Machine learning-based detoxification enzymes-related genes prognosis model in breast cancer: immune landscape and clinical significance by Jingdi Zhang, Wendi Zhan, Haihong Hu, Hongxia Zhu, Bo Hao, Siyu Wang, Zhuo Li, Zhiming Zhang, Taolan Zhang

“…Lasso cox regression analysis and univariate and multivariate Cox analysis were used to process the data, and machine learning algorithm was used to construct breast cancer prognosis model. …”
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Modeling the service life of temporary airfield operational surfaces under multi-pass aircraft trafficking by R.P. Kinser, T.W. Rushing, A.R. Cisko, Mark E. Barkey, P.G. Allison, J.B. Jordon

“…The proposed framework is then used to predict the rate of subgrade deformation for additional lay patterns, which successfully ranked the performance of each relative to full-scale trafficking experiments. …”
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Computed Tomography‐Based Habitat Analysis for Prognostic Stratification in Colorectal Liver Metastases by Chaoqun Zhou, Hao Xin, Lihua Qian, Yong Zhang, Jing Wang, Junpeng Luo

“…An unsupervised K‐means clustering algorithm classified the tumors into two clusters based on their habitat characteristics. …”
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AADNet: An End-to-End Deep Learning Model for Auditory Attention Decoding by Nhan Duc Thanh Nguyen, Huy Phan, Simon Geirnaert, Kaare Mikkelsen, Preben Kidmose

“…First, the algorithm predicts representations of the attended speech signal envelopes; second, it identifies the attended speech by finding the highest correlation between the predictions and the representations of the actual speech signals. …”
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Spectral Fingerprinting of Tencha Processing: Optimising the Detection of Total Free Amino Acid Content in Processing Lines by Hyperspectral Analysis by Qinghai He, Yihang Guo, Xiaoli Li, Yong He, Zhi Lin, Hui Zeng

“…This study employs VNIR-HSI combined with machine learning algorithms to develop a model for visualizing the total free amino acid content in Tencha samples that have undergone different processing steps on the production line. …”
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The Use of Artificial Intelligence in Medical Diagnostics: Opportunities, Prospects and Risks by Nataliia Sheliemina

“…However, the AI use in medicine carries certain risks related to ethics and data privacy, shortcomings in the quality of data for training algorithms, and importance of protecting against cyberthreats. …”
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Deciphering the role of miR-71 in Echinococcus multilocularis early development in vitro. by Matías Gastón Pérez, Markus Spiliotis, Natalia Rego, Natalia Macchiaroli, Laura Kamenetzky, Nancy Holroyd, Marcela Alejandra Cucher, Klaus Brehm, Mara Cecilia Rosenzvit

“…Using genomic information and bioinformatic algorithms for miRNA binding prediction, we found a high number of potential miR-71 targets in E. multilocularis. …”
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Development of an immune-related gene signature applying Ridge method for improving immunotherapy responses and clinical outcomes in lung adenocarcinoma by Zhen Chen, Yongjun Zhang

“…The sequencing data of immune-related genes were comprehensively analyzed by introducing a new computational framework and 10 machine learning algorithms (a total of 101 combinations) to determine the prognostic genes, which were further combined to develop an immune prognostic signature (IMMPS) using the stepCox and Ridge methods. …”
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CLINICAL AND LABORATORY ASPECTS OF DETECTING SPECIFIC IgE ANTIBODIES TO COW’S MILK AND ITS COMPONENTS by N. A. Alkhutova, N. A. Kovyazina, O. L. Zhizhina

“…So far, however, we have no generally approved laboratory algorithms for diagnostics and monitoring of treatment efficiency in the cow milk allergy and its compomemts.We have performed a laboratory study of 187 children at the age of 3 months to 10 years. …”
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Oxidative stress gene expression in ulcerative colitis: implications for colon cancer biomarker discovery by Ting Yan, Ting Su, Miaomiao Zhu, Qiyuan Qing, Binjie Huang, Jun Liu, Tenghui Ma

“…The model may be beneficial in prognostic prediction and guiding treatment decisions.…”
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Machine vision and learning for evaluating different rancidity grades of Prunus mandshurica (Maxim.) Koehne by Yashun Wang, Huirong Chen, Jianting Gong, Yang Cui, Huiqin Zou, Yonghong Yan

