Construction of an oligometastatic prediction model for nasopharyngeal carcinoma patients based on pathomics features and dynamic multi-swarm particle swarm optimization support ve... by Yunfei Li, Dongni Zhang, Yiren Wang, Yiren Wang, Yiheng Hu, Zhongjian Wen, Zhongjian Wen, Cheng Yang, Ping Zhou, Wen-Hui Cheng

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Machine Learning Framework for Early Detection of Chronic Kidney Disease Stages Using Optimized Estimated Glomerular Filtration Rate by Samit Kumar Ghosh, Namareq Widatalla, Ahsan H. Khandoker

“…Shapley Additive Explanations (SHAP) provide global and local feature importance insights, enhancing clinical decision-making and model transparency. Future research will validate the model using more extensive and more diverse datasets. …”
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GPT for RCTs? Using AI to determine adherence to clinical trial reporting guidelines by Karim M Khan, Clare L Ardern, David Moher, Paul Blazey, James G Wrightson

“…The dataset was randomly split (80/20) into a TRAIN and TEST dataset. Hyperparameter and fine-tuning were performed using the TRAIN dataset. …”
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Genetic programming-based algorithms application in modeling the compressive strength of steel fiber-reinforced concrete exposed to elevated temperatures by Mohsin Ali, Li Chen, Qadir Bux Alias Imran Latif Qureshi, Deema Mohammed Alsekait, Adil Khan, Kiran Arif, Muhammad Luqman, Diaa Salama Abd Elminaam, Amir Hamza, Majid Khan

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Design of Block-Scrambling-Based privacy protection mechanism in healthcare using fusion of transfer learning models with Hippopotamus optimization algorithm by Ghada Moh. Samir Elhessewi, Mohammed Yahya Alzahrani, Mohammad Alamgeer, Abdulbasit A. Darem, Da’ad Albalawneh, Mohammed Alqahtani, Mutasim Al Sadig, Sultan Alanazi

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Among Artificial Intelligence/Machine Learning Methods, Automated Gradient-Boosting Models Accurately Score Intraoral Plaque in Non-Standardized Images by Eric Coy, William Santo, Bonnie Jue, Helen Betts, Francisco Ramos-Gomez, Stuart A. Gansky

“…Models were tuned with 80:20 train:test split, stratified 5-fold cross-validation (5-CV) (unstratified in regression models), and hyperparameter optimization. Area-under-the-curve receiver operating characteristic (AUC-ROC) curve and R2 determined the best classification and regression models, respectively, compared to calibrated dentist researcher ratings. …”
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An enhanced fusion of transfer learning models with optimization based clinical diagnosis of lung and colon cancer using biomedical imaging by N. A. S. Vinoth, J. Kalaivani, R. Madonna Arieth, S. Sivasakthiselvan, Gi-Cheon Park, Gyanendra Prasad Joshi, Woong Cho

“…Finally, the beluga whale optimization (BWO) technique alters the hyperparameter range of the TPA‐BiGRU model optimally and results in greater classification performance. …”
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Feature-Driven Density Prediction of Maraging Steel Additively Manufactured Samples Using Pyrometer Sensor and Supervised Machine Learning by Rajesh Kumar Balaraman, Shaista Hussain, John Kgee Ong, Qing Yang Tan, Nagarajan Raghavan

“…The performance of these models was enhanced through three hyperparameter optimization (HPO) techniques: Random Search (RS), Grid Search (GS), and Bayes Search (BS), alongside a feature selection (FS) method to refine the input feature dimensions. …”
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The problematic case of data leakage: A case for leave-profile-out cross-validation in 3-dimensional digital soil mapping by Kingsley John, Daniel D. Saurette, Brandon Heung

“…Data leakage occurs when there is an overlap between the data used for model fitting and hyperparameter tuning, and those used for testing. This overlap biases the model performance, making it uninformative regarding the model’s ability to generalize. …”
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Harmonizing remote sensing and ground data for forest aboveground biomass estimation by Ying Su, Zhifeng Wu, Xiaoman Zheng, Yue Qiu, Zhuo Ma, Yin Ren, Yanfeng Bai

