritic plaques, consisting of amyloid-beta peptide (A beta). While there has been some advancement ...

Public Library Science2012

Effects of hardware heterogeneity on the performance of SVM Alzheimer's disease classifier

Bénédicte Marie Maréchal, Ahmed Abdulkadir, Gunnar Krüger

Fully automated machine learning methods based on structural magnetic resonance imaging data can assist radiologists in the diagnosis of Alzheimer's disease (AD). These algorithms require large data sets to learn the separation of subjects with and without ...

Elsevier2011