What question did this study set out to answer?

To develop a novel architecture that enhances the detection of amyotrophic lateral sclerosis (ALS) using machine learning and blockchain.

A Hybrid Machine Learning and Blockchain Architecture for Enhanced ALS Detection

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Integrating deep learning and blockchain improves diagnostic accuracy in ALS, suggesting better patient privacy and regulatory compliance.

To develop a novel architecture that enhances the detection of amyotrophic lateral sclerosis (ALS) using machine learning and blockchain.
Integrated deep learning with blockchain technology for ALS detection
Utilized CNN-BiLSTM architecture with attention mechanism
Analyzed acoustic characteristics from 217 participants across various datasets
Achieved 96.5% accuracy in ALS detection
Reported a sensitivity of 95.3% and specificity of 97.8%
Improved data integrity and governance through blockchain implementation

Louja et al. (2025) studied this question.

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View Full Paper

Ask AI

Bookmark

Authors

Integrating deep learning and blockchain improves diagnostic accuracy in ALS, suggesting better patient privacy and regulatory compliance.

To develop a novel architecture that enhances the detection of amyotrophic lateral sclerosis (ALS) using machine learning and blockchain.
Integrated deep learning with blockchain technology for ALS detection
Utilized CNN-BiLSTM architecture with attention mechanism
Analyzed acoustic characteristics from 217 participants across various datasets
Achieved 96.5% accuracy in ALS detection
Reported a sensitivity of 95.3% and specificity of 97.8%
Improved data integrity and governance through blockchain implementation

Louja et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark