Accurate and robust prediction of Amyloid-β brain deposition from plasma biomarkers and clinical information using machine learning by Jiayuan Xu, Andrew J. Doig, Sofia Michopoulou, Sofia Michopoulou, Petroula Proitsi, Petroula Proitsi, Fumie Costen, The Alzheimer's disease neuroimaging initiative

“…This study aims to develop and validate machine learning algorithms for accurately predicting brain Aβ positivity using plasma biomarkers, genetic information, and clinical data as a cost-effective alternative to PET imaging.MethodsWe analyzed 1,043 patients from the Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset and validated our models on 127 patients from the Center for Neurodegeneration and Translational Neuroscience (CNTN) dataset. …”
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Detection of Rice Leaf Folder in Paddy Fields Based on Unmanned Aerial Vehicle-Based Hyperspectral Images by Shanshan Feng, Shun Jiang, Xuying Huang, Lei Zhang, Yangying Gan, Laigang Wang, Canfang Zhou

“…Secondly, 23 vegetation indices were calculated as candidates for identifying rice pests. Then, hyperspectral data and field investigation data from the jointing stage were used to construct a machine learning (extreme gradient boosting, XGBoost) algorithm for detecting rice pests. …”
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Artificial intelligence: clinical applications and future advancement in gastrointestinal cancers by Abolfazl Akbari, Maryam Adabi, Mohsen Masoodi, Abolfazl Namazi, Abolfazl Namazi, Fatemeh Mansouri, Seidamir Pasha Tabaeian, Seidamir Pasha Tabaeian, Zahra Shokati Eshkiki

“…Deep learning algorithms can swiftly and effectively analyze unstructured, high-dimensional data, including texts, images, and waveforms, while advanced machine learning approaches could reveal new insights into disease risk factors and phenotypes. …”
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Cloud-based optimized deep learning framework for automated glaucoma detection using stationary wavelet transform and improved grey-wolf-optimization with ELM approach by Debendra Muduli, Syed Irfan Yaqoob, Santosh Kumar Sharma, Anuradha S. Kanade, Mohammad Shameem, Harendra S. Jangwan, P.M. Ashok Kumar, Abu Taha Zamani

“…Finally, an improved gray wolf optimization algorithm integrated with an extreme learning machine (IMGWO-ELM) classifies the images as either healthy or glaucomatous. …”
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Topology Knapsack Problem for Geometry Optimization by Hsiao-Hui Li, Po-Chun Chang, Yuan-Hsun Liao

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An Intelligent LoRaWAN-Based IoT Device for Monitoring and Control Solutions in Smart Farming Through Anomaly Detection Integrated With Unsupervised Machine Learning by Maram Fahaad Almufareh, Mamoona Humayun, Zulfiqar Ahmad, Asfandyar Khan

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Memory Efficient Local Features Descriptor for Identity Document Detection on Mobile and Embedded Devices by Daniil P. Matalov, Elena E. Limonova, Natalya S. Skoryukina, Vladimir V. Arlazarov

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DVAEGMM: Dual Variational Autoencoder With Gaussian Mixture Model for Anomaly Detection on Attributed Networks by Wasim Khan, Mohammad Haroon, Ahmad Neyaz Khan, Mohammad Kamrul Hasan, Asif Khan, Umi Asma Mokhtar, Shayla Islam

“…As a result, decoders can make graphs that are more like the original graph. Each input data point is represented by a low-dimensional representation and a probability of reconstruction by the algorithm. …”
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Multi-Task Retrieval of Sea Ice Based on GNSS-R: An Integrated Framework Guided by Semi-Supervised Anomaly Detection by Dan Ma, Yuan Gao, Chunping Hou, Menglong Li, Yang Yang

“…To overcome these challenges, the Anomaly Detection Driven Semi-supervised Multi-task Retrieval Algorithm for Sea Ice based on GNSS-R is proposed in this paper. …”
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Localization of Conveyor Belt Damages Using a Deep Neural Network and a Hybrid Method for 1D Sequential Data Augmentation by Iwona Komorska, Andrzej Puchalski, Damian Bzinkowski

