Explainable and secure framework for autism prediction using multimodal eye tracking and kinematic data

Complex & Intelligent Systems, Journal Year: 2025, Volume and Issue: 11(3)

Published: Feb. 19, 2025

Language: Английский

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Intelligent analysis system based on MWS-RF-SDAE:A novel analysis method in forensic science for body fluids and interferents identification by Raman spectra

Microchemical Journal, Journal Year: 2025, Volume and Issue: unknown, P. 113905 - 113905

Published: May 1, 2025

Language: Английский

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Explainable Federated Learning for Enhanced Privacy in Autism Prediction Using Deep Learning

Deleted Journal, Journal Year: 2024, Volume and Issue: 3(7)

Published: Jan. 1, 2024

This research introduces a novel approach, termed “explainable federated learning,” designed for privacy-preserving autism prediction in toddlers using deep learning (DL) techniques. The primary objective is to contribute the development of efficient screening methods spectrum disorder (ASD) while safeguarding individual privacy. methodology encompasses multiple stages, starting with exploratory data analysis and progressing through machine (ML) algorithms, (FL), model explainability local interpretable model-agnostic explanations (LIME). Leveraging non-linear predictive models such as autoencoders, k-nearest neighbors, multi-layer perceptron, this approach ensures accurate ASD predictions. FL paradigm facilitates collaboration among clients without centralizing raw data, addressing privacy concerns medical sharing. Privacy-preserving strategies, including differential privacy, are integrated enhance security. Furthermore, achieved LIME, providing insights into process. experimental results demonstrate significant improvements accuracy interpretability compared traditional ML approaches. Specifically, our an average increase 8% across all classifiers tested, demonstrating superior performance both metrics over methods. findings highlight efficacy proposed advancing methodologies era DL applications.

Language: Английский

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Improving Machine Learning based ASD Diagnosis with Effective Feature Selection

Published: Feb. 21, 2024

Language: Английский

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