Results 141 to 150 of about 118,357 (248)

Deep learning-based multimodal risk stratification for atherosclerosis management

Archives of Medical Science
Introduction Atherosclerosis is a leading cause of cardiovascular events, requiring accurate risk stratification. Traditional methods rely on subjective imaging and clinical scores, limiting precision.
Min Xu, Yaosheng Mei, Chengnan Liu, Yanxia Lv, Yifan Pan, Zhenzhong Zhu, Yunxiang Wang   +6 more
doaj   +1 more source

Bio‐to‐Robot Transfer of Fish Sensorimotor Dynamics via Interpretable Model

Advanced Intelligent Systems, EarlyView.
This study demonstrates how a biologically interpretable model trained on real‐fish muscle activity can accurately predict the motion of a robotic fish. By linking real‐fish sensorimotor dynamics with robotic fish, the work offers a transparent, data‐efficient framework for transferring biological intelligence to bioinspired robotic systems.
Waqar Hussain Afridi, Ahsan Tanveer, Rahdar Hussain Afridi, Muhammad Hamza, Mingxin Wu, Liang Li, Guangming Xie   +6 more
wiley   +1 more source

Building an Intelligent Cardiovascular System Platform: Embedding Artificial Intelligence across All Facets of Cardiovascular Medicine

Advanced Intelligent Systems, EarlyView.
This paper presents an integrated AI‐driven cardiovascular platform unifying multimodal data, predictive analytics, and real‐time monitoring. It demonstrates how artificial intelligence—from deep learning to federated learning—enables early diagnosis, precision treatment, and personalized rehabilitation across the full disease lifecycle, promoting a ...
Mowei Kong, Xingwei Zhao, Qiuting Li, Yang Yu, Chunxiang Zhang   +4 more
wiley   +1 more source

Comparison of Residual Network and Other Classical Models for Classification of Interlayer Distresses in Pavement

Applied Sciences
Many automatic classification methods published can identify the main hidden distress types of highways, but they cannot meet the precise needs of operation and maintenance.
Wenlong Cai, Mingjie Li, Guanglai Jin, Qilin Liu, Congde Lu   +4 more
doaj   +1 more source

Human‐Machine Mutual Trust Based Shared Control Framework for Intelligent Vehicles

Advanced Intelligent Systems, EarlyView.
This work introduces a bidirectional‐trust‐driven shared control framework for human‐machine co‐driving. The method models human‐to‐machine trust from intention discrepancies and Bayesian skill assessment, and machine‐to‐human trust from integrated ability evaluation.
Zhishuai Yin, Qian Li, Zhiwei Li, Xukai Zhai, Jinhui Gao   +4 more
wiley   +1 more source

GAN‐LSTM‐3D: An efficient method for lung tumour 3D reconstruction enhanced by attention‐based LSTM

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Three‐dimensional (3D) image reconstruction of tumours can visualise their structures with precision and high resolution. In this article, GAN‐LSTM‐3D method is proposed for 3D reconstruction of lung cancer tumours from 2D CT images. Our method consists of three phases: lung segmentation, tumour segmentation, and tumour 3D reconstruction. Lung
Lu Hong, Mohammad Hossein Modirrousta, Mohammad Hossein Nasirpour, Mohammadreza Mirshekari Chargari, Fardin Mohammadi, Seyed Vahid Moravvej, Leila Rezvanishad, Mohammadreza Rezvanishad, Ivan Bakhshayeshi, Roohallah Alizadehsani, Imran Razzak, Hamid Alinejad‐Rokny, Saeid Nahavandi   +12 more
wiley   +1 more source

TacEva: A Performance Evaluation Framework for Vision‐Based Tactile Sensors

Advanced Intelligent Systems, EarlyView.
This work introduces TacEva, a unified framework for evaluating vision‐based tactile sensors. It standardizes intrinsic, performance, and robustness metrics through shared experimental procedures and links them to task‐level requirements in robotic manipulation.
Qingzheng Cong, Steven Oh, Wen Fan, Shan Luo, Kaspar Althoefer, Dandan Zhang   +5 more
wiley   +1 more source

GastroNet: A robust attention‐based deep learning and cosine similarity feature selection framework for gastrointestinal disease classification from endoscopic images

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Diseases of the Gastrointestinal (GI) tract significantly affect the quality of human life and have a high fatality rate. Accurate diagnosis of GI diseases plays a pivotal role in healthcare systems. However, processing large amounts of medical image data can be challenging for radiologists and other medical professionals, increasing the risk ...
Muhammad Nouman Noor, Muhammad Nazir, Imran Ashraf, Nouf Abdullah Almujally, Muhammad Aslam, Syeda Fizzah Jilani   +5 more
wiley   +1 more source

Deep Learning Methods for Assessing Time‐Variant Nonlinear Signatures in Clutter Echoes

Advanced Intelligent Systems, EarlyView.
Motion classification from biosonar echoes in clutter presents a fundamental challenge: extracting structured information from stochastic interference. Deep learning successfully discriminates object speed and direction from bat‐inspired signals, achieving 97% accuracy with frequency‐modulated calls but only 48% with constant‐frequency tones. This work
Ibrahim Eshera, Gaurav Duggal, Rolf Müller   +2 more
wiley   +1 more source

An efficient deep learning model for brain tumour detection with privacy preservation

CAAI Transactions on Intelligence Technology, EarlyView., 2023
Abstract Internet of medical things (IoMT) is becoming more prevalent in healthcare applications as a result of current AI advancements, helping to improve our quality of life and ensure a sustainable health system. IoMT systems with cutting‐edge scientific capabilities are capable of detecting, transmitting, learning and reasoning.
Mujeeb Ur Rehman, Arslan Shafique, Imdad Ullah Khan, Yazeed Yasin Ghadi, Jawad Ahmad, Mohammed S. Alshehri, Mimonah Al Qathrady, Majed Alhaisoni, Muhammad H. Zayyan   +8 more
wiley   +1 more source