Machine learning-driven multi-omics analysis identifies a prognostic gene signature associated with programmed cell death and metabolism in hepatocellular carcinoma by Xiang Li, Donghao Yin, Jiahao Geng, Yanyu Xu, Zijing Xu, Xuemeng Yang, Quanwei Li, Zimeng Shang, Zhiyun Yang, Zhong Xu, Jiabo Wang, Enxiang Zhang, Xinhua Song

“…Based on prognosis-related DEGs, patients and cells were stratified into high- and low-expression groups using corresponding computational algorithms. The intersecting DEGs from both datasets were analyzed using univariate Cox regression, and a prognostic risk score model was constructed through machine learning algorithms. …”
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A Nomogram for Predicting Recurrence in Stage I Non‐Small Cell Lung Cancer by Rongrong Bian, Feng Zhao, Bo Peng, Jin Zhang, Qixing Mao, Lin Wang, Qiang Chen

“…In the discovery phase, two algorithms, least absolute shrinkage and selector operation and support vector machine‐recursive feature elimination, were used to identify candidate genes. …”
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Identification of SMYD2 as a candidate diagnostic and prognostic biomarker for gastric cancer by Sichao Wang, Chuanxi Zhao, Dongmei Li, Qingzhi Liu, Cuiping Mao, Shanshan Ding, Shujun Zhang, Wenjing Shang

“…This study aimed to investigate their biological functions and mechanisms in GC, with additional focus on exploring the clinical value of SMYD2.MethodsWe performed integrated analyses of transcriptome profiling and somatic mutation alteration in GC samples from the Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO) datasets to characterize HMEs alterations in GC. …”
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A Monocyte-Driven Prognostic Model for Multiple Myeloma: Multi-Omics and Machine Learning Insights by Xie L, Gao M, Tan S, Zhou Y, Liu J, Wang L, Li X

“…Subsequently, based on 482 prognostic moDEGs, we developed and validated an optimal model, termed the Monocyte-related Gene Prognostic Signature (MGPS), by integrating 101 predictive models generated from 10 machine learning algorithms across multiple transcriptome sequencing datasets. …”
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RAD-Seq-derived SSR markers: a new paradigm for genetic analysis and construction of genetically improved production populations in Pinus koraiensis by Pingyu Yan, Wanying Zhang, Junfei Hao, Xiaotian Miao, Jun Wu, Zixiong Xie, Zhixin Li, Lei Zhang, Hanguo Zhang

“…The genetic data were then integrated with multiyear cone production records from the population of plus trees, thus facilitating the construction of a production population. …”
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Uso de inteligencia artificial para predecir complicaciones en cirugías de columna toracolumbar degenerativa: revisión sistemática by G. Ricciardi, J.I. Cirillo Totera, R. Pons Belmonte, L. Romero Valverde, F. López Muñoz, A. Manríquez Díaz

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[Translated article] Use of artificial intelligence to predict complications in degenerative thoracolumbar spine surgery: A systematic review by G. Ricciardi, J.I. Cirillo Totera, R. Pons Belmonte, L. Romero Valverde, F. López Muñoz, A. Manríquez Díaz

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Pose measurement method for coal mine drilling robot based on deep learning by Jiangnan LUO, Jianping LI, Hongxiang JIANG, Deyi ZHANG

“…Specifically, the IoU values for the drill head and gripper increased by 34.9% and 60.3%, respectively. …”
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Developing a Multisensor-Based Machine Learning Technology (Aidar Decompensation Index) for Real-Time Automated Detection of Post–COVID-19 Condition: Protocol for an Observational... by Jenny Mathew, Jaclyn A Pagliaro, Sathyanarayanan Elumalai, Lauren K Wash, Ka Ly, Alison J Leibowitz, Varsha G Vimalananda

“…To improve prediction accuracy, data may be stratified based on biological sex, race, ethnicity, or underlying clinical characteristics into subgroups to determine if there are differences in performance and detection lead times. Using appropriate algorithmic techniques, the study expects the model to have a sensitivity of >80% and a positive predicted value of >70%. …”
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Application of Concentration-Area fractal modeling and artificial neural network to identify Cu, Zn±Pb geochemical anomalies in Hashtjin area, NW of Iran by Ali Imamalipour, Hamed Ebrahimi, Amir reza Abdollahpur

“…Recent research investigations have shown that Machine Learning (ML) algorithms can identify geochemical anomalies associated with mineralization that represent targets for mineral exploration. …”
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Modeling and validation of wearable sensor-based gait parameters in Parkinson’s disease patients with cognitive impairment by Guo Hong, Guo Hong, Fengju Mao, Fengju Mao, Mingming Zhang, Fei Zhang, Fei Zhang, Xiangcheng Wang, Kang Ren, Kang Ren, Zhonglue Chen, Zhonglue Chen, Xiaoguang Luo, Xiaoguang Luo

