Prediction of Shield Tunneling Attitude Based on WM-CTA Method by GAO Su, CHEN Cheng

“…The Convolutional Neural Network (CNN) integrated with a channel-wise attention mechanism explored parameter weight differences and extracted local data features. …”
Get full text

Machine learning-based model for CD4+ conventional T cell genes to predict survival and immune responses in colorectal cancer by Zijing Wang, Zhanyuan Sun, Hengyi Lv, Wenjun Wu, Hai Li, Tao Jiang

“…These biomarkers may enhance therapeutic approaches and, in turn, elevate the clinical outcomes for patients with CRC by facilitating an integrated treatment strategy.…”
Get full text

Explainable Ensemble Learning Model for Residual Strength Forecasting of Defective Pipelines by Hongbo Liu, Xiangzhao Meng

“…Traditional machine learning algorithms often fail to comprehensively account for the correlative factors influencing the residual strength of defective pipelines, exhibit limited capability in extracting nonlinear features from data, and suffer from insufficient predictive accuracy. …”
Get full text

Inertial measurement unit technology for gait detection: a comprehensive evaluation of gait traits in two Italian horse breeds by Vittoria Asti, Michela Ablondi, Arnaud Molle, Andrea Zanotti, Matteo Vasini, Alberto Sabbioni

“…Overall, the GBM model exhibits the highest accuracy and the lowest error. In conclusion, integrating IMU technology into horse performance evaluation offers valuable insights, with implications for breeding and training.…”
Get full text

Implementasi Algoritma AES 256 CBC, BASE 64, Dan SHA 256 dalam Pengamanan dan Validasi Data Ujian Online by Ferzha Putra Utama, Gusman Wijaya, Ruvita Faurina, Arie Vatresia

“…One solution for maintaining the integrity of online-based exam results is to encrypt exam data with cryptographic methods. …”
Get full text

Identification and analysis of the endoplasmic reticulum stress hub genes in sepsis-associated ARDS by Ling Gao, Tingting Liu, Xiaoyan Li

“…The aim of this study was to identify and analyze hub genes related to ERS in sepsis-associated ARDS using bioinformatics and machine learning algorithms, which may serve as diagnostic markers and therapeutic targets. …”
Get full text

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. …”
Get full text

Machine learning with the body roundness index and associated indicators: a new approach to predicting metabolic syndrome by Yaxuan He, Zekai Chen, Zhaohui Tang, Yuexiang Qin, Fang Wang

“…Objective To develop a non-invasive prediction model for MetS by integrating body roundness index (BRI), gender, age, height, and waist circumference with machine learning algorithms, and to validate its generalizability across different ethnic groups. …”
Get full text

USE OF METHODOLOGICAL TASKS IN PROFESSIONAL TRAINING OF FUTURE TEACHERS OF INFORMATICS by Nataliia S. Pavlova

“…It is established that the process of solving methodological tasks cannot be fully algorithmized in the form of a clear sequence of actions of all participants in the educational process, and, therefore, it must contain standard professional actions of teachers, elements of creative decisions, based on awareness of the value of knowledge and experience which are reached in these conditions. …”
Get full text

Computational analysis of reproducibility and image quality of 2011 and 2017 models of Heidelberg Spectralis SD-OCT machines by Kyoung A Viola Lee, Corey Tesdahl, Keith Zimmerman, Kimberly Jun, Sabrina Khalil, Alexander Shahin, Abdullah Abou-Samra, Ramesh Ayyala, Radouil Tzekov

“…Methods and testing: TRT measurements were performed using the Posterior Pole Algorithm (PPA) and Early Treatment Diabetic Retinopathy Study (ETDRS) grid protocols. …”
Get full text

Inflammation Biomarker-Driven Vertical Visualization Model for Predicting Long-Term Prognosis in Unstable Angina Pectoris Patients with Angiographically Intermediate Coronary Lesio... by Zhou B, Tan W, Duan S, Wang Y, Bian F, Zhao P, Wang J, Yao Z, Li H, Hu X, Wang J, Liu J

“…In the training cohort, the area under the curve values for the nomogram at 24, 32, and 40 months were 0.669, 0.707, and 0.718, respectively, while those in the validation cohort were 0.613, 0.612 and 0.630, respectively. …”
Get full text

Spatial analysis of air pollutant exposure and its association with metabolic diseases using machine learning by Jingjing Liu, Chang Liu, Zhangdaihong Liu, Yibin Zhou, Xiaoguang Li, Yang Yang

