Search Results for author: Dimitris Spathis

Found 17 papers, 7 papers with code

Looking for Out-of-Distribution Environments in Multi-center Critical Care Data

no code implementations26 May 2022 Dimitris Spathis, Stephanie L. Hyland

Clinical machine learning models show a significant performance drop when tested in settings not seen during training.

Evaluating Contrastive Learning on Wearable Timeseries for Downstream Clinical Outcomes

no code implementations13 Nov 2021 Kevalee Shah, Dimitris Spathis, Chi Ian Tang, Cecilia Mascolo

Vast quantities of person-generated health data (wearables) are collected but the process of annotating to feed to machine learning models is impractical.

Contrastive Learning Data Augmentation +2

Anticipatory Detection of Compulsive Body-focused Repetitive Behaviors with Wearables

1 code implementation21 Jun 2021 Benjamin Lucas Searle, Dimitris Spathis, Marios Constantinides, Daniele Quercia, Cecilia Mascolo

Body-focused repetitive behaviors (BFRBs), like face-touching or skin-picking, are hand-driven behaviors which can damage one's appearance, if not identified early and treated.

The INTERSPEECH 2021 Computational Paralinguistics Challenge: COVID-19 Cough, COVID-19 Speech, Escalation & Primates

no code implementations24 Feb 2021 Björn W. Schuller, Anton Batliner, Christian Bergler, Cecilia Mascolo, Jing Han, Iulia Lefter, Heysem Kaya, Shahin Amiriparian, Alice Baird, Lukas Stappen, Sandra Ottl, Maurice Gerczuk, Panagiotis Tzirakis, Chloë Brown, Jagmohan Chauhan, Andreas Grammenos, Apinan Hasthanasombat, Dimitris Spathis, Tong Xia, Pietro Cicuta, Leon J. M. Rothkrantz, Joeri Zwerts, Jelle Treep, Casper Kaandorp

The INTERSPEECH 2021 Computational Paralinguistics Challenge addresses four different problems for the first time in a research competition under well-defined conditions: In the COVID-19 Cough and COVID-19 Speech Sub-Challenges, a binary classification on COVID-19 infection has to be made based on coughing sounds and speech; in the Escalation SubChallenge, a three-way assessment of the level of escalation in a dialogue is featured; and in the Primates Sub-Challenge, four species vs background need to be classified.

Representation Learning

Exploring Contrastive Learning in Human Activity Recognition for Healthcare

1 code implementation23 Nov 2020 Chi Ian Tang, Ignacio Perez-Pozuelo, Dimitris Spathis, Cecilia Mascolo

Human Activity Recognition (HAR) constitutes one of the most important tasks for wearable and mobile sensing given its implications in human well-being and health monitoring.

Contrastive Learning Human Activity Recognition

Self-supervised transfer learning of physiological representations from free-living wearable data

1 code implementation18 Nov 2020 Dimitris Spathis, Ignacio Perez-Pozuelo, Soren Brage, Nicholas J. Wareham, Cecilia Mascolo

Our contributions are two-fold: i) the pre-training task creates a model that can accurately forecast HR based only on cheap activity sensors, and ii) we leverage the information captured through this task by proposing a simple method to aggregate the learnt latent representations (embeddings) from the window-level to user-level.

Human Activity Recognition Representation Learning +1

Learning Generalizable Physiological Representations from Large-scale Wearable Data

2 code implementations9 Nov 2020 Dimitris Spathis, Ignacio Perez-Pozuelo, Soren Brage, Nicholas J. Wareham, Cecilia Mascolo

To date, research on sensor-equipped mobile devices has primarily focused on the purely supervised task of human activity recognition (walking, running, etc), demonstrating limited success in inferring high-level health outcomes from low-level signals, such as acceleration.

Human Activity Recognition Representation Learning +1

Exploring Automatic Diagnosis of COVID-19 from Crowdsourced Respiratory Sound Data

4 code implementations10 Jun 2020 Chloë Brown, Jagmohan Chauhan, Andreas Grammenos, Jing Han, Apinan Hasthanasombat, Dimitris Spathis, Tong Xia, Pietro Cicuta, Cecilia Mascolo

This work opens the door to further investigation of how automatically analysed respiratory patterns could be used as pre-screening signals to aid COVID-19 diagnosis.

BIG-bench Machine Learning COVID-19 Diagnosis

Interactive dimensionality reduction using similarity projections

no code implementations13 Nov 2018 Dimitris Spathis, Nikolaos Passalis, Anastasios Tefas

In order to visualize that data in 2D or 3D, usually Dimensionality Reduction (DR) techniques are employed.

Dimensionality Reduction Domain Adaptation

Photo-Quality Evaluation based on Computational Aesthetics: Review of Feature Extraction Techniques

no code implementations19 Dec 2016 Dimitris Spathis

Researchers try to model the aesthetic quality of photographs into low and high- level features, drawing inspiration from art theory, psychology and marketing.

BIG-bench Machine Learning Marketing

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