Related publications (32)

Generalization and Personalization of Machine Learning for Multimodal Mobile Sensing in Everyday Life

Lakmal Buddika Meegahapola

A range of behavioral and contextual factors, including eating and drinking behavior, mood, social context, and other daily activities, can significantly impact an individual's quality of life and overall well-being. Therefore, inferring everyday life aspe ...
EPFL2024

Optical Urea Sensing in Sweat for Kidney Healthcare by Sensitive and Selective Non-enhanced Raman Spectroscopy

Christian Enz, Sandro Carrara, Assim Boukhayma, Ata Jedari Golparvar, Mattia Petrelli

Sweat biomarker analysis has attracted much interest in applications ranging from sports to wearable healthcare. Among all the sweat biomolecules, abnormal urea levels have been linked to several complications, particularly renal dysfunction. Here, we repo ...
SPIE-INT SOC OPTICAL ENGINEERING2023

Predicting Changes in Depression Severity Using the PSYCHE-D (Prediction of Severity Change-Depression) Model Involving Person-Generated Health Data: Longitudinal Case-Control Observational Study

Martin Jaggi, Mariko Makhmutova

Background: In 2017, an estimated 17.3 million adults in the United States experienced at least one major depressive episode, with 35% of them not receiving any treatment. Underdiagnosis of depression has been attributed to many reasons, including stigma s ...
Toronto2022

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.