From intensive care monitors to cloud environments: a structured data pipeline for advanced clinical decision supportResearch in context by Sijm H. Noteboom, Eline Kho, Maria Galanty, Clara I. Sánchez, Frans C.P. ten Bookum, Denise P. Veelo, Alexander P.J. Vlaar, Björn J.P. van der Ster

“…Summary: Background: Clinical decision-making is increasingly shifting towards data-driven approaches and requires large databases to develop state-of-the-art algorithms for diagnosing, detecting and predicting diseases. …”
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Automatic titration detection method of organic matter content based on machine vision by Bingjie Zhang, Meng Li, Qing Song, Lujian Xu

“…First, by analysing the colour change characteristics during the titration process, machine learning techniques are used to classify the titration speed, and a titration experiment state recognition model is constructed to divide the titration speed into four categories and improve titration efficiency; Second, through a large number of titration experiments to collect relevant data and extract key feature parameters, an efficient titration algorithm based on histogram similarity was designed to accurately identify titration endpoints and improve detection accuracy. …”
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Green cover change detection using a modified adaptive ensemble of extreme learning machines for North-Western India by Madhu Khurana, Vikas Saxena

“…Non-availability of standard datasets and limited labeled data points makes it difficult to attain high accuracies in change detection. …”
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Detecting of a Patient's Condition From Clinical Narratives Using Natural Language Representation by Thanh-Dung Le, Rita Noumeir, Jerome Rambaud, Guillaume Sans, Philippe Jouvet

“…<italic>Methods:</italic> The methodology consisted of empirical experiments of a learning algorithm to learn the hidden interpretation and presentation of the French clinical note data. …”
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BCAST IDS: A Novel Network Intrusion Detection System for Broadcast Networks by Javier Gombao

“…A modern approach to enhancing the capabilities of NIDSs is the use of machine learning (ML) algorithms that predict attacks based on data. …”
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A federated learning-based privacy-preserving image processing framework for brain tumor detection from CT scans by Abdullah Al-Saleh, Ghanshyam G. Tejani, Shailendra Mishra, Sunil Kumar Sharma, Seyed Jalaleddin Mousavirad

“…Because traditional deep learning models store all their data together, they raise questions about privacy, complying with regulations and the different types of data used by various institutions. …”
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Outlier Detection and Removal in Multivariate Time Series for a More Robust Machine Learning–based Solar Flare Prediction by Junzhi Wen, Azim Ahmadzadeh, Manolis K. Georgoulis, Viacheslav M. Sadykov, Rafal A. Angryk

“…Although various machine learning algorithms have been employed to improve solar flare prediction, there has been limited focus on improving performance using outlier detection. …”
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Ambulance Siren Detection using Artificial Intelligence in Urban Scenarios by Muhammad Usaid, Muhammad Asif, Tabarka Rajab, Munaf Rashid, Syeda Iqra Hassan

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High Accuracy of Epileptic Seizure Detection Using Tiny Machine Learning Technology for Implantable Closed-Loop Neurostimulation Systems by Evangelia Tsakanika, Vasileios Tsoukas, Athanasios Kakarountas, Vasileios Kokkinos

“…One of its key characteristics is the ability to run machine learning algorithms without the need for high computational complexity and powerful hardware resources. …”
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Machine Learning Method Application to Detect Predisposing Factors to Open-Pit Landslides: The Sijiaying Iron Mine Case Study by Jiang Li, Zhuoying Tan, Naigen Tan, Aboubakar Siddique, Jianshu Liu, Fenglin Wang, Wantao Li

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Automated Detection of Tailing Impoundments in Multi-Sensor High-Resolution Satellite Images Through Advanced Deep Learning Architectures by Lin Qin, Wenyue Song

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Automatic Paddy Planthopper Detection and Counting Using Faster R-CNN by Siti Khairunniza-Bejo, Mohd Firdaus Ibrahim, Marsyita Hanafi, Mahirah Jahari, Fathinul Syahir Ahmad Saad, Mohammad Aufa Mhd Bookeri

“…The datasets were subjected to data augmentation and utilised to train four convolutional object detection models based on transfer learning. …”
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Advances in Federated Learning: Applications and Challenges in Smart Building Environments and Beyond by Mohamed Rafik Aymene Berkani, Ammar Chouchane, Yassine Himeur, Abdelmalik Ouamane, Sami Miniaoui, Shadi Atalla, Wathiq Mansoor, Hussain Al-Ahmad

“…Federated Learning (FL) is a transformative decentralized approach in machine learning and deep learning, offering enhanced privacy, scalability, and data security. …”
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Nondestructive detection of sweet potato leaf curl virus using 3D laser imaging combined with deep learning by Yican Yang, Nuwan K. Wijewardane, Tyler J. Slonecki, Phillip A. Wadl, Sharon A. Andreason, Jingdao Chen, Lorin Harvey

“…Therefore, there is a need to establish alternative, point-of-care techniques for SPLCV detection. The goal of this study was to investigate the potential of using 3D point cloud data and deep learning to detect SPLCV. …”
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Advanced artificial intelligence with federated learning framework for privacy-preserving cyberthreat detection in IoT-assisted sustainable smart cities by Mahmoud Ragab, Ehab Bahaudien Ashary, Bandar M. Alghamdi, Rania Aboalela, Naif Alsaadi, Louai A. Maghrabi, Khalid H. Allehaibi

“…Nevertheless, the possibility of FL regarding IoT forensics remains mostly unexplored. Deep learning (DL) focused cyberthreat detection has developed as a powerful and effective approach to identifying abnormal patterns or behaviours in the data field. …”
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DeepGenMon: A Novel Framework for Monkeypox Classification Integrating Lightweight Attention-Based Deep Learning and a Genetic Algorithm by Abdulqader M. Almars

“…However, there is still room for improvement to accurately detect and classify monkeypox cases. Furthermore, the currently proposed pre-trained deep learning models can consume extensive resources to achieve accurate detection and classification of monkeypox. …”
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Supervised Machine Learning for Real-Time Intrusion Attack Detection in Connected and Autonomous Vehicles: A Security Paradigm Shift by Ahmad Aloqaily, Emad E. Abdallah, Hiba AbuZaid, Alaa E. Abdallah, Malak Al-hassan

“…To accurately distinguish between benign and malicious messages, this study employed seven distinct supervised machine-learning algorithms for data classification. The selected algorithms encompassed Decision Trees, Random Forests, Naive Bayes, Logistic Regression, XG Boost, LightGBM, and Multi-layer Perceptrons. …”
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Enhanced Fault Detection in Satellite Attitude Control Systems Using LSTM-Based Deep Learning and Redundant Reaction Wheels by Sajad Saraygord Afshari

“…In light of this, we introduce a fault detection methodology grounded in deep learning techniques specifically designed for satellite attitude control systems. …”
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Development of a Fault-Tolerant Permanent Magnet Synchronous Motor Using a Machine-Learning Algorithm for a Predictive Maintenance Elevator by Vasileios I. Vlachou, Theoklitos S. Karakatsanis

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WGAN-DL-IDS: An Efficient Framework for Intrusion Detection System Using WGAN, Random Forest, and Deep Learning Approaches by Shehla Gul, Sobia Arshad, Sanay Muhammad Umar Saeed, Adeel Akram, Muhammad Awais Azam

“…False and disregarded alarms are a common problem for traditional IDSs in high-bandwidth and large-scale network systems. While applying learning techniques to intrusion detection, researchers are facing challenges mainly due to the imbalanced training sets and the high dimensionality of datasets, resulting from the scarcity of attack data and longer training periods, respectively. …”
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