Optimized workflow for behavior-coupled fiber photometry experiment: improved data navigation and accessibility by Anna Athanassi, Amaury François, Emmanuel Bourinet, Marc Thevenet, Nathalie Mandairon

“…Our approach allows ease of data analysis and exploration using custom algorithms and scripts that extract and process both fiber photometry and behavioral data, without relying on predefined event markers. …”
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Accurate estimation of permeability reduction resulted from low salinity water flooding in clay-rich sandstones by Xiaojuan Zhang, Muntadher Abed Hussein, Tarak Vora, Anupam Yadav, Asha Rajiv, Aman Shankhyan, Sachin Jaidka, Mehul Manu, Farzona Alimova, Issa Mohammed Kadhim, Zainab Jamal Hamoodah, Fadhil Faez, Ahmad Khalid

“…The results show that random forest and ensemble learning algorithms delivered the highest predictive accuracy, evidenced by the most substantial coefficient of determination (R2) and minimal error metrics. …”
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Data-driven prediction of critical diameter for deterministic lateral displacement devices: an integrated DPD-ML approach by Shuai Liu, Peng Zhang, Anbin Wang, Keke Tang, Shuo Chen, Chensen Lin

“…This leads to significant economic and time costs, while the complexity of instruments and algorithms further raises the barrier for DLD design and optimization. …”
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Feasibility of machine learning–based modeling and prediction to assess osteosarcoma outcomes by Qinfei Zhao, Weiquan Hu, Yu Xia, Shengyun Dai, Xiangsheng Wu, Jing Chen, Xiaoying Yuan, Tianyu Zhong, Xuxiang Xi, Qi Wang

“…Using 66 combinations of 10 machine learning (ML) algorithms, we developed a machine learning-derived prognostic signature (MLDPS) optimized by the average C-index across TARGET, GSE21257, and merged cohorts. …”
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Saliva-derived transcriptomic signature for gastric cancer detection using machine learning and leveraging publicly available datasets by Catarina Lopes, Andreia Brandão, Manuel R. Teixeira, Mário Dinis-Ribeiro, Carina Pereira

“…Leveraging transcriptomic data from the Gene Expression Omnibus (GEO), we constructed and validated predictive models through machine learning algorithms within the tidymodels framework. Tissue-based models were validated on independent tissue datasets, and subsequently applied to saliva. …”
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Designing CITOBOT: A portable device for cervical cancer screening using human-centered design, smart prototyping, and artificial intelligence by Marcela Arrivillaga, Paula C. Bermúdez, Juan Pablo García-Cifuentes, Hernán Darío Vargas-Cardona, Daniela Neira, Maria del Mar Torres, Mérida Rodríguez-López, Daniela Morales, Bleider Arizala

“…Additionally, we developed AI algorithms using the Inception V3 network, optimized with Transfer Learning and Fine Tuning, for cervical image classification and offline-operating software that guides the physician through the examination and provides a risk assessment for cervical cancer. …”
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Towards a digital twin: Digitization and model-based optimization of the innovative high-gradient magnetic separatorMendeley Data by Marko Tesanovic, Torben Bardel, Robin Karl, Sonja Berensmeier

“…Furthermore, process efficiency is often not fully realized due to the reliance on fixed operational recipes.This study presents a digital twin framework for a pilot-scale HGMS system, integrating real-time monitoring, automated control, advanced mechanistic models, and multi-objective optimization using Bayesian algorithms. The framework was validated for robustness, scalable data handling, and predictive control. …”
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Optimization Techniques for Physician Scheduling Problem: A Systematic Review of Recent Advancements and Future Directions by Norizal Abdullah, Masri Ayob, Meng Chun Lam, Nasser R. Sabar, Graham Kendall, Mohamad Khairulamirin Md Razali

“…Future research directions are outlined, emphasizing the need for more scalable algorithms, real-time scheduling capabilities, improved user interfaces, and comprehensive validation studies. …”
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Neural network architecture search enabled wide-deep learning (NAS-WD) for spatially heterogenous property awared chicken woody breast classification and hardness regression by Chaitanya Pallerla, Yihong Feng, Casey M. Owens, Ramesh Bahadur Bist, Siavash Mahmoudi, Pouya Sohrabipour, Amirreza Davar, Dongyi Wang

“…Hyperspectral imaging (HSI) combined with machine learning algorithms can evaluate the WB conditions of fillets in a non-invasive, objective, and high-throughput manner. …”
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Identification and validation of immune-related and inflammation-related genes in endometriosis by Yanzhen Zhou, Yanzhen Zhou, Jingmin Li, Meihuan Chen, Hailong Huang, Hailong Huang

“…Using machine learning algorithms, five key genes were selected in the endometriosis: BST2, IL4R, INHBA, PTGER2, and MET. …”
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Advancements in Hybrid Energy Storage Systems for Rural Electrification: A Comprehensive Case Study on Siwa Oasis in Egypt on Increasing Battery Longevity in Standalone PV Systems by Khalid Alqunun, Nehad M. Khattab, Ismail Marouani, Kamel Tlijani, Mohamed Abdelhameed Zaky, Loay Mohamed Ali El-Sayed, Ahmed Ibrahim Omar, Badr M. Alshammari, Tawfik Guesmi, Ahmed Hussain Elmetwaly, Ramy Adel Younis