“…Additionally, it sought to integrate these findings with machine learning methods to enhance prediction accuracy.MethodsA cross-sectional study was conducted on early-to-mid-stage PD patients, with approximately 28.8% diagnosed with cognitive impairment. …”
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Machine learning identification of a novel vasculogenic mimicry-related signature and FOXM1’s role in promoting vasculogenic mimicry in clear cell renal cell carcinoma by Chao Xu, Sujing Zhang, Jingwei Lv, Yilong Cao, Yao Chen, Hao Sun, Shengtao Dai, Bowei Zhang, Meng Zhu, Yuepeng Liu, Junfei Gu

“…We developed a machine learning framework integrating 12 algorithms to establish a consistent VM-related signature (VRG_score). …”
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Systemic immune-inflammatory biomarkers combined with the CRP-albumin-lymphocyte index predict surgical site infection following posterior lumbar spinal fusion: a retrospective stu... by Zixiang Pang, Jiawei Liang, Jiayi Chen, Yangqin Ou, Qinmian Wu, Shengsheng Huang, Shengbin Huang, Yuanming Chen

“…The top seven performing models (assessed by AUC, accuracy, sensitivity, specificity, precision, and F1 scores) were integrated into a dynamic nomogram. Internal validation employed ROC analysis and calibration curves, while Shapley Additive Explanations (SHAP) values interpreted feature importance in the optimal model.ResultsAmong 2,921 screened patients, 1,272 met inclusion criteria. …”
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Comprehensive Analysis of Phenotypic Traits in Chinese Cabbage Using 3D Point Cloud Technology by Chongchong Yang, Lei Sun, Jun Zhang, Xiaofei Fan, Dongfang Zhang, Tianyi Ren, Minggeng Liu, Zhiming Zhang, Wei Ma

“…Based on the plant spread and plant height, a linear regression prediction of Chinese cabbage weights was conducted, yielding an R² value of 0.76. Integrated optimization algorithms were used to test the parameters, reducing the measurement time from 55 min when using traditional methods to 3.2 min. …”
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Supporting self-management with an internet intervention for low back pain in primary care: a RCT (SupportBack 2) by Adam W A Geraghty, Taeko Becque, Lisa C Roberts, Jonathan Hill, Nadine E Foster, Lucy Yardley, Beth Stuart, David A Turner, Gareth Griffiths, Frances Webley, Lorraine Durcan, Alannah Morgan, Stephanie Hughes, Sarah Bathers, Stephanie Butler-Walley, Simon Wathall, Gemma Mansell, Malcolm White, Firoza Davies, Paul Little

“…Finally, we explored whether these options would represent ‘good value for money’ for the National Health Service. …”
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Predictors of Successful Testicular Sperm Extraction: A New Era for Men with Non-Obstructive Azoospermia by Aris Kaltsas, Sofoklis Stavros, Zisis Kratiras, Athanasios Zikopoulos, Nikolaos Machairiotis, Anastasios Potiris, Fotios Dimitriadis, Nikolaos Sofikitis, Michael Chrisofos, Athanasios Zachariou

“…Advanced imaging techniques like high-frequency ultrasound and functional magnetic resonance imaging offer potential but require further validation. Integrating molecular biomarkers with artificial intelligence and machine learning algorithms may enhance predictive accuracy. …”
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A precise estimation framework for individual tree AGB of Pinus kesiya var. Langbianensis utilizing point cloud registration Optimization by Zhibo Yu, Yong Wu, Ziyu Zhang, Chi Lu, Hong Wang, Zhi Liu, Xiaoli Zhang, Lei Bao, Jie Pan, Guanglong Ou, Hongbin Luo

“…To enhance AGB estimation accuracy, we integrated unmanned aerial vehicle laser scanning (ULS) and backpack laser scanning (BLS) point clouds using the Iterative Closest Point (ICP) algorithm for precise registration and fusion under varying slope conditions, enabling 3D tree reconstruction. …”
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Modeling the effects of climate change scenarios on the potential distribution of Vespa crabro Linnaeus, 1758 (Hymenoptera: Vespidae) in a Mediterranean biodiversity hotspot by Erika Bazzato, Arturo Cocco, Emanuele Salaris, Ignazio Floris, Alberto Satta, Michelina Pusceddu

“…Future projections indicate a distribution range contraction by the 2040s and 2060s, primarily driven by extreme variability in precipitation and rising temperatures approaching the species' thermal tolerance limits.Our study demonstrates the value of integrating citizen science data, high-resolution climate data, and advanced modeling techniques to understand and manage alien species in the context of climate change. …”
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Defining analytical skills for human resources analytics: A call for standardization by Konrad Kulikowski

“…PURPOSE: Human resources (HR) analytics systems, powered by big data, AI algorithms, and information technology, are increasingly adopted by organizations to enhance HR’s impact on business performance. …”
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Pengukuran Performa Apache Spark dengan Library H2O Menggunakan Benchmark Hibench Berbasis Cloud Computing by Aminudin Aminudin, Eko Budi Cahyono

“…In order for Apache Spark to be able to do machine learning processes, in this paper an experiment will be conducted that integrates Apache Spark which acts as a large data processing environment and the concept of parallel computing will be combined with H2O libraries specifically for handling data processing using machine learning algorithms . …”
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