A Novel Multi-Level Perceptron for Accurate Heart Stroke Diagnosis by Muhammad Zaman, Muhammad Khubaib, Tanzila Kahkashan, Anam Zahoor, Narges Shahbaz, Shahzad Shoukat, Fahma Nisar

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Efficient diagnosis of diabetes mellitus using an improved ensemble method by Blessing Oluwatobi Olorunfemi, Adewale Opeoluwa Ogunde, Ahmad Almogren, Abidemi Emmanuel Adeniyi, Sunday Adeola Ajagbe, Salil Bharany, Ayman Altameem, Ateeq Ur Rehman, Asif Mehmood, Habib Hamam

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A novel double machine learning approach for detecting early breast cancer using advanced feature selection and dimensionality reduction techniques by Suganya Athisayamani, Tamilazhagan S, A. Robert Singh, Jae-Yong Hwang, Gyanendra Prasad Joshi

“…Abstract In this paper, three Double Machine Learning (DML) models are proposed to enhance the accuracy of breast cancer detection using machine learning techniques using breast cancer detection dataset. …”
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A comprehensive review of machine learning and deep learning techniques for intraclass variability breast cancer recognition by Kashif Khan, Suryanti Awang, Mohammed Ahmed Talab, Hasan Kahtan

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Automated classification of oral potentially malignant disorders and oral squamous cell carcinoma using a convolutional neural network framework: a cross-sectional studyResearch in... by Cristina Saldivia-Siracusa, Eduardo Santos Carlos de Souza, Arnaldo Vitor Barros da Silva, Anna Luíza Damaceno Araújo, Caíque Mariano Pedroso, Tarcília Aparecida da Silva, Maria Sissa Pereira Sant'Ana, Felipe Paiva Fonseca, Hélder Antônio Rebelo Pontes, Marcos G. Quiles, Marcio Ajudarte Lopes, Pablo Agustin Vargas, Syed Ali Khurram, Alexander T. Pearson, Mark W. Lingen, Luiz Paulo Kowalski, Keith D. Hunter, André Carlos Ponce de Leon Ferreira de Carvalho, Alan Roger Santos-Silva

“…Obtained results suggest that the adoption of DL models in healthcare could aid in diagnostic assistance and decision-making during clinical practice. …”
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Identifying where and when urban renewal occurs: a continuous change detection-based framework using two decades’ worth of Landsat data by Chong Liu, Qi Zhang, Huabing Huang, Hanzeyu Xu, Xiao Cheng

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A Hidden Surveillant Transmission Line Protection Layer for Cyber-Attack Resilience of Power Systems by Hossein Ebrahimi, Sajjad Golshannavaz, Amin Yazdaninejadi, Edris Pouresmaeil

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Prediction of Pt, Ir, Ru, and Rh complexes light absorption in the therapeutic window for phototherapy using machine learning by V. Vigna, T. F. G. G. Cova, A. A. C. C. Pais, E. Sicilia

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Explainable Supervised Learning Models for Aviation Predictions in Australia by Aziida Nanyonga, Hassan Wasswa, Keith Joiner, Ugur Turhan, Graham Wild

“…This study investigates the classification performance of multiple supervised machine learning models and employs SHapley Additive exPlanations (SHAPs) to provide global model explanations, identifying key features that influence decision boundaries. …”
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Competence region estimation for black-box surrogate models by Tapan Shah

“…Thekey contributions of the paper are •  For 3 standard machine learning models, Support Vec-tor Machines, Decision Trees and Linear (Logistic)Regression, we compare the performance loss for astandard static quantization and stochastic quantiza-tion for 55 classification and 30 regression datasetswith 1-8 bits quantization…”
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Predicting Respiratory Conditions Using Random Forest and XGBoost by Dhiyaussalam Dhiyaussalam, Ahmad Yusuf, Isna Wardiah, Nitami Lestari Putri

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EEG-Based Inverse Reinforcement Learning for Safety-Oriented Global Path Planning in Dynamic Environments by Hao Zhu, Jialin Wang, Rui Gao

“…Results highlight the synergy between neural feedback and computational models, advancing inclusive human–robot collaboration in safety-critical scenarios.…”
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Thermal stratification and mixing of dam reservoirs in Iran by Roohollah Noori, Mojtaba Noury, Maryam Khalilzadeh Poshtegal, Masoud Sadrinasab, Mehran Mahdian, Rabin Bhattarai, Mohammad Moradi, Soroush Abolfathi

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Evaluation of Weed Infestations in Row Crops Using Aerial RGB Imaging and Deep Learning by Plamena D. Nikolova, Boris I. Evstatiev, Atanas Z. Atanasov, Asparuh I. Atanasov

“…Based on an experimental study with the DeepLabV3 classification algorithm, it was found that the ResNet-34-backed model ensures the highest performance compared to different versions of ResNet, DenseNet, and VGG backbones. …”
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Land cover changes in grassland landscapes: combining enhanced Landsat data composition, LandTrendr, and machine learning classification in google earth engine with MLP-ANN scenari... by Cecilia Parracciani, Daniela Gigante, Onisimo Mutanga, Stefania Bonafoni, Marco Vizzari

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Outlier Detection of Photovoltaic Power Generation System Data Based on GMM-IF Algorithm by Xin Li, Guoxin Du, Yuman Li, Zengqiang Ma, Lihu Liu, Minglong Jiang, Feiyu Liu, Tianming Mu

“…The Gaussian Mixture Model (GMM) is widely used in anomaly detection due to its flexibility in handling complex data distributions and its soft classification mechanism. …”
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Machine learning models for enhanced stroke detection and prediction by Shilpa Bajaj, Manju Bala, Mohit Angurala

“…This research evaluates the performance of three machine learning models—OzNet-mRMR-NB, Logistics Regression, and an Ensemble CNN—using medical images for stroke prediction. …”
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Predictive Model for Incipient Faults in Oil-Filled Transformers by Michael Osajeh, Linda Usiosefe, Efosa Igodan

“…This study proposed a data-driven fault/defect diagnostic model using four ensemble models with three base classifiers respectively. …”
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An Empirical Analysis of Crash Injury Severity Among Young Drivers in England: Accounting for Data Imbalance by Amirhossein Taheri, Kevin Switala, Grigorios Fountas, Abbas Sheykhfard, Nima Dadashzadeh, Steffen Müller

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SNUH methylation classifier for CNS tumors by Kwanghoon Lee, Jaemin Jeon, Jin Woo Park, Suwan Yu, Jae-Kyung Won, Kwangsoo Kim, Chul-Kee Park, Sung-Hye Park

“…We set established ‘Decisions’ categories based on histopathology, clinical information, and next-generation sequencing to assess the classification results. …”
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