Machine learning-driven multi-targeted drug discovery in colon cancer using biomarker signatures by Tingting Liu, Lifan Zhong, Xizhe Sun, Zhijiang He, Witiao Lv, Liyun Deng, Yanfei Chen

“…The artificial intelligence model personalizes therapy by leveraging patient-specific molecular profiles, optimizing drug selection and dosage while minimizing side effects. …”
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A regression based approach to phylogenetic reconstruction from multi-sample bulk DNA sequencing of tumors. by Henri Schmidt, Benjamin J Raphael

“…This algorithm has both asymptotic and empirical improvements over linear programming (LP) approaches to the problem. …”
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Research and Analysis of Out-of-Tolerance Problem in Mold Processing Based on Intelligence by Juxian Wang

“…According to the numerical simulation results, the reasoning mechanism of an intelligent design system including instance and rule knowledge is designed, and an uncertain knowledge reasoning algorithm based on the reliability factor is proposed to improve the accuracy of mold size and reduce the overtolerance of the mold.…”
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Advancing thyroid diagnosis: integrating AI-driven CAD framework with numerical data and ultrasound images by Saleh Ateeq Almutairi

“…The proposed CAD framework employs the sparse search algorithm (SSA) for optimized feature selection from numerical data and the tree-structured Parzen estimator for tuning the hyperparameters. …”
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SSOME MODERN ASPECTS OF CATARACT TREATMENT IN CHILDREN by K. B. Pershin, N. F. Pashinova, A. V. Tcherkashina

“…On the basis of the own experience the authors suggest the algorithm of surgical tactics and optimal terms of treatment of congenital cataract and amblyopia.…”
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Research on the integrated "cloud-edge-end" intelligent and precise management and control technology system for coal mine disasters by LIU Yubing, LI Yiteng, LI Zhonghui, YIN Shan, JING Chao, LI Kai, LI Zhenxing, ZHAO Shenglei, LIU Chengfei

“…Existing research mainly focuses on monitoring and early warning technologies or algorithm optimization for individual disasters, lacking a coordinated mechanism for multi-disaster monitoring and early warning, as well as disaster avoidance path planning under emergency response. …”
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Machine learning enables legal risk assessment in internet healthcare using HIPAA data by Shixian Liu, Hailing Liu, Siyu Fan, Leming Song, Zeyu Wang

“…DNN demonstrates strong capabilities in handling complex nonlinear relationships, and XGBoost further improves classification accuracy by optimizing decision tree models through gradient boosting. …”
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Beyond labels: determining the true type of blood gas samples in ICU patients through supervised machine learning by Johan Helleberg, Anna Sundelin, Johan Mårtensson, Olav Rooyackers, Ragnar Thobaben

“…The best performing algorithm was extreme gradient boosting (XGboost) using 9 features, with an AUCPR of 0.9974 (95% CI 0.9961–0.9984), significantly better than the LR model (AUCPR = 0.9791, 95% CI 0.9651–0.9904). …”
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Target Detection in Low Grazing Angle with Adaptive OFDM Radar by Yang Xia, Zhiyong Song, Zaiqi Lu, Hao Wu, Qiang Fu

“…Then, we propose an algorithm to optimally design the transmitted subcarrier weights to improve the detection performance. …”
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Design of Automatic Scoring System for Oral English Test Based on Sequence Matching and Big Data Analysis by Ping Li, Hua Zhang, Sang-Bing Tsai

“…With the application of an automatic scoring system to all kinds of oral English tests at all levels, the efficiency of test implementation has been greatly improved. The traditional speech signal processing method only focuses on the extraction of scoring features, which could not ensure the accuracy of the scoring algorithm. …”
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Advanced GPU Techniques for Dynamic Remeshing and Self-Collision Handling in Real-Time Cloth Tearing by Jong-Hyun Kim, Jung Lee

