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BabyNet＋＋: Fetal birth weight prediction using biometry multimodal data acquired less than 24 hours before delivery

computers in Biology and Medicine 2023年 167卷 107602-107602页

作者： Plotka, Szymon Grzeszczyk, Michal K. Brawura-Biskupski-Samaha, Robert Gutaj, Pawel Lipa, Michal Trzciński, Tomasz Išgum, Ivana Sánchez, Clara I. Sitek, Arkadiusz Sano Centre for Computational Medicine Cracow Poland Informatics Institute University of Amsterdam Amsterdam Netherlands Department of Biomedical Engineering and Physics Amsterdam University Medical Center Amsterdam Netherlands Second Department of Obstetrics and Gynecology The Medical Centre of Postgraduate Education Warsaw Poland Department of Reproduction Poznan University of Medical Sciences Poznan Poznan Poland First Department of Obstetrics and Gynecology Medical University of Warsaw Warsaw Poland Institute of Computer Science Warsaw University of Technology Warsaw Poland Department of Radiology and Nuclear Medicine Amsterdam University Medical Center location University of Amsterdam Amsterdam Netherlands Center for Advanced Medical Computing and Simulation Massachusetts General Hospital Harvard Medical School BostonMA United States

Accurate prediction of fetal weight at birth is essential for effective perinatal care, particularly in the context of antenatal management, which involves determining the timing and mode of delivery. The current standard of care involves performing a prenatal ultrasound 24 hours prior to delivery. However, this task presents challenges as it requires acquiring high-quality images, which becomes difficult during advanced pregnancy due to the lack of amniotic fluid. In this paper, we present a novel method that automatically predicts fetal birth weight by using fetal ultrasound video scans and clinical data. Our proposed method is based on a Transformer-based approach that combines a Residual Transformer Module with a Dynamic Affine Feature Map Transform. This method leverages tabular clinical data to evaluate 2D+t spatio-temporal features in fetal ultrasound video scans. Development and evaluation were carried out on a clinical set comprising 582 2D fetal ultrasound videos and clinical records of pregnancies from 194 patients performed less than 24 hours before delivery. Our results show that our method outperforms several state-of-the-art automatic methods and estimates fetal birth weight with an accuracy comparable to human experts. Hence, automatic measurements obtained by our method can reduce the risk of errors inherent in manual measurements. Observer studies suggest that our approach may be used as an aid for less experienced clinicians to predict fetal birth weight before delivery, optimizing perinatal care regardless of the available expertise. © 2023 The Author(s)

关键词： Forecasting

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Human Eyes Move to the Target Earlier When Performing an Aiming Task with Increasing Difficulties

SSRN

引用

SSRN 2022年

作者： Liu, Xin Zhang, Yao Jiang, Xianta Zheng, Bin School of Computer and Communication Engineering University of Science and Technology Beijing Beijing100083 China Surgical Simulation Research Laboratory Department of Surgery University of Alberta EdmontonABT6G 2E1 Canada Department of Computing Science Memorial University of Newfoundland NewfoundlandA1B 3X5 Canada Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing100083 China

We examined whether human operators move their eyes earlier to a target before hands when the level of task difficulty increases. We hypothesized that subjects would perform less proactive eye movements in the difficult task than in the easy one, as they would need to focus on their current hand movements. Sixteen university students were recruited to perform the aiming and touching task reciprocally on three paired targets (circles) differing in sizes and distances, while had their eye movements tracked. The movement time, the early eye engagement time (EEET), and the number of eye adjustments were recorded. The EEET was defined as the time that a subject’s eyes fix on a target to the moment that the tool reaches out for it. The movement time increased as the index of difficulty (ID) value increased, echoing with the Fitts’ Law prediction. When aiming to a target with higher ID, subjects’ EEET was longer comparing to when reaching for a target with lower ID. Participants reduced movement speed to give themselves a longer time in searching visually for the target information before moving their hands. Results suggested that a proportional relationship may exist between task difficulty and the early eye engagement time. Subjects also performed an increasing number of eye adjustments over the course of moving from the easy to the hard target. Future research is needed to examine eye hand coordination under the regulation of Fitts’ Law. © 2022, The Authors. All rights reserved.