“…Discrimination and prediction models based on color features combined with multiple machine learning algorithms were established using 10-fold cross-validation and external test set validation. …”
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Current Status of Application of Spaceborne GNSS-R Raw Intermediate-Frequency Signal Measurements: Comprehensive Review by Qiulan Wang, Jinwei Bu, Yutong Wang, Donglan Huang, Hui Yang, Xiaoqing Zuo

“…These research results have important application potential in fields such as environmental monitoring, climate change research, and weather prediction, and are expected to provide new technological means for global geophysical parameter retrieval.…”
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FrameBoost: Advanced Video Analytics With Inference Trigger Frame Selection via Tracking Error Estimation by Jin Mo Yang, Sunwook Hwang, Jeongjun Park, Saewoong Bahk

“…Beyond selecting critical frames for system accuracy, a major requirement for ITF selection algorithms is efficiency. They must be able to extract informative frames while imposing minimal computational overhead on the analytics pipeline. …”
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Machine Learning–Based Analysis of Lifestyle Risk Factors for Atherosclerotic Cardiovascular Disease: Retrospective Case-Control Study by Hye-Jin Kim, Heeji Choi, Hyo-Jung Ahn, Seung-Ho Shin, Chulho Kim, Sang-Hwa Lee, Jong-Hee Sohn, Jae-Jun Lee

“…MethodsUsing data from the Korea National Health and Nutrition Examination Survey, 5 ML algorithms were used for the prediction of high ASCVD risk: logistic regression (LR), support vector machine, random forest, extreme gradient boosting, and light gradient boosting models. …”
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Electricity Demand Forecasting Using Deep Polynomial Neural Networks and Gene Expression Programming During COVID-19 Pandemic by Cagatay Cebeci, Kasım Zor

“…The power-generation mix of future grids will be quite diversified with the ever-increasing share of renewable energy technologies. Therefore, the prediction of electricity demand will become crucial for resource optimization and grid stability. …”
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Identification and experimental validation of biomarkers associated with mitochondrial and programmed cell death in major depressive disorder by Shengjie Xiong, Lixin Liao, Meng Chen, Qing Gan

“…The predictive nomogram and drug predictions offer valuable tools for MDD management.…”
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AI for rapid identification of major butyrate-producing bacteria in rhesus macaques (Macaca mulatta) by Annemiek Maaskant, Donghyeok Lee, Huy Ngo, Roy C. Montijn, Jaco Bakker, Jan A. M. Langermans, Evgeni Levin

“…In addition, to improve transparency, we employed explainability analysis to uncover the image features influencing the model’s predictions. Results By integrating fecal image data with corresponding metagenomic sequencing information, the deep learning (DL) and machine learning (ML) algorithms successfully predicted 16 individual bacterial genera (area under the curve (AUC) > 0.7) among the 50 most abundant genera in rhesus macaques (Macaca mulatta). …”
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Application of Energy Dispersive X-ray Fluorescence Spectroscopy in Analysis of Heavy Metals in Soil: A Review by Aosong JIANG, Longhua WU, Zhu LI

“…Therefore, the current mainstream focus is on combining the advantages of different algorithms for the preprocessing analysis of ED-XRF spectroscopy and the establishment of quantitative analysis models to improve the accuracy of ED-XRF detection. …”
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Drought Detection in Satellite Imagery: A Layered Ensemble Machine Learning Approach by Muhammad Owais Raza, Naeem Ahmed Mahoto, Mana Saleh Al Reshan, Ali Alqazzaz, Adel Rajab, Asadullah Shaikh

“…Abstract Drought has been a major calamity due to climate change in recent years. Predicting drought has grabbed the attention of meteorologists and climate scientists, who study and look for modern techniques. …”
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Multiparameter diagnostic model using S100A9, CCL5 and blood biomarkers for nasopharyngeal carcinoma by Lu Long, Ya Tao, Wenze Yu, Qizhuo Hou, Yunlai Liang, Kangkang Huang, Huidan Luo, Bin Yi

“…Variable selection was conducted using least absolute shrinkage and selection operator (LASSO) regression. NPC prediction models were developed using four machine-learning algorithms, and their performance was evaluated with ROC curves. …”
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