Optimizing the light gradient-boosting machine algorithm for an efficient early detection of coronary heart disease by Temidayo Oluwatosin Omotehinwa, David Opeoluwa Oyewola, Ervin Gubin Moung

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Classification of Flying Drones Using Millimeter-Wave Radar: Comparative Analysis of Algorithms Under Noisy Conditions by Mauro Larrat, Claudomiro Sales

“…This study evaluates different machine learning algorithms in detecting and identifying drones using radar data from a 60 GHz millimeter-wave sensor. …”
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Phishing detection algorithm based on attention and feature fusion by ZHANG Sirui, YAN Zhiwei, DONG Kejun, YUCHI Xuebiao

“…The effectiveness of the algorithm was ultimately verified. This hierarchical detection method effectively avoids the extraction of image data from a large number of domain names to be detected, significantly improving detection efficiency while ensuring the accuracy of detection.…”
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Malware Classification Using Few-Shot Learning Approach by Khalid Alfarsi, Saim Rasheed, Iftikhar Ahmad

“…Hardware Performance Counter data are used by machine learning algorithms in security mechanisms, such as hardware-based malware detection, to categorize and detect malware. …”
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Enhanced IoT-Based Face Mask Detection Framework Using Optimized Deep Learning Models: A Hybrid Approach With Adaptive Algorithms by Parul Dubey, Pushkar Dubey, Celestine Iwendi, Cresantus N. Biamba, Deepak Dasaratha Rao

“…The HFSO algorithm optimizes crucial parameters such as detection thresholds and learning rates. …”
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Comparison of a machine learning model with a conventional rule-based selective dry cow therapy algorithm for detection of intramammary infections by S.M. Rowe, E. Zhang, S.M. Godden, A.K. Vasquez, D.V. Nydam

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Artificial-Intelligence Bio-Inspired Peptide for Salivary Detection of SARS-CoV-2 in Electrochemical Biosensor Integrated with Machine Learning Algorithms by Marcelo Augusto Garcia-Junior, Bruno Silva Andrade, Ana Paula Lima, Iara Pereira Soares, Ana Flávia Oliveira Notário, Sttephany Silva Bernardino, Marco Fidel Guevara-Vega, Ghabriel Honório-Silva, Rodrigo Alejandro Abarza Munoz, Ana Carolina Gomes Jardim, Mário Machado Martins, Luiz Ricardo Goulart, Thulio Marquez Cunha, Murillo Guimarães Carneiro, Robinson Sabino-Silva

“…Developing affordable, rapid, and accurate biosensors is essential for SARS-CoV-2 surveillance and early detection. We created a bio-inspired peptide, using the SAGAPEP AI platform, for COVID-19 salivary diagnostics via a portable electrochemical device coupled to Machine Learning algorithms. …”
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Design of an Efficient Deep Learning-Based Diagnostic Model for Wind Turbine Gearboxes Using SCADA Data by Xuan-Kien Mai, Jun-Yeop Lee, Jae-In Lee, Byeong-Soo Go, Seok-Ju Lee, Minh-Chau Dinh

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Optimizing anomaly detection models for edge IIoT with an enhanced firefly algorithm-based hyperparameter tuning strategy by Mohemmed Yousuf Rahamathulla, Mangayarkarasi Ramaiah

“…By means of adaptive attack detection models, machine learning (ML) presents a potential solution. …”
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Leveraging retinanet based object detection model for assisting visually impaired individuals with metaheuristic optimization algorithm by Alaa O. Khadidos, Ayman Yafoz

“…This paper proposes a novel Object Detection Model for Visually Impaired Individuals with a Metaheuristic Optimization Algorithm (ODMVII-MOA) technique. …”
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Identifying candidate biomarkers for detecting bronchogenic carcinoma stages using metaheuristic algorithms based on information fusion theory by Bagher Khalvati, Kaveh Kavousi, Amir Hosein Keyhanipour, Masoud Arabfard

“…This study aims to identify non-invasive biomarkers for detecting bronchogenic carcinoma and its various stages by analyzing gene expression data using bioinformatics and machine learning techniques. …”
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Detection of Sleep Posture via Humidity Fluctuation Analysis in a Sensor-Embedded Pillow by Won-Ho Jun, Youn-Sik Hong

“…Furthermore, the PELT algorithm was utilized for precise change-point detection. …”
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Comparative study on Functional Machine learning and Statistical Methods in Disease detection and Weed Removal for Enhanced Agricultural Yield by Sudha D., Menaga D.

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Prediction of Hypertension Patients with Machine Learning Algorithm by Eko Priyono

“…These algorithms can predict hypertension risk based on clinical data, such as age, medical history, and lifestyle. …”
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Ensemble Techniques for Robust Fake News Detection: Integrating Transformers, Natural Language Processing, and Machine Learning by Mohammed Al-alshaqi, Danda B. Rawat, Chunmei Liu

“…The proliferation of fake news across multiple modalities has emerged as a critical challenge in the modern information landscape, necessitating advanced detection methods. This study proposes a comprehensive framework for fake news detection integrating text, images, and videos using machine learning and deep learning techniques. …”
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Trade-Space Exploration With Data Preprocessing and Machine Learning for Satellite Anomalies Reliability Classification by Abdul Mutholib, Nadirah Abdul Rahim, Teddy Surya Gunawan, Mira Kartiwi

“…Leveraging a Seradata dataset spanning 66 years and 4,455 satellite records, the framework systematically evaluates four data cleaning methods, four data transformation techniques, five normalization strategies, and seven machine learning algorithms across 480 configurations. …”
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Alzheimer’s Disease Detection Using Deep Learning and Federated Learning by Taha Bin Niaz, Usman Amjad, Humera

“…The goal of this paper is to defend sensitive patient data by proposing a deep learning algorithm that utilizes Federated learning techniques in an IoT-based edge computing framework. …”
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Applications of machine learning algorithms in lithological mapping of Saint Katherine Neoproterozoic rocks in the South Sinai of Egypt using hyperspectral PRISMA data by Mohamed W. Ali-Bik, Tehseen Zafar, Safaa M. Hassan, Mohamed F. Sadek, Saif M. Abo Khashaba

“…Automatic lithological mapping has been carried out using Support Vector Machine (SVM), and Random Forest (RF) machine learning algorithms applied to hyperspectral PRISMA data with an overall accuracy (OA) of up to 91.41% and 86.64%, respectively. …”
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Integration of epigenomic and genomic data to predict residual feed intake and the feed conversion ratio in dairy sheep via machine learning algorithms by Pablo Augusto de Souza Fonseca, Aroa Suarez-Vega, Cristina Esteban-Blanco, Héctor Marina, Rocío Pelayo, Beatriz Gutiérrez-Gil, Juan-José Arranz

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Secure healthcare data sharing and attack detection framework using radial basis neural network by Abhishek Kumar, Priya Batta, Pramod Singh Rathore, Sachin Ahuja

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