The molecular characteristics of DNA damage and repair related to P53 mutation for predicting the recurrence and immunotherapy response in hepatocellular carcinoma by Jiayao Ma, Diya Tang, Guangzu Cui, Xiangyang Zhang, Xinwen Wang, Yin Li, Erya Hu, Xin Zhou, Haicong Liu, Qingping Peng, Changjing Cai, Xiangying Deng, Shan Zeng, Yihong Chen, Zemin Xiao

“…It came out that DDR pathways were significantly enriched in samples with P53 mutations. Next, among the 173 combinations of algorithms and parameters, CoxBoost + RSF, Lasso [fold = 10] + RSF, and Lasso [fold = 50] + RSF demonstrated the best performance. …”
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Providing contexts for classification of transients in a wide-area sky survey: An application of noise-induced cluster ensemble by Tossapon Boongoen, Natthakan Iam-On, James Mullaney

“…The results with simulated data and algorithms of NB, C4.5 and KNN have shown that the proposed framework can filter out some negative samples quickly, while making classification of the rest more effective. …”
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Optimizing Neural Recording Front-Ends Toward Enhanced Spike Sorting Accuracy in High-Channel-Count Systems by Yunzhu Chen, Xiaolin Yang, Georges Gielen, Carolina Mora Lopez

“…These include the filter order and cutoff frequency, ADC resolution, ADC sampling frequency, and nonlinearity. Our findings indicate that optimal spike-sorting results are obtained with a 1st-order bandpass Butterworth filter ranging from 700 Hz to 7.5 kHz, coupled with an ADC that offers a 15-kHz sampling frequency at 8-bit resolution and no missing codes. …”
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Screening of endoplasmic reticulum stress characteristic genes and immune infiltration manifestations in chronic obstructive pulmonary disease by ZHANG Shuang, LUO Chenyang, HE Zhiyi

“…Three machine learning algorithms, LASSO, SVM-RFE, and RF, were used to screen the characteristic genes, and their diagnostic performance was verified and evaluated in the GSE10006. …”
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Exploring ischemic stroke based on the ferroptosis perspective: ECH1 may serve as a new biomarker and therapeutic target by Rendong Qu, Yiyan Zhang, Haojia Zhang, Ke Li, Boning Zhang, Hongxuan Tong, Tao Lu

“…Using differential expression analysis and machine learning algorithms, 12 potential hub genes were successfully screened. …”
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Fish Detection Using Deep Learning by Suxia Cui, Yu Zhou, Yonghui Wang, Lujun Zhai

“…An advanced system with more computing power can facilitate deep learning feature, which exploit many neural network algorithms to simulate human brains. In this paper, a convolutional neural network (CNN) based fish detection method was proposed. …”
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Identification and verification of immune and oxidative stress-related diagnostic indicators for malignant lung nodules through WGCNA and machine learning by Zhou An, Meichun Zeng, Xianhua Wang

“…To develop a diagnostic model for LNs, we investigated 113 combinations of 12 machine-learning algorithms, employing 10-fold cross-validation on the training set, followed by external validation of the test set. …”
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Physics-Based Data Augmentation Enables Accurate Machine Learning Prediction of Melt Pool Geometry by Siqi Liu, Ruina Li, Jiayi Zhou, Chaoyuan Dai, Jingui Yu, Qiaoxin Zhang

“…This study proposes a hybrid framework that integrates an explicit thermal model with ML algorithms to improve prediction under sparse data conditions. …”
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PoPoolation: a toolbox for population genetic analysis of next generation sequencing data from pooled individuals. by Robert Kofler, Pablo Orozco-terWengel, Nicola De Maio, Ram Vinay Pandey, Viola Nolte, Andreas Futschik, Carolin Kosiol, Christian Schlötterer

“…Recent statistical analyses suggest that sequencing of pooled samples provides a cost effective approach to determine genome-wide population genetic parameters. …”
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Computational fluid dynamics and machine learning integration for evaluating solar thermal collector efficiency -Based parameter analysis by Xiaoyu Hu, Lanting Guo, Jiyuan Wang, Yang Liu

