Deep learning-based encryption scheme for medical images using DCGAN and virtual planet domain by Manish Kumar, Aneesh Sreevallabh Chivukula, Gunjan Barua

“…Further, statistical NPCR and UACI are calculated in Tables 12 and 13, respectively. The proposed algorithm is also compared with existing algorithms, and compared values are provided in Table 15. …”
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Combining multi-parametric MRI radiomics features with tumor abnormal protein to construct a machine learning-based predictive model for prostate cancer by Chi Zhang, Zewen Wang, Peicheng Shang, Yibin Zhou, Jin Zhu, Lijun Xu, Zeyu Chen, Mengqi Yu, Yachen Zang

“…Abstract This study aims to investigate the diagnostic value of integrating multi-parametric magnetic resonance imaging (mpMRI) radiomic features with tumor abnormal protein (TAP) and clinical characteristics for diagnosing prostate cancer. …”
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A smarter approach to liquefaction risk: harnessing dynamic cone penetration test data and machine learning for safer infrastructure by Shubhendu Vikram Singh, Sufyan Ghani

“…This paper presents a novel approach for assessing liquefaction potential by integrating Dynamic Cone Penetration Test (DCPT) data with advanced machine learning (ML) techniques. …”
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The Development of Digital Twin Baby Incubators for Fault Detection and Performance Analysis by Hatice Kabaoğlu, Emine Uçar, Fecir Duran

“…The digital twin employs a hybrid model integrating Long Short-Term Memory (LSTM) and Random Forest (RF) algorithms to predict potential errors and alarms. …”
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A radiomics approach for predicting gait freezing in Parkinson’s disease based on resting-state functional magnetic resonance imaging indices: A cross-sectional study by Miaoran Guo, Hu Liu, Long Gao, Hongmei Yu, Yan Ren, Yingmei Li, Huaguang Yang, Chenghao Cao, Guoguang Fan

“…We used the least absolute shrinkage and selection operator algorithm to extract features and established feedforward neural network models based solely on resting-state functional magnetic resonance imaging indicators. …”
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Machine learning prediction model for functional prognosis of acute ischemic stroke based on MRI radiomics of white matter hyperintensities by Yayuan Xia, Linhui Li, Peipei Liu, Tianxu Zhai, Yibing Shi

“…Abstract Objective The purpose of the current study is to explore the value of a nomogram that integrates clinical factors and MRI white matter hyperintensities (WMH) radiomics features in predicting the prognosis at 90 days for patients with acute ischemic stroke (AIS). …”
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AI in Medical Questionnaires: Innovations, Diagnosis, and Implications by Xuexing Luo, Yiyuan Li, Jing Xu, Zhong Zheng, Fangtian Ying, Guanghui Huang

“…Overall, 24 AI technologies were identified, covering traditional algorithms such as random forest, support vector machine, and k-nearest neighbor, as well as deep learning models such as convolutional neural networks, Bidirectional Encoder Representations From Transformers, and ChatGPT. …”
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Transceiver Design for Full-Duplex UAV Based Zero-Padded OFDM System With Physical Layer Security by Joarder Jafor Sadique, Shaikh Enayet Ullah, Md. Rabiul Islam, Raad Raad, Abbas Z. Kouzani, M. A. Parvez Mahmud

“…In this proposed system, intertwining logistic map (ILM)-cosine transform aided encryption algorithm combined with artificial noise enhancing physical layer security (PLS) is introduced. …”
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Surface Defect Detection for Small Samples of Particleboard Based on Improved Proximal Policy Optimization by Haifei Xia, Haiyan Zhou, Mingao Zhang, Qingyi Zhang, Chenlong Fan, Yutu Yang, Shuang Xi, Ying Liu

“…The proposed method is based on the proximal policy optimization (PPO) algorithm of the Actor-Critic framework, and defect detection is achieved by performing a series of scaling and translation operations on the mask. …”
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An optimized machine learning framework for predicting and interpreting corporate ESG greenwashing behavior. by Fanlong Zeng, Jintao Wang, Chaoyan Zeng

“…This paper addresses the limitations in hyperparameter optimization and interpretability of existing prediction models by introducing an optimized machine learning framework. The framework integrates an Improved Hunter-Prey Optimization (IHPO) algorithm, an eXtreme Gradient Boosting (XGBoost) model, and SHapley Additive exPlanations (SHAP) theory to predict and interpret corporate ESG greenwashing behavior. …”
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Identification and validation of endoplasmic reticulum stress-related diagnostic biomarkers for type 1 diabetic cardiomyopathy based on bioinformatics and machine learning by Qiao Tang, Yanwei Ji, Zhongyuan Xia, Yuxi Zhang, Chong Dong, Chong Dong, Qian Sun, Shaoqing Lei

