Efficient Deep Learning-Based Cyber-Attack Detection for Internet of Medical Things Devices by Abigail Judith, G. Jaspher W. Kathrine, Salaja Silas, Andrew J

“…These attacks can lead to significant data loss or unauthorized alterations. Machine learning, particularly in cyber-attack detection systems, is crucial for identifying and classifying such attacks. …”
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Transcriptome Data Combined With Mendelian Randomization Analysis Identifies Key Genes Associated With Mitochondria and Programmed Cell Death in Intervertebral Disc Degeneration by Hongfei Nie, Xiao Hu, Jiaxiao Wang, Jia Wang, Xiaoqian Yu, Jun Li

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Smart Belay Device for Sport Climbing—An Analysis about Falling by Heiko Oppel, Michael Munz

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Artificial intelligence techniques for stability analysis in modern power systems by Jiashu Fang, Chongru Liu

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Predicting Sugar Yield From Sugarcane Using Machine Learning for Jaggery Production by Kathirvel Narayanasamy, Ilayaraja Venkatachalam

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Deep Learning Techniques in DICOM Files Classification: A Systematic Review by Mabirizi, Vicent, Kawuma, Simon, Natumanya, Deborah, Wasswa, William

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Enhanced Deep Learning for Robust Stress Classification in Sows from Facial Images by Syed U. Yunas, Ajmal Shahbaz, Emma M. Baxter, Mark F. Hansen, Melvyn L. Smith, Lyndon N. Smith

“…A facial image dataset of sows was collected at Scotland’s Rural College (SRUC) and the images were categorized into primiparous Low-Stressed (LS) and High-Stress (HS) groups based on expert behavioural assessments and cortisol level analysis. The selected deep learning models were then trained on this enriched dataset and their performance was evaluated using cross-validation on unseen data. …”
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Advancing Early Detection of Major Depressive Disorder Using Multisite Functional Magnetic Resonance Imaging Data: Comparative Analysis of AI Models by Masab Mansoor, Kashif Ansari

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Watch Your Callback: Offline Anomaly Detection Using Machine Learning in ROS 2 by Jeonghwan Kang, Kyounghwan Kim, Donghyun Kwon

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Photodiagnosis with deep learning: A GAN and autoencoder-based approach for diabetic retinopathy detection by Kerem GENCER, Gülcan GENCER, Tuğçe Horozoğlu CERAN, Aynur ER BİLİR, Mustafa DOĞAN

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Innovative Sentiment Analysis and Prediction of Stock Price Using FinBERT, GPT-4 and Logistic Regression: A Data-Driven Approach by Olamilekan Shobayo, Sidikat Adeyemi-Longe, Olusogo Popoola, Bayode Ogunleye

“…., Finaance Bidirectional Encoder representations from Transsformers (FinBERT), Generatice Pre-trained Transformer GPT-4, and Logistic Regression, for sentiment analysis and stock index prediction using financial news and the NGX All-Share Index data label. …”
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Optimal design strategy of traditional courtyard based on performance and data-driven method—A case study of Yanshen ancient town, China by Zhixin Xu, Xin Zheng, Xiangfeng Li

“…To address the insufficient integration of performance evaluation and contextual analysis in traditional architectural design, this paper proposes a design workflow that combines data-driven and performance-driven approaches, establishing a comprehensive operational pathway from typology selection and design generation to performance assessment. …”
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Large Scale Asset Detection Within Railway Scene Point Cloud Data From Mobile Laser Scanning by Bram Ton, Rick Akster

“…Additionally, this study demonstrates that transfer learning effectively reduces the labeling burden. For instance, when using 25% of the training data, the average Precision (AP) for the tension rod class improves from 9.5% without transfer learning to 70.8% with transfer learning.…”
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Multidisciplinary analysis of the prognosis and biological function of NUBPL in gastric cancer by Luqian Liu, Fengyu Zhang, Jiaye Yu, Pingping Dong, Jing Deng, Weiwei Liu, Xinlei Cao, Juanjuan Huang, Xiaoming Lin, Xiangyang Xue

“…Meanwhile, the ESTIMATE algorithm was used for immune infiltration analysis and prediction of immunotherapy response, and the Genomics of Drug Sensitivity in Cancer (GDSC) database was utilized for the drug sensitivity analysis of NUBPL. …”
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Harnessing Social Media Data to Understand Information Needs About Kidney Diseases and Emotional Experiences With Disease Management: Topic and Sentiment Analysis by Hee Jeong Hwang, Nara Kim, Jeong Yun You, Hye Ri Ryu, Seo-Young Kim, Jung Han Yoon Park, Ki Won Lee

“…A total of 124,211 posts from 10 disease-specific boards were analyzed using latent Dirichlet allocation for topic modeling and Bidirectional Encoder Representations From Transformers–based sentiment analysis. In addition, Efficiently Learning an Encoder That Classifies Token Replacements Accurately–based classification was used to further analyze posts related to disease management. …”
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Evaluating the impact of waste marble on the compressive strength of traditional concrete using machine learning by Kennedy C. Onyelowe, Viroon Kamchoom, Ahmed M. Ebid, Shadi Hanandeh, Susana Monserrat Zurita Polo, Rolando Fabián Zabala Vizuete, Rodney Orlando Santillán Murillo, Rolando Marcel Torres Castillo, Siva Avudaiappan

“…This research has focused on evaluating the impact of waste marble on the compressive strength of traditional concrete using machine learning (ML). Advanced ML techniques such as the Group Methods Data Handling Neural Network (GMDH-NN), Support Vector Regression (SVR), K-Nearest Neighbors (kNN) and Adaptive Boosting (AdaBoost) have been applied in this research work. …”
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Comprehensive analysis of single-cell and bulk RNA sequencing data reveals an EGFR signature for predicting immunotherapy response and prognosis in pan-cancer by Changchun Ye, Changchun Ye, Xiaoya Chen, Zilu Chen, Shiyuan Liu, Ranran Kong, Wenhao Lin, Minxia Zhu, Xuejun Sun, Zhengshui Xu

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Synthesizing field plot and airborne remote sensing data to enhance national forest inventory mapping in the boreal forest of Interior Alaska by Pratima Khatri-Chhetri, Hans-Erik Andersen, Bruce Cook, Sean M. Hendryx, Liz van Wagtendonk, Van R. Kane

“…In this study, we present a framework for forest type classification combining field plots and high-resolution remote sensing data using machine learning models in the boreal forest of Interior Alaska. …”
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Cascade-Based Input-Doubling Classifier for Predicting Survival in Allogeneic Bone Marrow Transplants: Small Data Case by Ivan Izonin, Roman Tkachenko, Nazarii Hovdysh, Oleh Berezsky, Kyrylo Yemets, Ivan Tsmots

“…In the field of transplantology, where medical decisions are heavily dependent on complex data analysis, the challenge of small data has become increasingly prominent. …”
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Advanced machine learning models for the prediction of ceramic tiles’ properties during the firing stage by V. Vasic, Milica, Awoyera, Paul O., Fadugba, Oladlu George, Barisic, Ivana, Nettinger Grubeša, Ivanka

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