“…The study identifies a critical transition at 100–300 samples where error rates drop sharply, with optimal performance requiring more than 600 samples. …”
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Features of the microelement composition of saliva in elderly patients by A. M. Imanov, Y. A. Mazur, E. M. Kakabadze

“…According to the results of the review study, it should be noted that it is promising to study the possibilities of the microelement composition of saliva in elderly patients both as an auxiliary method for diagnosing various pathological conditions and in developing algorithms for the prevention and treatment of a number of diseases, as well as a method for evaluating the effectiveness of ongoing therapeutic procedures.…”
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Improving Cardiovascular Disease Prediction through Stratified Machine Learning Models and Combined Datasets by Tara Yousif Mawlood, Alla Ahmad Hassan, Rebwar Khalid Muhammed, Aso M. Aladdin, Tarik A. Rashid, Bryar A. Hassan

“…Seven classification algorithms – logistic regression, random forest (RF), support vector machine (SVM), Gaussian naive Bayes (GNB), gradient boosting (GB), K-nearest neighbors, and decision tree (DT) – were employed. …”
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Transmissive Single-Pixel Grayscale Object Imaging by Zhixing Guo, Chao Zhang, Juntao Huang, Jankun Sun, Yue Zhang, Yonghang Tai, Mengdi Li

“…The efficacy of the proposed method is validated via multiple evaluation metrics alongside reconstruction algorithms, including compressive sensing total variation. …”
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A Novel Dual-Branch Global and Local Feature Extraction Network for SAR and Optical Image Registration by Xuanran Zhao, Yan Wu, Xin Hu, Zhikang Li, Ming Li

“…Second, in order to establish accurate keypoints correspondence in the matching phase, hard-mean loss function is proposed to optimize GLFE-Net, which jointly utilizes hard negative samples and remaining negative samples to guide descriptors in learning more discriminant features to better distinguish positive and negative samples in SAR and optical images. …”
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Construction and validation of immune prognosis model for lung adenocarcinoma based on machine learning by Jinyu Zheng, Xiaoyi Xu, Xianguo Chen, Xianshuai Li, Miao Fu, Yiping Zheng, Jie Yang

“…Identifying novel prognostic biomarkers is essential for improving patient outcomes.MethodsTranscriptomic and clinicopathological data from TCGA (55 tumor samples and 38 normal samples) were used to construct a prognostic model, with 30 samples for internal validation. …”
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Improving network security using keyboard dynamics: A comparative study by Ugwunna, C.O., Chukwuogo, O.E., Alabi, O.A., Kareem, M.K., Belonwu, T.S., Oloyede, S.O.

“…The keystroke dynamics dataset was gathered from Kaggle and consists of 51 subjects' keyboard dynamics data, which was collected over the course of eight sessions and six months. There are 20400 samples in all in the data. This study assessed the effectiveness of machine learning algorithms with a focus on the keystroke dynamic authentication system. …”
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Evaluation of machine learning methods for forecasting turbidity in river networks using Sentinel-2 remote sensing data by Victor Oliveira Santos, Paulo Alexandre Costa Rocha, Jesse Van Griensven Thé, Bahram Gharabaghi

“…Results show that considering the individual monitoring stations, the ML algorithms for turbidity modeling were satisfactory at locations with a larger range and standard deviation of turbidity values, achieving a mean R2 value of 59.5 %. …”
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Measuring Comparative Statistical Effectiveness of Cancer Subtype Categorization Using Gene Expression Data by Avila Clemenshia P., Deepa C.

“…When dealing with limited samples and high-dimensional biological data, most classifiers may suffer from overfitting and lower precision. …”
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Spiked Dirichlet Process Priors for Gaussian Process Models by Terrance Savitsky, Marina Vannucci

“…Our simulation results, in particular, show a reduction in posterior sampling variability and, in turn, enhanced prediction performances. …”
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Programming Languages Prediction from Stack Overflow Questions Using Deep Learning by Razowana Khan Mim, Tapu Biswas

“…In our study, queries were selected from a Stack Overflow dataset using random sampling. Then the tags were cleaned and separated the data into title, title + body, and body. …”
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