“…This study introduces a novel machine learning (ML) pipeline, an Algorithm for Spatial Relationships Analysis between Exposome and Metabolic Diseases (ASEMD), to analyze spatial associations between APs and MDs at the prefecture-level city scale in China. …”
Get full text

THE DYNAMICS STUDY OF PATIENTS STATE WITH MUSCLE AND JOINT DYSFUNCTION OF TMJ, WHICH DECIDED TO COMPLETE THE TREATMENT AFTER ELIMINATION OF THEIR DISEASE SYMPTOMS ACHIEVED BY USING... by A.M. Boyan, V.I. Bessonov

“…An individual treatment plan was developed for each patient in accordance with the algorithm considered in the article using the author's modified method of percutaneous electroneurostimulation and the proposed occlusal splint structure. …”
Get full text

A risk prediction system for depression in middle-aged and older adults grounded in machine learning and visualization technology: a cohort study by Jinsong Du, Jinsong Du, Jinsong Du, Xinru Tao, Le Zhu, Wenhao Qi, Xiaoqiang Min, Xiaoqiang Min, Hongyan Deng, Shujie Wei, Xiaoyan Zhang, Xiao Chang

“…The developed risk prediction system can output the probability of users developing depressive symptoms or depression within five years and provide explanations for the prediction results, improving user accessibility and interpretability.DiscussionRooted in China's national longitudinal cohort, this platform integrates machine learning analytics with interactive visualization, with web deployment enhancing its clinical translational value. …”
Get full text

Determining time since deposition of latent fingerprints on forensic adhesive tape using ultrafast DESI-MS and machine learning by Nora Rajs, Yinon Harush-Brosh, Ron Raisch, Ravit Yakobi Arancibia, Amani Zoabi, Guy Nevet Golan, Moshe Shpitzen, Sarena Wiesner, Michal Levin-Elad, Tommy Kaplan, Katherine Margulis

“…Data analysis using the XGBoost and SMOTE algorithms achieved a correlation of 0.54 (p-value < 1e−5) between TSD prediction and true TSD, achieving 83.3% accuracy in distinguishing between 0-4 days and 10–15 days old prints. …”
Get full text

Hybrid closed-loop systems for managing blood glucose levels in type 1 diabetes: a systematic review and economic modelling by Asra Asgharzadeh, Mubarak Patel, Martin Connock, Sara Damery, Iman Ghosh, Mary Jordan, Karoline Freeman, Anna Brown, Rachel Court, Sharin Baldwin, Fatai Ogunlayi, Chris Stinton, Ewen Cummins, Lena Al-Khudairy

“…The system includes a combination of real-time continuous glucose monitoring from a continuous glucose monitoring device and a control algorithm to direct insulin delivery through an insulin pump. …”
Get full text

Optimized Landing Site Selection at the Lunar South Pole: A Convolutional Neural Network Approach by Yongjiu Feng, Haoteng Li, Xiaohua Tong, Pengshuo Li, Rong Wang, Shurui Chen, Mengrong Xi, Jingbo Sun, Yuhao Wang, Huaiyu He, Chao Wang, Xiong Xu, Huan Xie, Yanmin Jin, Sicong Liu

“…Although intelligent algorithms have been increasingly investigated for this purpose, the application of deep learning techniques in landing site selection remains unexplored. …”
Get full text

Identifying emphysema risk using brominated flame retardants exposure: a machine learning predictive model based on the SHAP methodology by Qihang Xie, Haoran Qu, Jianfeng Li, Rui Zeng, Wenhao Li, Rui Ouyang, Chengxiang Zhang, Siyu Xie, Siyu Xie, Ming Du

“…Eight machine learning algorithms, including lightGBM, MLP, DT, KNN, RF, SVM, Enet, and XGBoost, were applied to build and evaluate the model. …”
Get full text

Large-area urban TomoSAR method with limited a priori knowledge and a complex deep learning model by Haoxuan Duan, Yuzhou Liu, Hong Zhang, Peifeng Ma, Zhongqi Shi, Zihuan Guo, Yixian Tang, Fan Wu, Chao Wang

“…To address the above issues, this study proposes a novel large-area urban TomoSAR method integrating limited a priori knowledge constraints with a complex-valued (CV) deep learning model. …”
Get full text

Using composable NFTs and blockchain for the creation of EV battery digital passports with sustainability and traceability features by Haya R. Hasan, Khaled Salah, Ahmad Mayyas, Ahmad Musamih, Ibrar Yaqoob, Mohammed Omar, Raja Jayaraman

“…We present a system architecture, smart contracts, and supporting algorithms are presented, with testing and validation in a simulated environment. …”
Get full text