“…We also present a method to optimize kernels based on a complete binary tree in arbitrary triangular meshes, improving performance. …”
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Research on Near-Infrared Non-Invasive Blood Glucose Detection Technology by Wang Jinshuo

“…In response to the complex and easily interfered characteristics of near-infrared spectral signals, an innovative BP neural network algorithm is introduced to construct a prediction model. …”
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An Integrated Approach to Scheduling B-CAVs in Container Terminals considering Battery Management by Shuo Wang, Jiliang Luo, Weimin Wu, Dahai Zhang, Tao Zhang

“…Furthermore, a congestion-free path plan-based improved genetic algorithm is presented to obtain a near-optimal plan for dispatching B-CAVs to perform transporting and charging operations. …”
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Guaranteed efficient energy estimation of quantum many-body Hamiltonians using ShadowGrouping by Alexander Gresch, Martin Kliesch

“…They are helpful for identifying measurement settings that improve the energy estimate the most. This task constitutes an NP-hard problem. …”
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Ultrasound combined with serological markers for predicting neonatal necrotizing enterocolitis: a machine learning approach by Yi Yang, Shoulan Zhou, Xiaomin Liu, Yanhong Zhang, Liping Lin, Chenhan Zheng, Xiaohong Zhong

“…SHAP analysis identified bowel peristalsis, C-reactive protein, albumin, bowel thickness, and procalcitonin as the most influential predictors. Decision curve analysis demonstrated a positive relative net benefit of the USPN model compared to the US and serological models in the validation set.ConclusionA machine learning model integrating ultrasound and serological markers significantly improves the prediction of NEC in neonates compared to single-modality approaches. …”
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Susceptibility assessment of freeze-thaw erosion induced debris flow using random forest, Eastern Tibetan Plateau by Yongjie Yang, Yongjie Yang, Yongjie Yang, Yuqi Zhang, Yuqi Zhang, Yuqi Zhang, Hai Huang, Hai Huang, Jinsong Zhu, Jinsong Zhu, Jinsong Zhu, Qiwei Lv, Qiwei Lv, Qiwei Lv, Jiang Peng, Jiang Peng

“…Control factors with high frequency and performance were selected from the perspectives of material sources, dynamic conditions, and hydrological factors, leading to an optimized selection strategy, and the Random Forest Algorithm was employed for susceptibility assessment (No Freeze-thaw erosion model, NFEM). …”
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Load-dependent vehicle routing problem with route time constraint: a heuristic approach by Nguyen Thuy Trang, Parthana Parthanadee, Jirachai Buddhakulsomsiri, Pham Duc Tai

“…The results show that for instances with known optimal solutions, the heuristic algorithm can reach solutions with small gaps to the optimal. …”
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End-of-Line Quality Control Based on Mel-Frequency Spectrogram Analysis and Deep Learning by Jernej Mlinarič, Boštjan Pregelj, Gregor Dolanc

“…The neural network was trained on a highly imbalanced dataset, using oversampling and Bayesian hyperparameter optimization. The final classification algorithm achieved classification metrics with high accuracy (99%). …”
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Vehicle Reidentification via Multifeature Hypergraph Fusion by Wang Li, Zhang Yong, Yuan Wei, Shi Hongxing

“…To merge multiple feature descriptors, an efficient and appropriate representation is particularly necessary, and a hypergraph is naturally suitable for modeling high-order relationships. In addition, the spatiotemporal correlation of traffic status between cameras is the constraint beyond the image, which can greatly improve the re-ID accuracy of different vehicles with similar appearances. …”
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Energy-Efficient UAV Relaying Robust Resource Allocation in Uncertain Adversarial Networks by Shakil Ahmed, Mostafa Zaman Chowdhury, Saifur Rahman Sabuj, Md Imtiajul Alam, Yeong Min Jang

“…We compare our algorithm with existing algorithms and demonstrate the improved EE UAV relaying communication for our model.…”
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