“…Limma package analyzed differentially expressed genes (DEGs) in the DC and control groups, and then integrated with ERGs to identify ERS-related DEGs (ERDEGs). …”
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An explainable GeoAI approach for the multimodal analysis of urban human dynamics: a case study for the COVID-19 pandemic in Rio de Janeiro by David Hanny, Dorian Arifi, Steffen Knoblauch, Bernd Resch, Sven Lautenbach, Alexander Zipf, Antonio Augusto de Aragão Rocha

“…Our findings demonstrate the value of integrating localised multimodal features in city-level epidemiological analysis and offer a method for effectively identifying them. …”
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Identification and validation of prognostic biomarkers in ccRCC: immune-stromal score and survival prediction by Fang Lyu, Yuxin Zhong, Qingliu He, Wen Xiao, Xiaoping Zhang

“…Abstract Background The tumor microenvironment (TME) is integral to tumor progression. However, its prognostic implications and underlying mechanisms in clear cell renal cell carcinoma (ccRCC) are not yet fully elucidated. …”
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Machine learning model for differentiating malignant from benign thyroid nodules based on the thyroid function data by Quan Zhou, Lihua Zhang, Nan Xiang, Lele Zhang, Fuqiang Ma, Fengchang Yu, Shenhui Lv, Zhilin Lu, He-Rong Mao

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Student Engagement Recognition: Comprehensive Analysis Through EEG and Verification by Image Traits Using Deep Learning Techniques by Ajitha Sukumaran, Arun Manoharan

“…In this paper, we propose an engagement recognition system that detects student engagement using EEG signals by integrating levels of valence and arousal with the Russel 2D circumplex model using deep learning algorithm. …”
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Research on automatic identification method for pipeline girth weld defects based on X-ray images and sparse representation by Shaohui JIA, Yaping LI, Weixin GAO, Yunchao PENG, Xinjian ZHANG, Yuxia WANG

“…To maximize the library of image features within the dictionary matrix, an optimal model was established for X-ray SDR images of welds based on orthogonal optimization, along with a dictionary matrix solving algorithm featuring orthogonal optimization. Results The established model and algorithm led to the development of pipeline girth weld defect detection software integrating sparse representation and X-ray image detection technology. …”
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Accelerated discovery of high-density pyrazole-based energetic materials using machine learning and density functional theory by Muhammad Tukur Ibrahim, Muktar Musa Ibrahim, Adamu Uzairu, Gideon Adamu Shallangwa, Sani Uba

“…The results indicate the best predictive performance was afforded by random forest algorithm with Pearson’s correlation coefficient (RTR), Cross-validation coefficient (QCV) and External validation coefficient (QEX) values of 0.9273, 0.7294 and 0.7184 respectively. …”
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Identifying Molecular Properties of Ataxin-2 Inhibitors for Spinocerebellar Ataxia Type 2 Utilizing High-Throughput Screening and Machine Learning by Smita Sahay, Jingran Wen, Daniel R. Scoles, Anton Simeonov, Thomas S. Dexheimer, Ajit Jadhav, Stephen C. Kales, Hongmao Sun, Stefan M. Pulst, Julio C. Facelli, David E. Jones

“…For each model, the maximum response assay values were analyzed, and E values and total rank values were applied. …”
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Improving total bone marrow and lymphoid irradiation: feasibility of intensity-modulated proton therapy (IMPT) and dosimetric comparison with helical tomotherapy (HT) by Dayananda Shamurailatpam Sharma, Arjunan Manikandan, Gaganpreet Singh, Sanjib Gayen, Sham Sundar, Aishwarya G, Rangasamy S, Mahammood Suhail, Rajesh S, Ganapathy Krishnan, Revathi Raj, Srinivas Chilukuri, Jose Easow, Rakesh Jalali

“…In comparison to HT, IMPT plans reduced mean integral dosage to normal tissue by 38%, OARs by a factor of 1.32 to 3.94, and V107% by 520.97 cc for sub-PTVs and 1166 cc for upper-body PTVs. …”
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A novel fusion positioning navigation system for greenhouse strawberry spraying robot using LiDAR and ultrasonic tags by Haoran Tan, Xueguan Zhao, Hao Fu, Minli Yang, Changyuan Zhai

“…To further enhance positioning accuracy and robustness, a tightly-coupled framework combining LiDAR and ultrasonic tags was designed, incorporating an improved Iterative Closest Point (ICP) method and Singular Value Decomposition (SVD) algorithm for precise registration positioning. …”
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