“…For damage diagnosis, a Long Short-Term Memory Network with an attention mechanism (LSTM-AM) was employed, enabling anomaly detection in strain gauge signals. The application of the LSTM-AM algorithm allows for real-time monitoring of conveyor operation and facilitates precise localization and estimation of damage size through data synchronization.…”
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TriageHD: A Hyper-Dimensional Learning-to-Rank Framework for Dynamic Micro-Segmentation in Zero-Trust Network Security by Ryozo Masukawa, Sanggeon Yun, Sungheon Jeong, Nathaniel D. Bastian, Mohsen Imani

“…This paper presents TriageHD, a novel framework that integrates graph-based Hyper-Dimensional Computing (HDC) with a learning-to-rank algorithm to strengthen zero-trust network security. …”
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A novel ensemble model for fall detection: leveraging CNN and BiLSTM with channel and temporal attention by Sarita Sahni, Sweta Jain, Sri Khetwat Saritha

“…Despite the proliferation of machine learning and deep learning algorithms for fall detection, their efficacy remains hampered by resilience, robustness, and adaptability challenges across varied input scenarios. …”
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Enhancing diabetic retinopathy detection through federated convolutional neural networks: Exploring different stages of progression by Saad Alanazi, Rayan Alanazi

“…This paper presents a comprehensive solution for DR identification utilizing deep learning algorithms. To reduce class imbalance and strengthen this model, we first prepare unbalanced data utilizing the Synthetic Minority Oversampling Technique (SMOTE). …”
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Power quality validation in micro off-grid daily load using modular differential, LSTM deep, and probability statistics models processing NWP-data by Ladislav Zjavka

“…The DfL models were compared with recent deep and machine learning techniques. Prediction models were formed after an initial detection of adequate daily training intervals. …”
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Novel nocturnal insect pest monitoring for sustainable crop protection using ensemble augmented deep learning classification by Hui Zhao, Bo Fu, Fernando Auat Cheein, Matthew Butler, W. Edwin Harris, Tom W. Pope, Joe M. Roberts

“…This may be addressed by developing an identification algorithm for adult weevils. Here we present results that show improved machine learning models can identify adult vine weevils under laboratory and semi-field conditions. …”
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Apple Pest and Disease Detection Network with Partial Multi-Scale Feature Extraction and Efficient Hierarchical Feature Fusion by Weihao Bao, Fuquan Zhang

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A Preliminary Study on 2D Convolutional Neural Network-Based Discontinuous Rail Position Classification for Detection on Rail Breaks Using Distributed Acoustic Sensing Data by Hye-Yeun Chun, Jungtai Kim, Dongkue Kim, Ilmu Byun, Kyeongjun Ko

“…In this research, as a preliminary study on rail break detection system, a deep learning-based discontinuous rail position classification method, which is using vibration data obtained from distributed acoustic sensing (DAS) system during train operation, is proposed. …”
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Advances in sensor technologies for breast cancer detection: a comprehensive review of imaging and non-imaging approaches by Emmy Bhatti, Prabhpreet Kaur

“…This research highlights the potential of a multi-sensor system, driven by real-time monitoring and powered by machine learning algorithms, to address the gaps in breast cancer diagnosis. …”
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The use of artificial intelligence to analyze and optimize financial flows by М. А. Miakisheva

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A hybrid CFD and machine learning study of energy performance of photovoltaic systems with a porous collector: Model development and validation by Yinling Wang, Lei Yu, Mazhar Ali, Imran Ali Khan, Tahir Maqsood, Haining Gao, Qi Wang, Xiaolei Guo

“…A systematic preprocessing pipeline was developed to enhance model performance, including outlier detection and feature normalization. Hyperparameter optimization process in this study uses the Water Cycle Algorithm (WCA), a metaheuristic method inspired by natural processes. …”
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