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Smart wearable sensor-based model for monitoring medication adherence using sheep flock optimization algorithm-attention-based bidirectional long short-term memory (SFOA-Bi-LSTM) by Yasser Alatawi, Palanisamy Amirthalingam, Narmatha Chellamani, Manimurugan Shanmuganathan, Mostafa A. Sayed Ali, Saleh Fahad Alqifari, Vasudevan Mani, Muralikrishnan Dhanasekaran, Abdulelah Saeed Alqahtani, Ahmed Aljabri

“…The SFOA method was utilized to optimize the hyperparameters of the attention-based Bi-LSTM model. …”
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Construction and validation of HBV-ACLF bacterial infection diagnosis model based on machine learning by Neng Wang, Shuai Tao, Liang Chen

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Improved chaotic fruit fly optimization with elman neural network based data-driven approach on product reviews classification by Mohammed Alghamdi, Najla I. Al-shathry, Yahia Said, Hasan Beyari, Shaymaa Sorour, Khalid Nazim Abdul Sattar, Fouad Shoie Alallah, Abdulrhman Alshareef

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Enhancing pediatric distal radius fracture detection: optimizing YOLOv8 with advanced AI and machine learning techniques by Farid Amirouche, Aashik Mathew Prosper, Majd Mzeihem

“…We optimized the model through hyperparameter tuning, implementing data cleaning, augmentation, and normalization techniques using the GRAZPEDWRI-DX dataset. …”
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A Combined PSO-LSTM Prediction Model for Dam Deformation by HAO Ze-jia, SHI Yu-qun, CHENG Bo-chao, HE Jin-ping

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Estimating Soil Cd Contamination in Wheat Farmland Using Hyperspectral Data and Interpretable Stacking Ensemble Learning by Liang Zhong, Meng Ding, Shengjie Yang, Xindan Xu, Jianlong Li, Zhengguo Sun

“…Then, we constructed and compared the estimation accuracy of multiple machine learning models and a Stacking ensemble learning method and utilized the Optuna method for hyperparameter optimization. Ultimately, the SHAP method was used to shed light on the model’s decision-making process. …”
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Supervised learning and resampling techniques on DISC personality classification using Twitter information in Bahasa Indonesia by Ema Utami, Irwan Oyong, Suwanto Raharjo, Anggit Dwi Hartanto, Sumarni Adi

“…Purpose – Gathering knowledge regarding personality traits has long been the interest of academics and researchers in the fields of psychology and in computer science. …”
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Early prediction of CKD from time series data using adaptive PSO optimized echo state networks by Thangadurai Anbazhagan, Balamurugan Rangaswamy

“…This problem motivates researchers to work on a predictive model that successfully detects disease symptoms in the early stages. …”
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An open dataset and machine learning algorithms for Niacin Skin-Flushing Response based screening of psychiatric disorders by Xuening Lyu, Rimsa Goperma, Dandan Wang, Chunling Wan, Liang Zhao

“…Comparative results demonstrate that the ML-based diagnostic approach achieves a sensitivity ranging from 60.0 to 65.0% and a specificity from 75.0 to 88.3% across various types of illnesses, further underscoring its broad applicability and device independence. Conclusions This research conclusively demonstrates the significant potential of advanced AI tools in achieving precise diagnosis of psychiatric disorders, potentially surpassing human capabilities in both speed and accuracy. …”
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Proposing a framework for body mass prediction with point clouds: A study applied in typical swine pen environments by Gabriel Pagin, Luciane Silva Martello, Rubens André Tabile, Rafael Vieira de Sousa

“…In this context, the main objective of this research is to investigate a novel framework comprising effective algorithms for feature extraction, attribute selection, hyperparameter optimization, and prediction modelling, using point clouds collected from production animals (growing and finishing pigs). …”
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