A systematic review of trustworthy and explainable artificial intelligence in healthcare: Assessment of quality, bias risk, and data fusion

Information Fusion, Journal Year: 2023, Volume and Issue: 96, P. 156 - 191

Published: March 15, 2023

Language: Английский

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Data clustering: application and trends

Artificial Intelligence Review, Journal Year: 2022, Volume and Issue: 56(7), P. 6439 - 6475

Published: Nov. 27, 2022

Language: Английский

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A systematic review of data fusion techniques for optimized structural health monitoring

Information Fusion, Journal Year: 2023, Volume and Issue: 103, P. 102136 - 102136

Published: Nov. 10, 2023

Advancements in structural health monitoring (SHM) techniques have spiked the past few decades due to rapid evolution of novel sensing and data transfer technologies. This development has facilitated simultaneous recording a wide range data, which could contain abundant damage-related features. Concurrently, age omnipresent started with massive amounts SHM collected from large-size heterogeneous sensor networks. The abundance information diverse sources needs be aggregated enable robust decision-making strategies. Data fusion is process integrating various produce more useful, accurate, reliable about system behavior. paper reviews recent developments applied systems. theoretical concepts, applications, benefits, limitations current methods challenges are presented, future trends discussed. Furthermore, set criteria proposed evaluate contents original review papers this field, road map provided discussing possible work.

Language: Английский

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Shaping high-performance wearable robots for human motor and sensory reconstruction and enhancement

Nature Communications, Journal Year: 2024, Volume and Issue: 15(1)

Published: Feb. 26, 2024

Abstract Most wearable robots such as exoskeletons and prostheses can operate with dexterity, while wearers do not perceive them part of their bodies. In this perspective, we contend that integrating environmental, physiological, physical information through multi-modal fusion, incorporating human-in-the-loop control, utilizing neuromuscular interface, employing flexible electronics, acquiring processing human-robot biomechatronic chips, should all be leveraged towards building the next generation robots. These technologies could improve embodiment With optimizations in mechanical structure clinical training, better facilitate human motor sensory reconstruction enhancement.

Language: Английский

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Layered Double Hydroxides: Recent Progress and Promising Perspectives Toward Biomedical Applications

Advanced Science, Journal Year: 2024, Volume and Issue: 11(20)

Published: March 19, 2024

Abstract Layered double hydroxides (LDHs) have been widely studied for biomedical applications due to their excellent properties, such as good biocompatibility, degradability, interlayer ion exchangeability, high loading capacity, pH‐responsive release, and large specific surface area. Furthermore, the flexibility in structural composition ease of modification LDHs makes it possible develop specifically functionalized meet needs different applications. In this review, recent advances applications, which include LDH‐based drug delivery systems, cancer diagnosis therapy, tissue engineering, coatings, functional membranes, biosensors, are comprehensively discussed. From these various research fields, can be seen that there is great potential possibility use However, at same time, must recognized actual clinical translation still very limited. Therefore, current limitations related on discussed by combining limited examples with requirements biomaterials. Finally, an outlook future provided.

Language: Английский

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Explainable AI-driven IoMT fusion: Unravelling techniques, opportunities, and challenges with Explainable AI in healthcare

Information Fusion, Journal Year: 2024, Volume and Issue: 110, P. 102472 - 102472

Published: May 16, 2024

Language: Английский

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EEG-Based Driver Fatigue Detection Using Spatio-Temporal Fusion Network With Brain Region Partitioning Strategy

IEEE Transactions on Intelligent Transportation Systems, Journal Year: 2024, Volume and Issue: 25(8), P. 9618 - 9630

Published: July 11, 2024

Language: Английский

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A Lightweight multi-path convolutional neural network architecture using optimal features selection for multiclass classification of brain tumor using magnetic resonance images

Results in Engineering, Journal Year: 2025, Volume and Issue: unknown, P. 104327 - 104327

Published: Feb. 1, 2025

Language: Английский

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A feature level image fusion for Night-Vision context enhancement using Arithmetic optimization algorithm based image segmentation

Expert Systems with Applications, Journal Year: 2022, Volume and Issue: 209, P. 118272 - 118272

Published: July 26, 2022

Language: Английский

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A survey of identity recognition via data fusion and feature learning

Information Fusion, Journal Year: 2022, Volume and Issue: 91, P. 694 - 712

Published: Nov. 7, 2022

With the rapid development of Mobile Internet and Industrial Things, a variety applications put forward an urgent demand for user device identity recognition. Digital with hidden characteristics is essential both individual users physical devices. assistance multimodalities as well fusion strategies, recognition can be more reliable robust. In this survey, we turn to investigate concepts limitations unimodal recognition, motivation, advantages multimodal summarize technologies via feature level, match score decision rank level data strategies. Additionally, also discuss security concerns future research orientations learning-based which enables researchers achieve better understanding current status field select directions. This survey summarizes expands processing methods multi-source multimodality data, provides theoretical support their in complicated scenarios. addition, it proper • User by leveraging physiological behavioral biometrics. Device fingerprint. Multi-modality strategies combining multi-level semantic information. Security work towards

Language: Английский

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