TRANS: a prediction model for EGFR mutation status in NSCLC based on radiomics and clinical features by Zhigang Chen, Huiying Lu, Ao Liu, Jia Weng, Lei Gan, Lina Zhou, Xiao Ding, Shicheng Li

“…A nomogram was developed by integrating predictive features. Biological functions were analyzed utilizing RNA sequencing data. …”
Get full text

A multitask framework based on CA-EfficientNetV2 for the prediction of glioma molecular biomarkers by Qian Xu, Feng Ning Liang, Ya Ru Cao, Jin Duan, Teng Cui, Teng Zhao, Hong Zhu

“…The CA-EfficientNetV2 model, integrated with a coordinate attention mechanism, was constructed. …”
Get full text

Detection method for dangerous behaviors of underground coal mine personnel by ZHANG Xuhui, YU Henghan, DU Yuyang, YANG Wenjuan, ZHAO Yihui, WAN Jicheng, WANG Yanqun, ZHAO Dian, TANG Duwei

“…On this basis, a personnel behavior recognition algorithm was designed to classify underground behaviors into nine categories. …”
Get full text

The Value of PET/CT-Based Radiomics in Predicting Adrenal Metastases in Patients with Cancer by Qiujun He, Xiangxing Kong, Xiangxi Meng, Xiuling Shen, Nan Li

Get full text

An Overview of the Indian Monsoon Using Micropaleontological, Geochemical, and Artificial Neural Network (ANN) Proxies During the Late Quaternary by Harunur Rashid, Xiaohui He, Yang Wang, C. K. Shum, Min Zeng

“…These data were used to construct spatial maps of the five most dominant planktonic foraminifers and illuminate their underlying environmental factors. …”
Get full text

Utilizing bioinformatics and machine learning to identify CXCR4 gene-related therapeutic targets in diabetic foot ulcers by Hengyan Zhang, Ye Zhou, Heguo Yan, Changxing Huang, Licong Yang, Yangwen Liu

“…Meanwhile, protein-protein interaction (PPI) networks were constructed using STRING to identify core genes. Feature selection methods such as LASSO, SVM-RFE and random forest algorithm were applied to localize possible therapeutic target genes. …”
Get full text

Physical Implementation and Experimental Validation of the Compensation Mechanism for a Ramp-Based AUV Recovery System by Zhaoji Qi, Lingshuai Meng, Haitao Gu, Ziyang Guo, Jinyan Wu, Chenghui Li

“…In this study, a desktop-scale physical experimental platform for recovery compensation was designed and constructed. The system integrates attitude feedback provided by an attitude sensor and dual-motor actuation to achieve active roll and pitch compensation of the capture window. …”
Get full text

Implementing Blockchain Technology for Secure Data Transactions in Cloud Computing Environments Challenges and Solutions by Dandu Varalakshmi, N Shirisha, K Suresh, Saidhbi Shaik, V Venkatesh, C F Theresa Cenate

“…The main innovation consists of a light and energy-saving blockchain construct that minimizes computing overhead and is sustained by an AI-based anomaly detection algorithm to achieve real-time threat mitigation using built-in smart contracts. …”
Get full text

Identification and functional analysis of energy metabolism and pyroptosis-related genes in diabetic nephropathy by Shan He, Jian Ye, Yu Wang, Lu yang Xie, Si Yi Liu, Qin kai Chen

“…Background: Energy metabolism and pyroptosis are integral to the pathogenesis of diabetic nephropathy (DN). …”
Get full text

Advancing patient care: Machine learning models for predicting grade 3+ toxicities in gynecologic cancer patients treated with HDR brachytherapy. by Andres Portocarrero-Bonifaz, Salman Syed, Maxwell Kassel, Grant W McKenzie, Vishwa M Shah, Bryce M Forry, Jeremy T Gaskins, Keith T Sowards, Thulasi Babitha Avula, Adrianna Masters, Jose G Schneider, Scott R Silva

“…Brachytherapy, often used as a boost to external beam radiotherapy, is integral to treatment. Advances in computation, algorithms, and data availability have popularized the use of machine learning to predict patient outcomes. …”
Get full text

Machine Learning-Driven Identification of Exosome-Related Genes in Head and Neck Squamous Cell Carcinoma for Prognostic Evaluation and Drug Response Prediction by Hua Cai, Liuqing Zhou, Yao Hu, Tao Zhou

“…A predictive model was produced by using machine learning algorithms (LASSO regression, SVM, and random forest) to find disease-specific feature genes. …”
Get full text

