Predicting grade II-IV bone marrow suppression in patients with cervical cancer based on radiomics and dosiomics by Yanchun Tang, Yanchun Tang, Yaru Pang, Jingyi Tang, Jingyi Tang, Xinchen Sun, Xinchen Sun, Peipei Wang, Jinkai Li

“…The radiomic features and dosiomic features were extracted from the pelvic bone marrow (PBM) of planning CT images and radiotherapy planning documents, and the least absolute shrinkage and selection operator (LASSO) algorithm was employed to identify the best predictive characteristics. …”
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An Underground Goaf Locating Framework Based on D-InSAR with Three Different Prior Geological Information Conditions by Kewei Zhang, Yunjia Wang, Feng Zhao, Zhanguo Ma, Guangqian Zou, Teng Wang, Nianbin Zhang, Wenqi Huo, Xinpeng Diao, Dawei Zhou, Zhongwei Shen

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Groundwater pollution risk assessment in typical coal-related industry agglomeration area by Lai ZHOU, Yanzhuo LIU, Zenggang QI, Lei WANG, Lei MENG, Qiyan FENG, Yanqing RONG

“…At the same time, combined with the water quality level of groundwater sampling points in the study area, the Random Forest (RF) classification algorithm was utilized to construct the groundwater pollution risk classification prediction method, and the evaluation results were compared with those of the superposition index method. …”
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Development of an interpretable model for foot soft tissue stiffness based on gait plantar pressure analysis by Xiaotian Bai, Xiao Hou, Dazhi Lv, Dazhi Lv, Jialin Wei, Jialin Wei, Yiling Song, Zhengyan Tang, Hongfeng Huo, Hongfeng Huo, Jingmin Liu

“…A backpropagation neural network, optimized by integrating particle swarm optimization and genetic algorithm, was constructed to predict foot soft tissue stiffness using plantar pressure data collected during walking. …”
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Development of a machine learning-based predictive risk model combining fatty acid metabolism and ferroptosis for immunotherapy response and prognosis in prostate cancer by Zhenwei Wang, Zhihong Dai, Yuren Gao, Zhongxiang Zhao, Zhen Li, Liang Wang, Xiang Gao, Qiuqiu Qiu, Xiaofu Qiu, Zhiyu Liu

“…Abstract Prostate cancer (PCa) remains a leading cause of cancer-related mortality, necessitating robust prognostic models and personalized therapeutic strategies. This study integrated bulk RNA sequencing, single-cell RNA sequencing (scRNA-seq), and spatial transcriptomics to construct a prognostic model based on genes shared between ferroptosis and fatty acid metabolism (FAM). …”
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Building radiomics models based on ACR TI-RADS combining clinical features for discriminating benign and malignant thyroid nodules by Xingxing Chen, Xingxing Chen, Lili Zhang, Bin Chen, Jiajia Lu

“…A total of 107 radiomics features were extracted from the US images, and the radiomics score (Rad-score) was constructed using the Least Absolute Shrinkage and Selection Operator (LASSO) algorithm. …”
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Automatic segmentation model and machine learning model grounded in ultrasound radiomics for distinguishing between low malignant risk and intermediate-high malignant risk of adnex... by Lu Liu, Wenjun Cai, Feibo Zheng, Hongyan Tian, Yanping Li, Ting Wang, Xiaonan Chen, Wenjing Zhu

“…The nomogram using the LightGBM algorithm reached the best AUC (0.966, 95% CI: 0.927–1.000). …”
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Diagnostic Value of Glycosylated Extracellular Vesicle microRNAs in Gastric Cancer by Wang S, Ma C, Ren Z, Zhang Y, Hao K, Liu C, Xu L, He S, Zhang J

“…The signatures were screened in a discovery cohort of GC patients (n=55) and non-disease controls (n=46) using an integrated process, including high-throughput sequencing technology, screening using a complete bioinformatics algorithm, validation using RT-qPCR, and evaluation by constructing a diagnostic model. …”
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Investigation and application of data balancing and combined discriminant model in rock burst severity prediction by Shaohong Yan, Runze Liu, Yanbo Zhang, Xulong Yao, Yueqi Yang, Qi Wang, Bin Guo, Shuai Wang

“…To accurately predict rock burst disasters and mitigate or eliminate related threats, this paper proposes a composite prediction model that integrates Density-Based Nonlinear Resampling (DBNR)-Tomek Link data balancing algorithms with Bayesian Optimization (BO)-Multilayer Perceptron (MLP)-Random Forest (RF). …”
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Development and Validation of a Radiomics Nomogram Based on Magnetic Resonance Imaging and Clinicoradiological Factors to Predict HCC TACE Refractoriness by Dong Y, Hu J, Meng X, Yang B, Peng C, Zhao W

“…Relevant indices of TACE refractoriness were selected. ML algorithms, including a support vector machine, random forest, logistic regression and adaptive boosting, were used to construct the radiomics, clinical prediction, and combined models. …”
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Aberrant fragmentomic features of circulating cell-free mitochondrial DNA enable early detection and prognosis prediction of hepatocellular carcinoma by Yang Liu, Fan Peng, Siyuan Wang, Huanmin Jiao, Kaixiang Zhou, Wenjie Guo, Shanshan Guo, Miao Dang, Huanqin Zhang, Weizheng Zhou, Xu Guo, Jinliang Xing

