medical-8

Disease Trajectory Forecasting

3260 papers • 126 benchmarks • 313 datasets

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Most implemented papers

CLIMAT: Clinically-Inspired Multi-Agent Transformers for Knee Osteoarthritis Trajectory Forecasting

Matthew B. Blaschko, Huy Hoang Nguyen, S. Saarakkala, A. Tiulpin•Wed Apr 07 2021

Inspired by a clinical decision-making process with two agents – a radiologist and a general practitioner, this work model a prognosis prediction problem with two transformer-based components that share information between each other and shows the effectiveness of the method in predicting the development of structural knee osteoarthritis changes over time.

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RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism

Jimeng Sun, E. Choi, M. T. Bahadori, Joshua A. Kulas, A. Schuetz, W. Stewart•Thu Aug 18 2016

The REverse Time AttentIoN model (RETAIN) is developed for application to Electronic Health Records (EHR) data and achieves high accuracy while remaining clinically interpretable and is based on a two-level neural attention model that detects influential past visits and significant clinical variables within those visits.

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Learning Dynamic and Personalized Comorbidity Networks from Event Data using Deep Diffusion Processes

A. Alaa, M. Schaar, Zhaozhi Qian, A. Bellot, J. Rashbass•Tue Jan 07 2020

Deep diffusion processes are developed to model "dynamic comorbidity networks", i.e., the temporal relationships betweenComorbid disease onsets expressed through a dynamic graph, serving the dual purpose of accurate risk prediction and intelligible representation of disease pathology.

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Clinically-Inspired Multi-Agent Transformers for Disease Trajectory Forecasting From Multimodal Data

Matthew B. Blaschko, Huy Hoang Nguyen, S. Saarakkala, A. Tiulpin•Mon Oct 24 2022

Inspired by a clinical decision-making process with two agents–a radiologist and a general practitioner – this work predicts prognosis with two transformer-based components that share information with each other, and outperforms multiple state-of-the-art baselines with respect to performance and calibration, both of which are needed for real-world applications.

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