Predicting phage-host interaction via hyperbolic Poincaré graph embedding and large-scale protein language technique by Jie Pan, Rui Wang, Wenjing Liu, Li Wang, Zhuhong You, Yuechao Li, Zhemeng Duan, Qinghua Huang, Jie Feng, Yanmei Sun, Shiwei Wang

“…In this study, we present GE-PHI, a machine-learning-based model for predicting phage-host interactions (PHIs) by integrating knowledge graph embedding algorithm with a large-scale protein language model. …”
Get full text

Aryana-bs: context-aware alignment of bisulfite-sequencing reads by Hassan Nikaein, Ali Sharifi-Zarchi, Afsoon Afzal, Saeedeh Ezzati, Farzane Rasti, Hamidreza Chitsaz, Govindarajan Kunde-Ramamoorthy

“…While the Expectation-Maximization (EM) algorithm provides only modest initial improvements, it establishes a valuable framework for future refinement and potential enhancements in sensitive applications.…”
Get full text

Development of a postoperative recurrence prediction model for stage Ⅰ non-small cell lung cancer patients using multimodal data based on machine learning by ZHANG Di, WU Yi, XU Yu

“…A combined model was further constructed by integrating both feature sets, and model performance was compared to identify the optimal predictive model.Results‍　‍This study screened the features from non-contrast CT images and ultimately selected 7 radiomic features for constructing radiomic model. …”
Get full text

Development and validation of an ensemble learning risk model for sepsis after abdominal surgery by Xin Shu, Yujie Li, Yiziting Zhu, Zhiyong Yang, Xiang Liu, Xiaoyan Hu, Chunyong Yang, Lei Zhao, Tao Zhu, Yuwen Chen, Bin Yi

“…After feature selection, the ensemble learning model constructed by integrating k-Nearest Neighbor (KNN) and Support Vector Machine (SVM) yielded the ROC AUC of 0.892 (0.841–0.944) and accuracy of 85.0% on the test data, and the ROC AUC of 0.782 (0.727–0.838) and accuracy of 68.1% on the validation data, which performed best. …”
Get full text

A seismic random noise suppression method based on CNN-Mamba by Xiujuan WEI, Xingye LIU, Huailai ZHOU

“…However, these models face challenges such as slow computation, high resource consumption, and limited applications.Objective and Methods To address these issues, this study proposed a CMUNet seismic random noise suppression network that integrates CNN and Mamba. Based on the 2D-selective-scan (SS2D) mechanism, which can traverse the input data along horizontal and vertical directions, a global dynamic system was constructed using state-space equations. …”
Get full text

Development and validation of a decision tree model for prediction of insomnia risk among ischemic stroke convalescence patients by Xuefeng Sun, Zilin Wang, Yuqing Song, Deyu Cong, Shu Sun, Xinye Zhang, Ye Zhang, Hongshi Zhang

“…Currently, few studies have established insomnia risk prediction models. Objectives To construct a decision tree model for insomnia risk among ISC patients based on the classification and regression tree algorithm. …”
Get full text

An oral microbiota-based deep neural network model for risk stratification and prognosis prediction in gastric cancer by Xue-Feng Gao, Can-Gui Zhang, Kun Huang, Xiao-Lin Zhao, Ying-Qiao Liu, Zi-Kai Wang, Rong-Rong Ren, Geng-Hui Mai, Ke-Ren Yang, Ye Chen

Get full text

Simulation of extreme flood events for risk assessment for flood control of a reservoir-lake-river system under spatially dependent uncertainties by Huili Wang, Bin Xu, Jianyun Zhang, Guoqing Wang, Ping-an Zhong, Xinman Qin, Xuesong Yang, Ran Mo, Jinshu Li, William W.-G. Yeh

“…Scenario trees are constructed using the Neural Gas Algorithm to generate the representative extreme flood scenarios. …”
Get full text

Intelligent Song Recognition via a Hollow‐Microstructure‐Based, Ultrasensitive Artificial Eardrum by Shaopeng Li, Jiangtao Tian, Ke Li, Kemeng Xu, Jiaqi Zhang, Tingting Chen, Yang Li, Hongbo Wang, Qiye Wu, Jinchun Xie, Yongjun Men, Weiping Liu, Xiaodan Zhang, Wenhan Cao, Zhongjie Huang

“…This strategy employs novel geometric engineering of sensing units in the soft microstructure array (to significantly reduce effective modulus) along with complex song recognition exploration leveraging machine learning algorithms. Unprecedented pressure sensitivity (6.9 × 103 kPa−1) is demonstrated in a sensor with a hollow pyramid architecture with porous slants. …”
Get full text