Machine learning and SHAP value interpretation for predicting the response to neoadjuvant chemotherapy and long-term clinical outcomes in Chinese female breast cancer by Quan Yuan, Rongjie Ye, Yao Qian, Hao Yu, Yuexin Zhou, Xiaoqiao Cui, Feng Liu, Ming Niu

“…The Least Absolute Shrinkage and Selection Operator (LASSO) Cox algorithm, combined with XGBoost and Random Forest (RF) models, identified 9 overlapping prognostic features, enhancing the nomogram’s predictive accuracy for overall survival (OS). …”
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LYN and CYBB are pivotal immune and inflammatory genes as diagnostic biomarkers in recurrent spontaneous abortion by Zhuna Wu, Qiuya Lin, Zhimei Zhou, Yajing Xie, Li Huang, Liying Sheng, Qirong Shi, Yumin Ke

“…KEGG enrichment analyses were performed mainly on Epithelial cell signaling in Helicobacter pylori infection, NOD-like receptor signaling pathway, and Ras signaling pathway. …”
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Substituted 1,4-naphthoquinones for potential anticancer therapeutics: In vitro cytotoxic effects and QSAR-guided design of new analogs by Veda Prachayasittikul, Prasit Mandi, Ratchanok Pingaew, Supaluk Prachayasittikul, Somsak Ruchirawat, Virapong Prachayasittikul

“…Four QSAR models were successfully constructed using multiple linear regression (MLR) algorithm providing good predictive performance (R: training set = 0.8928–0.9664; testing set = 0.7824–0.9157; RMSE: training set = 0.1755–0.2600; testing set = 0.2726–0.3748). …”
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Identifying key genes involved in HBV-related hepatocellular carcinoma: diagnose, prognosis, interaction and immune analysis by Yan Li, Sa-Sa Liu, Hua-Rong Jing, Hong-Wei Qian, Rui-Cheng Li

“…Immune infiltration analysis were performed by CIBERSORT algorithm. Drug–Gene Interaction Database (DGIdb) was used to screen the potential drug that affect hub genes. …”
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Towards quantitative assessment of cerebrovascular autoregulation in human neonates using ultrafast ultrasound imaging by Nikan Fakhari, Julien Aguet, Alison Howell, Minh Nguyen, Luc Mertens, Lynn Crawford, Maelys Venet, Christoph Haller, David Barron, John G. Sled, Jérôme Baranger, Olivier Villemain

“…This study aims to use UPD combined with an algorithm for the discrimination of arteries and veins to monitor CAR during DH-CPB in neonates. …”
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Central Vascular Access Devices: Current Standards and Future Implications by Benito Baldauf, Roberto Cemin, Jana Hummel, Hendrik Bonnemeier, Ojan Assadian

“…Conclusions: The review underscores the need for clear, concise algorithms adaptable to various healthcare settings and the scalability of infection prevention systems to ensure resilience.…”
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Specifics of predicting the profitability of individual bank products based on machine learning by Inna Strelchenko, Dmytro Stognii, Anatolii Strelchenko

“…The importance of introducing intelligent algorithms in the banking sector is emphasized, which is due to the need to improve the accuracy of financial forecasts, minimize risks and improve strategic management. …”
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Energy-Efficient model for integrated berth allocation and quay crane management by Saeedeh Khalilpoor, Mehdi A. Kamran, Reza Babazadeh, Reza Kia

“…Several numerical experiments in different dimensions are defined and implemented with both algorithms. The results analysis gives an overall perspective, while both algorithms show their value and strong points and weaknesses in meeting demanding requirements of modern container terminal logistics. …”
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Transportation Mode Detection Using Learning Methods and Self-Contained Sensors: Review by Ilhem Gharbi, Fadoua Taia-Alaoui, Hassen Fourati, Nicolas Vuillerme, Zebo Zhou

“…Nowadays, recent smartphones, equipped with integrated inertial measurement units (IMUs) and embedded algorithms, can play a crucial role in such development. …”
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Speech emotion recognition using long-term average spectrum by Huerta-Hernández Luis David, Meléndez-Acosta Nayeli Joaquinita, Troncoso-Romero David Ernesto, Ramírez-Pacheco Julio César, León-Borges Jose Antonio