关键词： Eye tracking

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Beyond Images: An Integrative Multi-modal Approach to Chest X-Ray Report Generation

arXiv

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arXiv 2023年

作者： Aksoy, Nurbanu Sharoff, Serge Baser, Selcuk Ravikumar, Nishant Frangi, Alejandro F. CISTIB Centre for Computational Imaging and Simulation Technologies in Biomedicine United Kingdom School of Computing University of Leeds Leeds United Kingdom School of Languages Cultures and Societies University of Leeds Leeds United Kingdom School of Health Sciences Faculty of Biology Medicine and Health The University of Manchester United Kingdom School of Computer Science Faculty of Science and Engineering The University of Manchester United Kingdom Department of Radiology Kastamonu Training and Research Hospital Kastamonu Turkey

Image-to-text radiology report generation aims to automatically produce radiology reports that describe the findings in medical images. Most existing methods focus solely on the image data, disregarding the other patient information accessible to radiologists. In this paper, we present a novel multi-modal deep neural network framework for generating chest X-rays reports by integrating structured patient data, such as vital signs and symptoms, alongside unstructured clinical *** introduce a conditioned cross-multi-head attention module to fuse these heterogeneous data modalities, bridging the semantic gap between visual and textual data. Experiments demonstrate substantial improvements from using additional modalities compared to relying on images alone. Notably, our model achieves the highest reported performance on the ROUGE-L metric compared to relevant state-of-the-art models in the literature. Furthermore, we employed both human evaluation and clinical semantic similarity measurement (Bio-ClinicalBERT Score1) alongside word-overlap metrics to improve the depth of quantitative analysis. A human evaluation, conducted by a board-certified radiologist, confirms the model’s accuracy in identifying high-level findings, however, it also highlights that more improvement is needed to capture nuanced details and clinical context. © 2023, CC BY-NC-SA.

关键词： Deep neural networks

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Detection of False Data Injection Attacks in Smart Grid: A Secure Federated Deep Learning Approach

arXiv

引用

arXiv 2022年

作者： Li, Yang Wei, Xinhao Li, Yuanzheng Dong, Zhaoyang Shahidehpour, Mohammad The Key Laboratory of Modern Power System Simulation and Control and Renewable Energy Technology Ministry of Education Northeast Electric Power University Jilin132012 China The School of Artifcial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China The School of Electrical and Electronic Engineering Nanyang Technological University 639798 Singapore The Electrical and Computer Engineering Department Illinois Institute of Technology ChicagoIL60616 United States The ECE Department The King Abdulaziz University Saudi Arabia

As an important cyber-physical system (CPS), smart grid is highly vulnerable to cyber attacks. Amongst various types of attacks, false data injection attack (FDIA) proves to be one of the top-priority cyber-related issues and has received increasing attention in recent years. However, so far little attention has been paid to privacy preservation issues in the detection of FDIAs in smart grids. Inspired by federated learning, a FDIA detection method based on secure federated deep learning is proposed in this paper by combining Transformer, federated learning and Paillier cryptosystem. The Transformer, as a detector deployed in edge nodes, delves deep into the connection between individual electrical quantities by using its multi-head self-attention mechanism. By using federated learning framework, our approach utilizes the data from all nodes to collaboratively train a detection model while preserving data privacy by keeping the data locally during training. To improve the security of federated learning, a secure federated learning scheme is designed by combing Paillier cryptosystem with federated learning. Through extensive experiments on the IEEE 14-bus and 118-bus test systems, the effectiveness and superiority of the proposed method are verified. Copyright © 2022, The Authors. All rights reserved.

关键词： Smart power grids

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Prediction of concrete compressive strength employing machine learning techniques

引用

Materials Today: Proceedings 2023年

作者： Keshav Malhotra Dhaneshwar Mishra Charanjeet Singh Tumrate Department of Computer Science (AI and ML) Manipal University Jaipur India Department of Mechanical Engineering Manipal University Jaipur India Multiscale Simulation Research Center (MSRC) Manipal University Jaipur India Department of Civil Engineering Manipal University Jaipur India

Machine learning (ML) methods have proven to be reliable techniques in estimating, classifying, and predicting material strength based on varying material properties. It is observed that the nature of the problem and the data at hand governs the selection of an appropriate ML method. Therefore, to determine the accuracy of ML models to predict concrete compressive strength , fifteen different ML algorithms were applied to a given concrete compressive strength dataset. Among all the ML algorithms used, the prediction accuracy of the Support Vector Regressor (SVR) was the highest (88.18%) due to its effective performance when dealing with continuous target variables and nonlinear relationships among the features and the target.

