Automatic Prediction of Amyotrophic Lateral Sclerosis Progression using Longitudinal Speech Transformer

Liming Wang, Yuan Gong, Nauman Dawalatabad, Marco Vilela, Katerina Placek +5 more
6/26/2024
cs.SDcs.AIeess.AS

No official code found. Best implementation: cactuswiththoughts/ALST (3 stars, last commit 2024-11-30).

Abstract

Automatic prediction of amyotrophic lateral sclerosis (ALS) disease progression provides a more efficient and objective alternative than manual approaches. We propose ALS longitudinal speech transformer (ALST), a neural network-based automatic predictor of ALS disease progression from longitudinal speech recordings of ALS patients. By taking advantage of high-quality pretrained speech features and longitudinal information in the recordings, our best model achieves 91.0\% AUC, improving upon the previous best model by 5.6\% relative on the ALS TDI dataset. Careful analysis reveals that ALST is capable of fine-grained and interpretable predictions of ALS progression, especially for distinguishing between rarer and more severe cases. Code is publicly available.

View on arXivView PDF

Code Implementations(1)

cactuswiththoughts/ALSTCommunity100%
31Shell, PythonNov 26, 20231 years ago

Similar Papers

Alzheimer's Disease Prediction Using EffNetViTLoRA and BiLSTM with Multimodal Longitudinal MRI Data

85% match2025

Detecting Speech Abnormalities with a Perceiver-based Sequence Classifier that Leverages a Universal Speech Model

83% match2023

Transformer Model for Alzheimer's Disease Progression Prediction Using Longitudinal Visit Sequences

82% match2025

Dynamic Survival Prediction using Longitudinal Images based on Transformer

82% match2025

A Temporal Machine Learning-Based Time-to-Event Model for Predicting ALS Progression and Healthcare Utilization

82% match2026

Deformation-aware Temporal Generation for Early Prediction of Alzheimers Disease

81% match2025

Cite this paper

@article{wang2024automatic,
  title  = {Automatic Prediction of Amyotrophic Lateral Sclerosis Progression using Longitudinal Speech Transformer},
  author = {Liming Wang and Yuan Gong and Nauman Dawalatabad and Marco Vilela and Katerina Placek and Brian Tracey and Yishu Gong and Alan Premasiri and Fernando Vieira and James Glass},
  year   = {2024},
  eprint = {2406.18625},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2406.18625v1}
}

Add a badge to your README

Shows whether official code is linked for this paper.

Code of Paper badge
[![Code of Paper](https://codeofpaper.com/badge/2406.18625.svg)](https://codeofpaper.com/paper/2406.18625)

Discussion