AFN-Net: Adaptive Fusion Nucleus Segmentation Network Based on Multi-Level U-Net by Ming Zhao, Yimin Yang, Bingxue Zhou, Quan Wang, Fu Li

“…The task of nucleus segmentation plays an important role in medical image analysis. However, due to the challenge of detecting small targets and complex boundaries in datasets, traditional methods often fail to achieve satisfactory results. …”
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Deep convolutional fuzzy neural networks with stork optimization on chronic cardiovascular disease monitoring for pervasive healthcare services by Nuzaiha Mohamed, Reem Lafi Almutairi, Sayda Abdelrahim, Randa Alharbi, Fahad M. Alhomayani, Amer Alsulami, Salem Alkhalaf

“…Employing newly established data analysis techniques and inspecting a patient’s health record might help recognize CVD promptly. …”
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Artificial Intelligence in Action (2019-2024): A Review on Parkinson’s Disease Detection Using Non-Invasive Procedures by Peetabas Patro, Tapan Kumar Das

“…Our study covers various feature extraction techniques, methods for reducing dimensionality, feature selection approaches, and classification strategies related to PD. …”
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Wavelet-Analysis of Cardiosignals Using Matlab by B. F. Badalyan, H. A. Gomtsyan, S. G. Gomtsyan

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Anomaly Detection and Remaining Useful Life Prediction for Turbofan Engines with a Key Point-Based Approach to Secure Health Management by Yuntao Duan, Tao Zhang, Dunhuang Shi

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Detecting severe coronary artery stenosis in T2DM patients with NAFLD using cardiac fat radiomics-based machine learning by Mengjie Liang, Liting Fang, Xie Chen, Wendi Huang

“…SHAP analysis revealed the importance of radiomics features from EAT and PAT, as well as clinical factors such as diabetes duration, global longitudinal strain (GLS), and low-density lipoprotein cholesterol (LDL-C), in detecting severe coronary artery stenosis. …”
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The value of MRI-based radiomics and clinicoradiological data for the detection of forkhead box protein A1 gene mutated prostate cancer by Lin Deng, Ruchuan Chen, Bingni Zhou, Guoqing Hu, Hualei Gan, Ling Zhang, Liangping Zhou, Kefu Liu, Xiaohang Liu

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Recent innovations in machine learning for skin cancer lesion analysis and classification: A comprehensive analysis of computer‐aided diagnosis by Syeda Shamaila Zareen, Md Shamim Hossain, Junsong Wang, Yan Kang

“…This paper carefully reviews the whole diagnostic process: data preparation, lesion segmentation, feature extraction, feature selection, and final classification. …”
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Clouds Detection in Polar Icy Terrains: A Deformable Attention-Based Deep Neural Network for Multispectral Polar Scene Parsing by Shaojin Dong, Cailan Gong, Yong Hu, Long Cheng, Yang Wang, Fuqiang Zheng

“…Cloud detection is crucial for remote sensing image analysis. …”
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Multi-Feature Fusion-Based Speech Disorder Classification Using MobileNetV3-EfficientNetB7, Linformer-Performer, and SHAP-Aware XGBoost by Abdul Rahaman Wahab Sait, Suresh Sankaranarayanan, P. Gouthaman

“…Traditional speech disorders (SD) detection relies on subjective analysis, resulting in inconsistent outcome. …”
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Detecting network intrusions in cyber-physical systems using deep autoencoder-based dimensionality reduction approach anddeep neural networks by A. E. Ibor, D. O. Egete, A. O. Otiko, D. U. Ashishie

“…Comparative analysis with state-of-the-art techniques further confirms the superior performance and generalisability of the presented solution, highlighting its applicability to real-time CPS threat detection systems. …”
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A Real-Time Green and Lightweight Model for Detection of Liquefied Petroleum Gas Cylinder Surface Defects Based on YOLOv5 by Burhan Duman

“…Industry requires defect detection to ensure the quality and safety of products. …”
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FREQUENCY OF DETECTION AND SPECIFIC MORPHOLOGY OF NON-TUBERCULOUS MYCOBACTERIOSIS IN THOSE AT THE ADVANCED STAGE OF HIV (AS PER DATA FROM ORENBURG REGION) by A. M. Mikhailovskiy, S. A. Churkin, N. A. Pashkova, L. N. Lepekha

“…Non-tuberculous mycobacteriosis possesses a specific diagnostic feature i.e. detection of non-caseous granulomas, consisting of histiocytes and "foamy" macrophages, containing large number of acid-fast mycobacteria in cytoplasm. …”
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RNA-BioLens: A Novel Raspberry Pi-Based Digital Microscope With Image Processing for Acute Lymphoblastic Leukemia Detection by Angeline Dwi Sanjaya, Rachmad Setiawan, Nada Fitrieyatul Hikmah

“…To address these challenges, this study presents a simplified digital microscope system integrated with the YOLOv4 (You Only Look Once) algorithm combined with additional segmentation and feature extraction methods designed explicitly for ALL cell detection. …”
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SubsurfaceBreaks v. 1.0: a supervised detection of fault-related structures on triangulated models of subsurface homoclinal interfaces by M. P. Michalak, C. Gerhards, P. Menzel

“…<p>The study presents a novel approach for fault detection on subsurface geological homoclinal interfaces (slopes) using a supervised learning algorithm and careful input variable (feature) selection. …”
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Hybrid Model for Novel Attack Detection Using a Cluster-Based Machine Learning Classification Approach for the Internet of Things (IoT) by Naveed Ahmed, Md Asri Ngadi, Abdulaleem Ali Almazroi, Nouf Atiahallah Alghanmi

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Clinical and biological features of acute myeloid leukemia with MLL gene rearrangements in children and results of therapy according to protocols AML-MM-2000/2006 in the Republic o... by Yu. A. Barovskaya, M. V. Stegantseva, O. V. Aleinikova

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A Hybrid Machine Learning-Based Framework for Data Injection Attack Detection in Smart Grids Using PCA and Stacked Autoencoders by Shahid Tufail, Hasan Iqbal, Mohd Tariq, Arif I. Sarwat

“…This analysis will strengthen cybersecurity in smart grids and focusing on the critical need for careful feature selection and tuning, particularly for models sensitive to dimensionality reduction.…”
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Hate Speech Detection and Online Public Opinion Regulation Using Support Vector Machine Algorithm: Application and Impact on Social Media by Siyuan Li, Zhi Li

“…Word embeddings are generated using Word2Vec’s Skip-gram model, combined with TF-IDF (Term Frequency–Inverse Document Frequency) weighting to capture contextual semantics. A multi-level feature extraction framework integrates sentiment analysis via lexicon-based methods and BERT for advanced sentiment recognition. …”
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MS-trust: a transformer model with causal-global dual attention for enhanced MRI-based multiple sclerosis and myelitis detection by Salha M. Alzahrani

“…Comparative analysis for Myelitis detection shows that MS-Trust achieves an approximated accuracy of 88–90% using both modalities while the benchmarking models do not exceed 79%. …”
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