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Leveraging Ligand Steric Demand to Control Ligand Exchange and Domain Composition in Stratified Metal–Organic Frameworks

引用

Angewandte Chemie 2024年第42期136卷

作者： Yiwen He Mattheus De Souza Tian-Yi Luo Siddarth K. Achar Prof. Dr. J. Karl Johnson Prof. Dr. Nathaniel L. Rosi Department of Chemistry University of Pittsburgh Pittsburgh Pennsylvania 15260 United States Computer Modeling & Simulation Program University of Pittsburgh Pittsburgh Pennsylvania 15261 United States Department of Chemical and Petroleum Engineering University of Pittsburgh Pittsburgh Pennsylvania 15261 United States

Incorporating diverse components into metal–organic frameworks (MOFs) can expand their scope of properties and applications. Stratified MOFs (sMOFs) consist of compositionally unique concentric domains (strata), offering unprecedented complexity through partitioning of structural and functional components. However, the labile nature of metal-ligand coordination handicaps achieving compositionally distinct domains due to ligand exchange reactions occurring concurrently with secondary strata growth. To achieve complex sMOF compositions, characterizing and controlling the competing processes of new strata growth and ligand exchange are vital. This work systematically examines controlling ligand exchange in UiO-67 sMOFs by tuning ligand sterics. We present quantitative methods for assessing and visualizing the outcomes of strata growth and ligand exchange that rely on high-angle annular dark-field images and elemental mapping via scanning transmission electron microscopy-energy dispersive X-ray spectroscopy. In addition, we leverage ligand sterics to create ‘blocking layers’ that minimize ligand exchange between strata which are particularly susceptible to ligand exchange and inter-strata ligand mixing. Finally, we evaluate strata compositional integrity in various solvents and find that sMOFs can maintain their compositions for >12 months in some cases. Collectively, these studies and methods enhance understanding and control over ligand placement in multi-domain MOFs, factors that underscore careful tunning of properties and function.

关键词： metal–organic frameworks porous materials core–shell materials ligand exchange

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Modeling particle transport in astrophysical outflows and simulations of associated emissions

arXiv

引用

arXiv 2021年

作者： Papadopoulos, Dimitrios A. Kosmas, O.T. Ganatsios, S. Department of Electrical and Computer Engineering University of Western Macedonia Kozani Greece Modelling and Simulation Center MACE University of Manchester Sackville Street Manchester United Kingdom Theoretical Physics Section University of Ioannina IoanninaGR-45110 Greece

In this work, after making an attempt to improve the formulation of the model on particle transport within astrophysical plasma outflows and constructing the appropriate algorithms, we test the reliability and effectiveness of our method through numerical simulations on well-studied Galactic microquasars as the SS 433 and the Cyg X-1 systems. Then, we concentrate on predictions of the associated emissions, focusing on detectable high energy neutrinos and γ-rays originated from the extra-galactic M33 X-7 system, which is a recently discovered X-ray binary located in the neighboring galaxy Messier 33 and has not yet been modeled in detail. The particle and radiation energy distributions, produced from magnetized astrophysical jets in the context of our method, are assumed to originate from decay and scattering processes taking place among the secondary particles created when hot (relativistic) protons of the jet scatter on thermal (cold) ones (p-p interaction mechanism inside the jet). These distributions are computed by solving the system of coupled integro-differential transport equations of multi-particle processes (reactions chain) following the inelastic proton-proton (p-p) collisions. For the detection of such high energy neutrinos as well as multi-wavelength (radio, X-ray and gamma-ray) emissions, extremely sensitive detection instruments are in operation or have been designed like the CTA, IceCube, ANTARES, KM3NeT, IceCube-Gen-2, and other space telescopes. © 2021, CC0.

关键词： Numerical methods

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Impact of Genetic Operators on Energy-Efficient Wireless Sensor Network 6

Impact of Genetic Operators on Energy-Efficient Wireless Sen...

引用

6th IEEE International Conference on engineering, Technologies and Applied Sciences, ICETAS 2019

作者： Chung, Vincent Tuah, Norah Lim, Kit Guan Tan, Min Keng Huang, Hui Teo, Kenneth Tze Kin Modelling Simulation Computing Laboratory Artificial Intelligence Research Unit Faculty of Engineering Universiti Malaysia Sabah Kota Kinabalu Malaysia Faculty of Computer and Mathematical Sciences Universiti Teknologi Mara Kota Kinabalu Malaysia Wuyi University Department of Intelligent Manufacturing Jiangmen China

ISBN: (纸本)9781728140827

The metaheuristic genetic algorithm is an evolutionary algorithm which means that it will always evolve to get an optimum solution. Due to this intrinsic characteristic, the conventional genetic algorithm might be trapped at local optimum when dealing with a global optimization problem that consists of several maximum points. As such, this paper aims to explore the potential of improving the genetic algorithm by manipulating its operators. With different procedures in selection and replacement operators, the genetic algorithm is be able to compute more efficiently. This mechanism is introduced to prevent the proposed algorithm to be trapped at the local optimum point with shorter computation time. The robustness of the proposed algorithm is tested in optimizing a wireless sensor network (WSN) because the WSN will exhibit multiple peaks with different network configuration. The existence of multiple peaks will lead to additional difficulties for the conventional routing protocol algorithm in tracking the global optimum network configuration or known as global optima. The simulation results show the effect of proposed genetic algorithm with different combinations of operators. © 2019 IEEE.