“…These systems differ in topology, intricacy, and control algorithms. This research article offers a thorough assessment of the latest advancements in the field of HESS and examines various topologies that could potentially increase the longevity of Lead-acid batteries in PVPS. …”
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YOLOv8-TF: Transformer-Enhanced YOLOv8 for Underwater Fish Species Recognition with Class Imbalance Handling by Chiranjibi Shah, M M Nabi, Simegnew Yihunie Alaba, Iffat Ara Ebu, Jack Prior, Matthew D. Campbell, Ryan Caillouet, Matthew D. Grossi, Timothy Rowell, Farron Wallace, John E. Ball, Robert Moorhead

“…However, implementing fish species detection algorithms in underwater environments presents significant challenges due to factors such as varying lighting conditions, water turbidity, and the diverse appearances of fish species. …”
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Individual Tree Segmentation Based on Region-Growing and Density-Guided Canopy 3-D Morphology Detection Using UAV LiDAR Data by Shihua Li, Shunda Zhao, Zhilin Tian, Hao Tang, Zhonghua Su

“…Currently, existing methods fail to fully utilize the height information, density information, and vertical structure details of tree crowns within point cloud data, resulting in complex algorithmic processes and reduced reliability. This study proposes a novel method that combines the canopy height model (CHM) and point cloud data for segmenting individual trees and employs height and density information for morphological detection of tree canopies. …”
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BioDeepfuse: a hybrid deep learning approach with integrated feature extraction techniques for enhanced non-coding RNA classification by Anderson P. Avila Santos, Breno L. S. de Almeida, Robson P. Bonidia, Peter F. Stadler, Polonca Stefanic, Ines Mandic-Mulec, Ulisses Rocha, Danilo S. Sanches, André C.P.L.F. de Carvalho

“…Recently, deep learning algorithms have provided advancements in ncRNA classification. …”
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Intelligent Diagnosis and Predictive Rehabilitation Assessment of Chronic Ankle Instability Using Shoe-Integrated Sensor System by Zhonghe Guo, Yanzhang Li, Yuchen Wang, Haoxuan Liu, Rui Guo, Jingzhong Ma, Xiaoming Wu, Dong Jiang, Tianling Ren

“…We collected and processed level walking data from 80 CAI patients diagnosed by professional experts and 42 healthy individuals using the system, including feature extraction and filtering algorithms. An artificial intelligence diagnosis was applied to the data, achieving a classification accuracy of 93.39% and an area under the curve (AUC) of 0.959, satisfying the clinical requirements for accuracy. …”
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Machine learning for prediction of childhood mental health problems in social care by Ryan Crowley, Katherine Parkin, Emma Rocheteau, Efthalia Massou, Yasmin Friedmann, Ann John, Rachel Sippy, Pietro Liò, Anna Moore

“…The best-performing model, a gradient boosting classifier, achieved an area under the receiver operating characteristic curve of 0.75 (95% CI 0.73–0.78). Assessments of algorithmic fairness showed potential biases within these models. …”
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Advanced thermal management with heat pipes in lithium-ion battery systems: Innovations and AI-driven optimization by Mehwish Khan Mahek, Mohamad Ramadan, Mohammed Ghazal, Fahid Riaz, Daniel S. Choi, Mohammad Alkhedher

“…Furthermore, extensive literature research reveals AI's role in fine-tuning operational parameters, crafting algorithms to predict core temperatures in HP systems, and employing advanced optimization and deep learning techniques for efficient and safe management of HP-cooled reactors under stringent power limitations. …”
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Blockchain and NFT-Based Solution for Genomic Data Management, Sharing, and Monetization by Ahmad Musamih, Khaled Salah, Raja Jayaraman, Samer Ellaham, Mohammed Omar, Ibrar Yaqoob

“…We present various diagrams and algorithms to illustrate the functionality of our solution. …”
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Climate change and tree cover loss affect the habitat suitability of Cedrela angustifolia: evaluating climate vulnerability and conservation in Andean montane forests by Fressia N. Ames-Martínez, Ivan Capcha Romero, Anthony Guerra, Janet Gaby Inga Guillen, Harold Rusbelth Quispe-Melgar, Esteban Galeano, Ernesto C. Rodríguez-Ramírez

“…Methods Using ecological niche modeling with two algorithms (maximum entropy (MaxEnt) and Random Forest) under the ecological niche conservatism approach, we generated 16,920 models with different combinations of variables and parameters. …”
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Analysis of follow-up data in large biobank cohorts: a review of methodology by Anastassia Kolde, Anastassia Kolde, Merli Koitmäe, Merli Koitmäe, Meelis Käärik, Märt Möls, Krista Fischer, Krista Fischer

“…We address four primary issues: left-truncation of the data, computational inefficiency of standard model-fitting algorithms, relatedness among individuals, and model misspecification. …”
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