Integrating bioinformatics and machine learning for comprehensive analysis and validation of diagnostic biomarkers and immune cell infiltration characteristics in pediatric septic... by Peng Lyu, Na Xie, Xu-peng Shao, Shuai Xing, Xiao-yue Wang, Li-yun Duan, Xue Zhao, Jia-min Lu, Rong-fei Liu, Duo Zhang, Wei Lu, Kai-liang Fan

“…Abstract This study aims to predict and diagnose pediatric septic shock through the screening of immune infiltration-related biomarkers. …”
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Social Media Suicide Watch by Katherine Prothro

“…However, the Samaritan’s Radar app did not notify users that an algorithm was analyzing their content for signs of distress. …”
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Transcription factor networks and novel immune biomarkers reveal key prognostic and therapeutic insights in ovarian cancer by Aiqin Zhao, Sufang Zhou, Xiaoyi Yang, Haiying Lu, Dan Zou, Xuan Zhang, Li Liu

“…To analyze the percentage of invading immune cells, the algorithms CIBERSORT, ESTIMATE, and xCell were used. …”
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Plasma cfDNA multi-omic biomarkers profiling for detection and stratification of gastric carcinoma by Shiyi Song, Xiuli Zhang, Pin Cui, Weihuang He, Jiyuan Zhou, Shubing Wang, Yong Xiong, Shu Xu, Xiaohui Lin, Guozeng Huang, Xiaohua Tan, Qinglong Xu, Yongling Liu, Qingqun Li, Kehua Yuan, Mingji Feng, Hanming Lai, Hui Yang, Shaorong Zhang

“…And these biomarkers were extracted from WGS data to build machine learning algorithm based classifiers, prediction models, to discriminate GC patients from healthy individuals, achieving extremely high precision of sensitivity at 94.87% and specificity at 99.35%. …”
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Rapid discrimination and quantification of chemotypes in Perillae folium using FT-NIR spectroscopy and GC–MS combined with chemometrics by Dai-xin Yu, Cheng Qu, Jia-yi Xu, Jia-yu Lu, Di-di Wu, Qi-nan Wu

“…Based on FT-NIR data, different chemotypes were accurately classified. The random forest algorithm achieved >90 % accuracy in chemotype classification. …”
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Universal Vector Calibration for Orientation-Invariant 3D Sensor Data by Wonjoon Son, Lynn Choi

“…To resolve these problems, we propose a universal vector calibration algorithm that enables consistent three-dimensional vector measurements for the same physical activity, regardless of device orientation. …”
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ADVERTISING CAMPAIGN OF HIGHER EDUCATION INSTITUTION DEVELOPMENT BASICS by Natela R. Kordzaia

“…The article also reveals the content of each of the stages of the algorithm. Each stage of the algorithm must be carefully thought out and worked out.…”
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Identification and validation of a prognostic risk model based on radiosensitivity-related genes in nasopharyngeal carcinoma by Yi Li, Xinyi Hong, Wenqian Xu, Jinhong Guo, Yongyuan Su, Haolan Li, Yingjie Xie, Xing Chen, Xiong Zheng, Sufang Qiu

“…This study aims to identify radiosensitivity-related genes in NPC and develop a prognostic model to predict patient outcomes. Methods: We analyzed 179 NPC samples from Fujian Cancer Hospital using RNA sequencing. …”
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Using Features Extracted From Upper Limb Reaching Tasks to Detect Parkinson’s Disease by Means of Machine Learning Models by Giuseppe Cesarelli, Leandro Donisi, Francesco Amato, Maria Romano, Mario Cesarelli, Giovanni D'Addio, Alfonso M. Ponsiglione, Carlo Ricciardi

“…The investigation carried out in our work has proved the predictive power of the features, extracted from the reaching tasks involving the upper limbs, to distinguish HCs and PD patients.…”
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Type 1 diabetes prevention clinical trial simulator: Case reports of model‐informed drug development tool by Juan Francisco Morales, Marian Klose, Yannick Hoffert, Jagdeep T. Podichetty, Jackson Burton, Stephan Schmidt, Klaus Romero, Inish O'Doherty, Frank Martin, Martha Campbell‐Thompson, Michael J. Haller, Mark A. Atkinson, Sarah Kim

“…To increase the size of the population pool, we generated virtual populations using multivariate normal distribution and ctree machine learning algorithms. As an output, power was calculated, which summarizes the probability of success, showing a statistically significant difference in the time distribution until the T1D diagnosis between the two arms. …”
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Machine learning identifies lipid-associated genes and constructs diagnostic and prognostic models for idiopathic pulmonary fibrosis by Xingren Liu, Junmei Song, Shujin Guo, Yi Liao, Jun Zou, Liqing Yang, Caiyu Jiang

