Search Results for author: Rita Kuznetsova

Found 10 papers, 4 papers with code

Multi-Modal Contrastive Learning for Online Clinical Time-Series Applications

no code implementations27 Mar 2024 Fabian Baldenweg, Manuel Burger, Gunnar Rätsch, Rita Kuznetsova

Electronic Health Record (EHR) datasets from Intensive Care Units (ICU) contain a diverse set of data modalities.

Contrastive Learning Time Series

On the Importance of Step-wise Embeddings for Heterogeneous Clinical Time-Series

no code implementations15 Nov 2023 Rita Kuznetsova, Alizée Pace, Manuel Burger, Hugo Yèche, Gunnar Rätsch

Recent findings in deep learning for tabular data are now surpassing these classical methods by better handling the severe heterogeneity of data input features.

Time Series

Knowledge Graph Representations to enhance Intensive Care Time-Series Predictions

no code implementations13 Nov 2023 Samyak Jain, Manuel Burger, Gunnar Rätsch, Rita Kuznetsova

Intensive Care Units (ICU) require comprehensive patient data integration for enhanced clinical outcome predictions, crucial for assessing patient conditions.

Data Integration Knowledge Graphs +1

Multi-modal Graph Learning over UMLS Knowledge Graphs

1 code implementation10 Jul 2023 Manuel Burger, Gunnar Rätsch, Rita Kuznetsova

The results demonstrate the significance of multi-modal medical concept representations based on prior medical knowledge.

Graph Learning Knowledge Graphs +1

On the Importance of Clinical Notes in Multi-modal Learning for EHR Data

no code implementations6 Dec 2022 Severin Husmann, Hugo Yèche, Gunnar Rätsch, Rita Kuznetsova

Understanding deep learning model behavior is critical to accepting machine learning-based decision support systems in the medical community.


Temporal Label Smoothing for Early Event Prediction

1 code implementation29 Aug 2022 Hugo Yèche, Alizée Pace, Gunnar Rätsch, Rita Kuznetsova

TLS reduces the number of missed events by up to a factor of two over previously used approaches in early event prediction.

Binary Classification Circulatory Failure +3

HiRID-ICU-Benchmark -- A Comprehensive Machine Learning Benchmark on High-resolution ICU Data

1 code implementation NeurIPS Datasets and Benchmarks 2021 Hugo Yèche, Rita Kuznetsova, Marc Zimmermann, Matthias Hüser, Xinrui Lyu, Martin Faltys, Gunnar Rätsch

The recent success of machine learning methods applied to time series collected from Intensive Care Units (ICU) exposes the lack of standardized machine learning benchmarks for developing and comparing such methods.

BIG-bench Machine Learning Circulatory Failure +7

Variational learning across domains with triplet information

no code implementations22 Jun 2018 Rita Kuznetsova, Oleg Bakhteev, Alexandr Ogaltsov

The work investigates deep generative models, which allow us to use training data from one domain to build a model for another domain.

Cross-Lingual Document Classification Document Classification +4

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