“…The performance of classification algorithms depends on the features extracted from speech. …”
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A learning trajectory for developing computational thinking in prospective mathematics teachers through Python programming in Google Colab by Edi Irawan, Moh. Khoridatul Huda, Ratni Purwasih

“…The results showed that HLT, designed in stages, improved the four main components of CT: decomposition, abstraction, pattern recognition, and algorithmic thinking. …”
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Fast, Robust, and Learned Distribution-Based Sorting by Paolo Ferragina, Mattia Odorisio

“…Despite a long history of research and achievements in designing sorting routines, new hardware features and application requirements pose advanced challenges that computer scientists are recently tackling through novel data-aware (learned) algorithms. This paper aims to better understand the strengths and limitations of learned sorters for numerical data, by addressing two main research and engineering questions: (Q1) Which is the best trade-off, in sorting items, between the efficacy of a “learned” model in approximating the distribution of the input data and its time-space complexity? …”
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Development of IIOT-Based Pd-Maas Using RNN-LSTM Model with Jelly Fish Optimization in the Indian Ship Building Industry by PNV Srinivasa Rao, PVY Jayasree

“…The study focuses on the optimization of predictive maintenance as a service on the industrial Internet of Things by machine learning algorithms. The main contribution of the study is the use of optimization techniques for feature selection and RNN-LSTM for improved accuracy.   …”
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Architecture of the discrete sosine transformation processor for image compression systems on the losless-to-lossy circuit by V. V. Kliuchenia

“…The hardware implementations of fixed-point DCT blocks, known as IntDCT [1] and BinDCT [2], require some solutions. One of the main issues is the choice between the implementation of the conversion on FPGA, or the implementation on a digital signal processor (Digital Signal Processor, DSP). …”
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Innovative Solutions for Oil Well Monitoring: Data-Driven Multiphase Virtual Flow Metering Using Ensemble Machine Learning and Historical Field Data by Wael A. Farag, Hussein H. Ismail, Muhammad Nadeem

“…By combining data-driven ensemble machine-learning algorithms and historical oil field portable test reports, this paper proposes a Data-Drive Multiphase Virtual Flow Meter (DD-MVFM) that estimates oil, gas, and water flow rates and provides real-time monitoring, and predicts future production with appropriate accuracy. …”
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Enhancing Epilepsy Seizure Detection Through Advanced EEG Preprocessing Techniques and Peak-to-Peak Amplitude Fluctuation Analysis by Muawiyah A. Bahhah, Eyad Talal Attar

“…<b>Results:</b> The results indicated that the frontal and parietal regions, particularly the electrode areas Cz, Pz and Fp2, are the main contributors to epileptic seizures. Additionally, the implementation of the PPAF metric enhanced the effectiveness of seizure detection and classification algorithms, achieving accuracy rates of 99%, 98% and 95% for datasets with three, four and five seizures, respectively. …”
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Research Progress on Process Optimization of Metal Materials in Wire Electrical Discharge Machining by Xinfeng Zhao, Binghui Dong, Shengwen Dong, Wuyi Ming

“…It highlights that the integration of AI by optimization algorithms (such as Genetic Algorithms, particle swarm optimization, and manta ray foraging optimization) offers an effective path toward the intelligent evolution of WEDM processes. …”
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Community detection in empirical kinase networks identifies new potential members of signalling pathways. by Celia De Los Angeles Colomina Basanta, Marya Bazzi, Maruan Hijazi, Conrad Bessant, Pedro R Cutillas

“…Here, we assess whether the application of community detection algorithms to such networks can identify new components linked to canonical signalling pathways. …”
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A Comparative Study in Fuzzy Control Systems for Cruise Control Vehicles by Adnan Shaout, Malek I El Amr

“…The challenging problem of comparing different algorithms for fuzzy cruise control has been considered, studied, and ana-lyzed. …”
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High-Performance Multi-Object Tracking for Autonomous Driving in Urban Scenarios With Heterogeneous Embedded Boards by Alessio Medaglini, Biagio Peccerillo, Sandro Bartolini

“…The main objective is to exploit the high-performance capabilities of NVIDIA heterogeneous embedded platforms, which are not automatically compatible with the peculiar features of these algorithms. …”
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