Patterns of childhood trauma co-occurrence and its predictivity for suicidality: A machine learning approach by Wenbang Niu, Yi Feng, Shicun Xu, Xin Cui, Zhihao Ma, Yuanyuan Wang

Get full text

Method of tail beam posture prediction of top coal caving hydraulic support based on LSTM by Yupeng YAO, Jinglin ZHANG, Wu XIONG

Get full text

Gas concentration prediction in photoacoustic spectroscopy using PSO-EAP-CNN to address correlation degradation by Zhanshang Su, Pengpeng Wang, Zhengzhuo Li, Yawen Li, Tianxiang Zhao, Yujie Duan, Fupeng Wang, Cunguang Zhu

Get full text

Ultrasound combined with serological markers for predicting neonatal necrotizing enterocolitis: a machine learning approach by Yi Yang, Shoulan Zhou, Xiaomin Liu, Yanhong Zhang, Liping Lin, Chenhan Zheng, Xiaohong Zhong

Get full text

ALSTNet: Autoencoder fused long‐ and short‐term time‐series network for the prediction of tunnel structure by Bowen Du, Haohan Liang, Yuhang Wang, Junchen Ye, Xuyan Tan, Weizhong Chen

Get full text

Integrating artificial intelligence with network evolution theory for community behavior prediction in dynamic complex systems by Yongyan Zhao, Jian Li

Get full text

Short-term Wind Speed Prediction Based on Wavelet Packet Decomposition and BP Neural Network by WANG Ning, LUO Rubin, LIAO Jun, LI Jun, JIANG Yi, YANG Zechuan, YUAN Junjie

Get full text

HSoMLSDP: A Hybrid Swarm-Optimized Machine Learning Framework for Software Defect Prediction by Madhusmita Das, Biju R. Mohan, Ram Mohana Reddy Guddeti

Get full text

Prediction of Flexural Ultimate Capacity for Reinforced UHPC Beams Using Ensemble Learning and SHAP Method by Zhe Zhang, Xuemei Zhou, Ping Zhu, Zhaochao Li, Yichuan Wang

Get full text

An artificial intelligence platform for predicting postoperative complications in metastatic spinal surgery: development and validation study by Weihao Jiang, Juan Zhang, Weiqing Shi, Xuyong Cao, Xiongwei Zhao, Bin Zhang, Haikuan Yu, Shengjie Wang, Yong Qin, Mingxing Lei, Yuncen Cao, Boyu Zhu, Yaosheng Liu

“…These variables were thus incorporated as key features in all the predictive models. Among the six machine learning models, the eXGBM model demonstrated the highest prediction accuracy, with an area under the curve (AUC) of 0.924 (95% CI: 0.884–0.965), outperforming the RF model (AUC = 0.892, 95% CI: 0.846–0.938) and the KNN model (AUC = 0.869, 95% CI: 0.818–0.920). …”
Get full text

Multimodal MRI radiomics based on habitat subregions of the tumor microenvironment for predicting risk stratification in glioblastoma. by Han Wang

Get full text

Machine-learning approach to atrial fibrillation prediction among individuals without prior cardiovascular diseases by Niklas Hammar, Javier Louro, Karin Modig, Shunsuke Murata, Mozhu Ding

Get full text

Value of multi-modal MRI in predicting the effect of high-intensity focused ultrasound for uterine fibroids by Si-Qi Tao, Li-Ye Shi, Xiao-Shan Chai, Xiao-Rui Yuan, Shi-Xiong Tang, Jun Zhang, Du-Jun Bian, Chun Fu

Get full text

A nomogram for predicting postpartum post-traumatic stress disorder: a prospective cohort study by Xiaoting Wang, Jiaxin Ren, Linping Kang, Jing Lu, Hongxia Wang

Get full text

Comparative Study on Total Organic Carbon Content Logging Prediction Method Based on Machine Learning by TANG Shengshou, YANG Bin, JIN Jiulong, LIU Hongrui, DAI Xingyu, PU Jincheng

Get full text

Measurement-Based Prediction of mmWave Channel Parameters Using Deep Learning and Point Cloud by Hang Mi, Bo Ai, Ruisi He, Anuraag Bodi, Raied Caromi, Jian Wang, Jelena Senic, Camillo Gentile, Yang Miao

Get full text

AlzhCPI: A knowledge base for predicting chemical-protein interactions towards Alzheimer's disease. by Jiansong Fang, Ling Wang, Yecheng Li, Wenwen Lian, Xiaocong Pang, Hong Wang, Dongsheng Yuan, Qi Wang, Ai-Lin Liu, Guan-Hua Du

“…In this investigation, we aimed to apply the mt-QSAR method to enlarge the model library to predict CPI towards AD. Another 104 binary classifiers were further constructed to predict the CPI for 26 preclinical AD targets based on the naive Bayesian (NB) and recursive partitioning (RP) algorithms. …”
Get full text

THGB: predicting ligand-receptor interactions by combining tree boosting and histogram-based gradient boosting by Liqian Zhou, Jiao Song, Zejun Li, Yingxi Hu, Wenyan Guo

Get full text

TraitBertGCN: Personality Trait Prediction Using BertGCN with Data Fusion Technique by Muhammad Waqas, Fengli Zhang, Asif Ali Laghari, Ahmad Almadhor, Filip Petrinec, Asif Iqbal, Mian Muhammad Yasir Khalil

Get full text

An evolutionary game theory-based machine learning framework for predicting mandatory lane change decision by Sixuan Xu, Mengyun Li, Wei Zhou, Jiyang Zhang, Chen Wang

Get full text