Hyperparameter optimization of XGBoost using artificial bee colony for predicting medical complications in hemodialysis patients by Rangga Laksana Aryananda, Trimono, Wahyu Syaifullah J, Wan Suryani Wan Awang

“…Five test scenarios with different ABC parameter configurations were conducted to optimize XGBoost hyperparameters. Results indicate that balancing the dataset with SMOTE enhances model accuracy. …”
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Bio-Inspired Hyperparameter Tuning of Federated Learning for Student Activity Recognition in Online Exam Environment by Ramu Shankarappa, Nandini Prasad, Ram Mohana Reddy Guddeti, Biju R. Mohan

“…However, identifying the best hyperparameters in the local client ResNet50 model is challenging. …”
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A Hybrid Brain Stroke Prediction Framework: Integrating Feature Selection, Classification, and Hyperparameter Optimization by Mohammad Amin, Khalid M. O. Nahar, Hasan Gharaibeh, Rabia Emhamed Al Mamlook, Ahmad Nasayreh, Nesrine Atitallah, Ali Gharaibeh, Raneem Hamad, Raed Abu Zitar, Aseel Smerat, Laith Abualigah

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Median interacted pigeon optimization-based hyperparameter tuning of CNN for paddy leaf disease prediction by Jasmy Davies, S. Sivakumari

“…Furthermore, to extract relevant features from images of rice leaf diseases, Convolutional Neural Networks (CNNs) require efficient hyperparameter tuning. Thus, a novel Median Interacted Pigeon-Inspired Optimization (MIPIO) is proposed, which optimizes CNN hyperparameters to enhance the accuracy of characterizing fungal infections and enable the recognition of antagonist interactions among virus species. …”
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RETRACTED ARTICLE: Hybrid CNN-LSTM model with efficient hyperparameter tuning for prediction of Parkinson’s disease by Umesh Kumar Lilhore, Surjeet Dalal, Neetu Faujdar, Martin Margala, Prasun Chakrabarti, Tulika Chakrabarti, Sarita Simaiya, Pawan Kumar, Pugazhenthan Thangaraju, Hemasri Velmurugan

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Securing IoT devices with zero day intrusion detection system using binary snake optimization and attention based bidirectional gated recurrent classifier by Ali Saeed Almuflih, Ilyos Abdullayev, Sergey Bakhvalov, Rustem Shichiyakh, Bibhuti Bhusan Dash, K. B. V. Brahma Rao, Kritika Bansal

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SKIN RASH CLASSIFICATION SYSTEM USING MODIFIED DENSENET201 THROUGH RANDOM SEARCH FOR HYPERPARAMETER TUNING by Fayza Nayla Riyana Putri, R.Rizal Isnanto, Aris Sugiharto

“…The findings highlight the potential of Random Search for hyperparameter tuning to enhance the performance of deep convolutional neural networks in the medical image classification domain, offering a promising tool for efficient and accurate skin disease detection. …”
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Optimised hybrid deep learning classification model for kidney stone diagnosis by Y Jini Jacob, Bethanney Janney J, Hemalatha RJ, Preethi S

Subjects: “…Kidney stone detection…”
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Unmasking insider threats using a robust hybrid optimized generative pretrained neural network approach by P. Lavanya, H. Anila Glory, Manuj Aggarwal, V. S. Shankar Sriram

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Early breast cancer detection via infrared thermography using a CNN enhanced with particle swarm optimization by Riyadh M. Alzahrani, Mohamed Yacin Sikkandar, S. Sabarunisha Begum, Ahmed Farag Salem Babetat, Maryam Alhashim, Abdulrahman Alduraywish, N. B. Prakash, Eddie Y. K. Ng

“…An Enhanced Particle Swarm Optimization (EPSO) algorithm is integrated to automatically fine-tune CNN hyperparameters, thereby minimizing manual effort and enhancing computational efficiency. …”
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Enhanced spectrum sensing for 5G and LTE signals using advanced deep learning models and hyperparameter tuning by Sally Mohamed Ali Elmorsy, Samah Mohamed Osman, Samah Adel Gamel

“…The research highlights that, through rigorous hyperparameter optimization, these models achieved substantial improvements in detection accuracy, reaching 97.3% and 98.2%, respectively, compared to initial performance levels of 93.0% and 95.0%. …”
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Enhancing Liver Cirrhosis Diagnosis Using Machine Learning With Explainable AI and Cross-Validated Hyperparameter Tuning Techniques by Koteswara Rao Makkena, Karthika Natarajan

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Integrated feature selection-based stacking ensemble model using optimized hyperparameters to predict breast cancer with smart web application by Rajib Kumar Halder, Marzana Akter Lima, Mohammed Nasir Uddin, Md.Aminul Islam, Adri Saha

“…Additionally, we have developed a user-friendly web app for breast cancer detection using our predictive model.…”
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Grid Search Based Hyperparameter-Tuned Deep Learning Model for Osteoporosis Diagnosis with Bi-Cubic Interpolation of X-Ray Images by Ruhul Amin, Md.Shamim Reza, Dewan Ahmed Muhtasim, Jungpil Shin, Md. Maniruzzaman, Md.Mahfujul Hasan

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Optimised RFO tuned RF-DETR model for precision urine microscopy for renal and systemic disease diagnosis by Neeraj Dahiya, Deo Prakash, Shakti Kundu, Shanu Rakesh Kuttan, Isha Suwalka, Manel Ayadi, Mitiku Dubale, Arshad Hashmi

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Gesture recognition for hearing impaired people using an ensemble of deep learning models with improving beluga whale optimization-based hyperparameter tuning by Mohammed Assiri, Mahmoud M. Selim

“…At present, hand gesture detection plays a vital part, and it is commonly employed in numerous applications worldwide. …”
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Lightweight convolutional neural networks using nonlinear Lévy chaotic moth flame optimisation for brain tumour classification via efficient hyperparameter tuning by Amin Abdollahi Dehkordi, Mehdi Neshat, Alireza Khosravian, Menasha Thilakaratne, Ali Safaa Sadiq, Seyedali Mirjalili

“…To assess the efficiency of the proposed model, empirical analyses were performed using a dataset of 2314 brain tumour detection images (1245 images of brain tumours and 1069 normal brain images). …”
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Analisis Algoritma Klasifikasi Untuk Mengidentifikasi Potensi Risiko Kesehatan Ibu Hamil by Jajang Jaya Purnama, Nina Kurnia Hikmawati, Sri Rahayu

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A Holistic Strategy of Modified Superpixel Segmentation and Randomized Adam Hyperparameter Tuning with Deep Learning Approaches for the Classification of Breast Cancer from BreakHi... by Gowri Shankar Manivannan, Karthikeyan Shanmugam, Harikumar Rajaguru, Satish V. Talawar, Rajanna Siddaiah

“…Abstract Breast cancer is a prevalent cancer type in women worldwide, and therefore it is necessary to do early detection that is accurate for effective treatment. …”
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Patient-Specific Hyperparameter Optimization of a Deep Learning-Based Tumor Autocontouring Algorithm on 2D Liver, Prostate, and Lung Cine MR Images: A Pilot Study by Gawon Han, Keith Wachowicz, Nawaid Usmani, Don Yee, Jordan Wong, Arun Elangovan, Jihyun Yun, B. Gino Fallone

“…However, for real-time tumor detection, it is unfeasible for a human expert to manually contour (gold standard) the tumor at the fast imaging rate of a linac-MR. …”
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