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Immunophenotype-guided interpretable radiomics model for predicting neoadjuvant anti-PD-1 response in stage III–IV d-MMR/MSI-H colorectal cancer by Xuan Zhang, Zhenhui Li, Yiwen Zhang, Yanli Li, Xi Zhong, Wenjing Jiang, Xiaobo Chen, Zaiyi Liu, Liebin Huang, Caixia Zhang, Lizhu Liu, Ruimin You, Xiaoping Yi

“…Eventually, an interpretable immunotherapy response prediction model was developed by integrating a decision tree algorithm with SHapley Additive exPlanations (SHAP) analysis.Results Two immunophenotypes (immune-hot and immune-cold) were identified, compared with the immune-cold, the former exhibited more abundant RNA-based immune cell infiltration and higher densities of CD3 and CD8 T cells in both the core tumor and invasive margin areas. …”
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A Novel 14-Gene Panel Associated With Efferocytosis for Predicting Pancreatic Cancer Prognosis Through Bulk and Single-Cell Databases by Yaheng Wu, Lin Zhao, Dingyan Yi, Zhihua Tian, Bin Dong, Chunxiang Ye, Jingtao Liu, Huachong Ma, Wei Zhao

“…Additionally, random survival forest (RSF) algorithms facilitated the identification of a key panel of genes, designated “LEAP” genes, including LGALS3, EREG, ASPH, and PLS3; three of which genes (ASPH, LGALS3, and EREG) were identified as key factors influencing the behaviors of PDAC tumors, tumor-associated stroma, and macrophages. …”
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Identifying low-risk breast cancer patients for axillary biopsy exemption: a multimodal preoperative predictive model by Jiaqi Zhang, Jianing Zhang, Zhihao Liu, Yudong Zhou, Xiaoni Zhao, Yalong Wang, Danni Li, Jinsui Du, Chenglong Duan, Yi Pan, Qi Tian, Feiqian Wang, Ke Wang, Lizhe Zhu, Bin Wang

“…Abstract Background As the most prevalent female malignancy worldwide, breast cancer frequently involves axillary lymph node metastasis (ALNM), which critically affects therapeutic algorithms. Current guidelines mandate preoperative ultrasound-guided axillary biopsy for suspicious lymph nodes, potentially exposing some low-risk patients with negative results to invasive risks. …”
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Urban Tree Canopy Mapping and Analysis Using Iterative Annotation Method and Deep Learning: A Case Study in Beijing by Yulong Ding, Ximin Cui, Zhengchao Chen, Zeqing Wang, Debao Yuan, Xiang Meng, Xuan Yang, Yue Xu, Xiangyu Tian

“…To address this, we propose an iterative method based on intersection over union (IoU), integrating multiscale segmentation and nearest-neighbor classification algorithms. …”
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Development of an explainable prediction model for portal vein system thrombosis post-splenectomy in patients with cirrhosis by Caixia Dong, Guodong Li, Rui Zhou, Dou Qu, Duwei Dai, Junxia Zhao, Lingbo An, Xiaojie Song, Jiazhen Zhu, Zong Fang Li

“…The predictive model integrated 37 candidate predictors based on accessible clinical data, including demographic characteristics, disease features, imaging results, laboratory values, perioperative details and postoperative prophylactic therapies, and finally, eight predictors were selected for model construction. …”
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HETDEX-LOFAR Spectroscopic Redshift Catalog by Maya H. Debski, Gregory R. Zeimann, Gary J. Hill, Donald P. Schneider, Leah Morabito, Gavin Dalton, Matt J. Jarvis, Erin Mentuch Cooper, Robin Ciardullo, Eric Gawiser, Nika Jurlin

“…We combine the power of blind integral field spectroscopy from the Hobby–Eberly Telescope (HET) Dark Energy Experiment (HETDEX) with sources detected by the Low Frequency Array (LOFAR) to construct the HETDEX-LOFAR Spectroscopic Redshift Catalog. …”
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Explainable machine learning model for predicting the transarterial chemoembolization response and subtypes of hepatocellular carcinoma patients by Yunjie Zhang, Songjian Tong, Junhui Yang, Jiawei Lin, Yifan Kong, Deyu Lu, Yan Chen, Yingchao Li, Linfeng Xu, Xiuyan Kong, Guoqing Zhu, Hao Zhang, Pixu Liu, Zhijie Yu, Jinglin Xia

“…RFE method identified 10 predictors for constructing ML models. XGBoost and CatBoost outperformed other algorithms, achieving AUCs of 0.796–0.799 (internal test) and 0.785–0.791 (external validation) with balanced accuracy (76-76.8%). …”
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3D spectral CT-based fusion model predicts prognosis and postoperative adjuvant chemotherapy benefit in locally advanced rectal cancer by Shuxuan Fan, Jiaxin Liu, Xiaomeng Yang, Lisha Qi, Xiaomei Lu, Haiwei Liu, Xiaonan Cui

“…The SHapley Additive exPlanation (SHAP) algorithm was used to attribute interpretability to the optimal prediction model. …”
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MMAgentRec, a personalized multi-modal recommendation agent with large language model by Xiaochen Xiao

“…At the same time, this paper has constructed a comprehensive dataset in this field, each column contains 9004 data entries.…”
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