关键词： Wireless sensor networks

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Research on EEG signal preprocessing based on ICA fusion EMD

Research on EEG signal preprocessing based on ICA fusion EMD

引用

2020 International Conference on Virtual Reality and Intelligent Systems, ICVRIS 2020

作者： Xiaozhong, Geng Dezhi, Li Xintong, Zhang Department Jilin Province SandT Innovation Center for Physical Simulation Security of Water Resources and Electric Power Engineering Jilin Changchun130012 China Changchun Institute of Technology School of Computer Technology and Engineering Jilin Changchun130012 China Jilin University of Finance and Economics School of Accounting Jilin Changchun130117 China

ISBN: (纸本)9781728196367

The EEG signal is a random signal with a very complicated mechanism and very faint, and it is very susceptible to interference from electrooculogram artifact signals. This paper proposed an ICA-EMD EEG signal processing algorithm based on the fusion of independent component analysis (ICA) and empirical mode decomposition (EMD), which can remove noisy artifacts from EEG signals with high accuracy. This method firstly decomposes the multichannel EEG signal into statistically independent components by independent component analysis (ICA), and then using EMD filtering achieve the elimination of physiological artifacts of single-component EEG. the experiments show that the ICA-EMD algorithm can effectively retain the neural information in the artifacts and the brain electrical activity signals outside the artifact frequency band, therefore it avoids the loss of important brain electrical signals. © 2020 IEEE.

关键词： Empirical mode decomposition

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Magnetization and Spin Dynamics in Two-Dimensional Magnets

Magnetization and Spin Dynamics in Two-Dimensional Magnets

引用

2023 IEEE International Magnetic Conference - Short Papers, INTERMAG Short Papers 2023

作者： Alahmed, Laith Nepal, Bhuwan Macy, Juan Casas, Brian Sapkota, Arjun Mazza, Alessandro R. Brahlek, Matthew Wen, Jiajia Jin, Wencan Zhang, Steven S.-L. Mewes, Claudia Zhang, Li-Chuan Mokrousov, Yuriy Zhang, Wei Lee, Young S. Balicas, Luis Mewes, Tim Zhang, Xiaoqian Li, Peng Department of Electrical and Computer Engineering Auburn University AuburnAL36849 United States Department of Physics University of Alabama TuscaloosaAL35487 United States National High Magnetic Field Laboratory Florida State University TallahasseeFL32310 United States Materials Science and Technology Division Oak Ridge National Laboratory Oak RidgeTN37831 United States Department of Physics Auburn University AuburnAL36849 United States Stanford Institute for Materials and Energy Sciences Slac National Accelerator Laboratory Menlo ParkCA94025 United States Department of Physics Case Western Reserve University ClevelandOH44106 United States Peter Grünberg Institut Institute for Advanced Simulation Forschungszentrum Jülich Jara Jülich52425 Germany Department of Physics and Astronomy University of North Carolina at Chapel Hill Chapel HillNC27599 United States Shenzhen Institute for Quantum Science and Engr. Southern University of Science and Technology Shenzhen518055 China School of Microelectronics University of Science and Technology of China Hefei230026 China Institute of Physics Johannes Gutenberg University Mainz Mainz55099 Germany

ISBN: (纸本)9798350338362

The discovery of magnetism in two-dimensional (2D) van der Waals (vdW) materials has flourished a new endeavor of fundamental problems in magnetism. In this talk, we will discuss the magnetization and spin dynamics in two types of 2D magnets: a room-temperature vdW magnetic crystal Fe5GeTe2 with a Curie temperature Tc = 332 K and Cu(1,3-bdc), a quasi-2D magnet with a Kagome lattice. Ferromagnetic resonance was performed with external magnetic fields applied along the c-axis (H||c) and the ab-plane (H||ab). We have found a sizable Landé g-factor difference between the H||c and H||ab cases for both Fe5GeTe2 and Cu(1,3-bdc). The FMR measurements have also revealed that Fe5GeTe2 has a damping constant comparable to Permalloy. Our experiments highlight key information regarding the magnetic state and spin scattering processes in 2D magnets, which can lead to implementations of 2D magnets based spintronic devices. © 2023 IEEE.

关键词： Nickel alloys

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