DeepAI AI Chat
Log In Sign Up

Multi-task Learning via Adaptation to Similar Tasks for Mortality Prediction of Diverse Rare Diseases

by   Luchen Liu, et al.

Mortality prediction of diverse rare diseases using electronic health record (EHR) data is a crucial task for intelligent healthcare. However, data insufficiency and the clinical diversity of rare diseases make it hard for directly training deep learning models on individual disease data or all the data from different diseases. Mortality prediction for these patients with different diseases can be viewed as a multi-task learning problem with insufficient data and large task number. But the tasks with little training data also make it hard to train task-specific modules in multi-task learning models. To address the challenges of data insufficiency and task diversity, we propose an initialization-sharing multi-task learning method (Ada-Sit) which learns the parameter initialization for fast adaptation to dynamically measured similar tasks. We use Ada-Sit to train long short-term memory networks (LSTM) based prediction models on longitudinal EHR data. And experimental results demonstrate that the proposed model is effective for mortality prediction of diverse rare diseases.


page 1

page 2

page 3

page 4


Clinical Risk Prediction with Temporal Probabilistic Asymmetric Multi-Task Learning

Although recent multi-task learning methods have shown to be effective i...

Subspace Network: Deep Multi-Task Censored Regression for Modeling Neurodegenerative Diseases

Over the past decade a wide spectrum of machine learning models have bee...

Multi-Task Learning for Mental Health using Social Media Text

We introduce initial groundwork for estimating suicide risk and mental h...

Multi-Task Learning for Budbreak Prediction

Grapevine budbreak is a key phenological stage of seasonal development, ...

Modular Universal Reparameterization: Deep Multi-task Learning Across Diverse Domains

As deep learning applications continue to become more diverse, an intere...

Grape Cold Hardiness Prediction via Multi-Task Learning

Cold temperatures during fall and spring have the potential to cause fro...

MultiCheXNet: A Multi-Task Learning Deep Network For Pneumonia-like Diseases Diagnosis From X-ray Scans

We present MultiCheXNet, an end-to-end Multi-task learning model, that i...