“…Genes from this module were used to construct diagnostic and prognostic models, which demonstrated strong predictive performance across multiple validation datasets. …”
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The multiple uses of artificial intelligence in exercise programs: a narrative review by Alberto Canzone, Alberto Canzone, Giacomo Belmonte, Antonino Patti, Domenico Savio Salvatore Vicari, Domenico Savio Salvatore Vicari, Fabio Rapisarda, Valerio Giustino, Patrik Drid, Antonino Bianco

“…BackgroundArtificial intelligence is based on algorithms that enable machines to perform tasks and activities that generally require human intelligence, and its use offers innovative solutions in various fields. …”
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METTL1-driven nucleotide metabolism reprograms the immune microenvironment in hepatocellular carcinoma: a multi-omics approach for prognostic biomarker discovery by Xie Weng, Yangyue Huang, Zhuoya Fu, Xingli Liu, Fuli Xie, Jiale Wang, Qiaohua Zhu, Dayong Zheng, Dayong Zheng

“…Moreover, the prognostic model integrating METTL1 expression and immune checkpoint profiles shows strong predictive performance across independent cohorts, highlighting its potential clinical utility.ConclusionThis study highlights the innovative role of METTL1-driven nucleotide metabolism reprogramming in reshaping the immune microenvironment of HCC. …”
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Metabolic pathway activation and immune microenvironment features in non-small cell lung cancer: insights from single-cell transcriptomics by Yanru Liu, Yanru Liu, Yanru Liu, Hanmin Liu, Hanmin Liu, Ying Xiong, Ying Xiong

“…Given that lung cancer is a leading cause of cancer-related deaths globally and NSCLC accounts for the majority of lung cancer cases, understanding the relationship between TME and metabolic pathways in NSCLC is crucial for developing new treatment strategies.MethodsFinally, machine learning algorithms were employed to construct a risk signature with strong predictive power across multiple independent cohorts. …”
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Projecting Forest Fire Probability in South Korea Under Climate Change, Population, and Forest Management Scenarios Using AI & Process-Based Hybrid Model (FLAM-Net) by Hyun-Woo Jo, Myoungsoo Won, Florian Kraxner, Seong Woo Jeon, Yowhan Son, Andrey Krasovskiy, Woo-Kyun Lee

“…Enhancements included improving backpropagation for optimization and introducing algorithms for national-specific fire ignition dynamics. …”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti, Hafsa Binte Kibria, Zareen Tasnim Pear, Md Nahiduzzaman, Md. Faysal Ahamed, Khandaker Reajul Islam, Jaya Kumar, Muhammad E. H. Chowdhury

“…Three different publicly available datasets have been used based on the age group to create the best predicting model for each case. After handling missing values, balancing the dataset, and analyzing the classifier’s performance, it is found that tree-based algorithms, particularly RF, perform better for all the datasets. …”
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Causes of embryo implantation failure: A systematic review and metaanalysis of procedures to increase embryo implantation potential by Francesco M. Bulletti, Romualdo Sciorio, Alessandro Conforti, Roberto De Luca, Carlo Bulletti, Antonio Palagiano, Marco Berrettini, Giulia Scaravelli, Roger A. Pierson

“…Subsequent studies ought to concentrate on modulating endometrial responses immunologically and developing algorithms to improve the precision of predicting implantation success; as well as the timing of endometrial receptivity and the occurrence of dormant embryo phenomena also warrants further investigation.…”
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Comprehensive profiling of chemokine and NETosis-associated genes in sarcopenia: construction of a machine learning-based diagnostic nomogram by Yingwei Wang, Le Wang, Yan Zhang, Minghui Wang, Huaying Zhao, Cheng Huang, Huaiyang Cai, Shuangyang Mo

“…Two machine learning algorithms and univariate analysis were integrated to screen signature genes, which were subsequently used to construct diagnostic nomogram models for sarcopenia. …”
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Bioinformatics analysis of comorbid mechanisms between ischemic stroke and end stage renal disease by Shuhong Wang, Zhongda Li, Xiao Wang, Jiexue Zhou, Shandong Meng, Jinyang Zhuang, Yan Zhou, Qin Zhao, Chunli Zhu, Yusheng Zhang, Sheng Shen

“…Protein-protein interaction networks were constructed using STRING with clustering algorithms. Immune cell infiltration analysis was performed via CIBERSORT. …”
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Enhancing ovarian cancer prognosis with an artificial intelligence-derived model: Multi-omics integration and therapeutic implications by You Wu, Kunyu Wang, Yan Song, Bin Li

“…Results: The AIDPI model demonstrated superior accuracy in predicting ovarian cancer prognosis compared to existing models. …”
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