A few-shot learning approach with domain adaptation for personalized real-life stress detection in close relationships

K Feng, JB Duong, KE Carta, S Walters… - arXiv preprint arXiv …, 2022 - arxiv.org
We design a metric learning approach that aims to address computational challenges that
yield from modeling human outcomes from ambulatory real-life data. The proposed metric …

Modeling inter-individual differences in ambulatory-based multimodal signals via metric learning: a case study of personalized well-being estimation of healthcare …

P Paromita, K Mundnich, A Nadarajan… - Frontiers in Digital …, 2023 - frontiersin.org
Introduction Intelligent ambulatory tracking can assist in the automatic detection of
psychological and emotional states relevant to the mental health changes of professionals …

Developing an Interpretable Machine Learning Model for Divorce Prediction

MS Satu, MMH Riyad, MAT Rony - … Conference on Big Data, IoT and …, 2023 - Springer
Divorce is a legal process that formally ends a marital union between two individuals. In
modern times, it is considered one of the major social issues which is rapidly increasing day …

Group-specific models of healthcare workers' well-being using iterative participant clustering

V Ravuri, P Paromita, K Mundnich… - 2020 Second …, 2020 - ieeexplore.ieee.org
Healthcare workers often experience stress and burnout due to the demanding job
responsibilities and long work hours. Ambulatory monitoring devices, such as wearable and …

[PDF][PDF] Что определяет удовлетворенность близкими отношениями? Обзор и мета-анализ

АС Панфилова - Ученые записки Института психологии РАН, 2021 - scientific-letters.ru
Аннотация В статье приводятся результаты обзора публикаций, использующих
корреляционный, регрессионный анализ и методы машинного обучения, по проблеме …

Fostering a Healthier Work Environment: An Artificial Intelligence-Based Approach for Identifying Individual and Team Wellbeing in Real-World Settings

P Paromita - 2023 - oaktrust.library.tamu.edu
Professionals with high job responsibilities, such as healthcare workers or astronauts, often
experience significant stress due to their demanding roles. This stress can lead to burnout …

Investigating Group-Specific Models of Hospital Workers' Well-Being: Implications for Algorithmic Bias

V Ravuri, P Paromita, K Mundnich… - … Journal of Semantic …, 2020 - World Scientific
Hospital workers often experience burnout due to the demanding job responsibilities and
long work hours. Data yielding from ambulatory monitoring combined with machine learning …

Introduction to the Special Section on Computational Modeling and Understanding of Emotions in Conflictual Social Interactions

R Damiano, V Patti, C Clavel, P Rosso - ACM Transactions on Internet …, 2020 - dl.acm.org
In today's media and social media, the expression of social, cultural, and political opinions
often features a strong affective component, especially when it occurs in highly polarized …

[PDF][PDF] Developing Personalized Algorithms for Sensing Mental Health Symptoms in Daily Life

A Timmons, AA Tutul, K Avramidis, K Carta, S Walters… - osf.io
The integration of artificial intelligence (AI) and pervasive computing offers new ways to
sense mental health symptoms and deliver real-time interventions via mobile devices. This …

[引用][C] PERSONALIZED ESTIMATION OF DAILY EMOTIONS AND INTERPERSONALCONFLICT BETWEEN ROMANTIC PARTNERS VIA METRIC LEARNING

V Venkataramu - 2022