Fibre tracing in biomedical images: An objective comparison between seven algorithms. by Youssef Arafat, Cristina Cuesta-Apausa, Esther Castellano, Constantino Carlos Reyes-Aldasoro

“…To compare the algorithms, four biomedical data sets with vastly distinctive characteristics were selected. …”
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Application of machine learning assisted multi-variate UV spectrophotometric models augmented by kennard stone clustering algorithm for quantifying recently approved nasal spray co... by Ahmed Emad F. Abbas, Mohammed Gamal, Ibrahim A. Naguib, Michael K. Halim, Basmat Amal M. Said, Mohammed M. Ghoneim, Mohmeed M. A. Mansour, Yomna A. Salem

“…The key innovation lies in the strategic implementation of the Kennard-Stone Clustering Algorithm to create a robust validation set of thirteen mixtures, resolving the limitations of reported chemometric methods’ random data splitting. …”
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Advancing Marine Surveillance: A Hybrid Approach of Physics Infused Neural Network for Enhanced Vessel Tracking Using Automatic Identification System Data by Tasmiah Haque, Md Asif Bin Syed, Srinjoy Das, Imtiaz Ahmed

“…Recognizing the strengths and limitations of the LSTM model, we propose a hybrid machine-learning algorithm that integrates LSTM with a physics-based model. …”
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Satellite Image Classification Using a Hybrid Manta Ray Foraging Optimization Neural Network by Amit Kumar Rai, Nirupama Mandal, Krishna Kant Singh, Ivan Izonin

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Identification of hypertension gene expression biomarkers based on the DeepGCFS algorithm. by Zongjin Li, Liqin Tian, Libing Bai, Zeyu Jia, Xiaoming Wu, Changxin Song

“…The algorithm then uses hybrid clustering methods for gene module detection. …”
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Advances in ECG and PCG-based cardiovascular disease classification: a review of deep learning and machine learning methods by Asmaa Ameen, Ibrahim Eldesouky Fattoh, Tarek Abd El-Hafeez, Kareem Ahmed

“…This work compares and reports the classification, machine learning, and deep learning algorithms that predict cardiovascular illnesses. …”
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Learning Analytics in a Non-Linear Virtual Course by Jhon Mercado, Carlos Mendoza-Cardenas, Luis Fletscher, Natalia Gaviria-Gomez

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Developing personalized algorithms for sensing mental health symptoms in daily life by Adela C. Timmons, Abdullah Aman Tutul, Kleanthis Avramidis, Jacqueline B. Duong, Kayla E. Carta, Sierra N. Walters, Grace A. Jumonville, Alyssa S. Carrasco, Gabrielle F. Freitag, Daniela N. Romero, Matthew W. Ahle, Jonathan S. Comer, Shrikanth S. Narayanan, Ishita P. Khurd, Theodora Chaspari

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Link Prediction in Social Networks Using the HTOA by Foad Asef, Vahid Majidnezhad, Mohammad-Reza Feizi-Derakhshi

“…Social networks are complex and dynamic data structures whose analysis holds significant importance. …”
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Intelligent Classification Method for Rail Defects in Magnetic Flux Leakage Testing Based on Feature Selection and Parameter Optimization by Kailun Ji, Ping Wang, Yinliang Jia

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Multimodal approaches and AI-driven innovations in dementia diagnosis: a systematic review by Revati M. Wahul, Sarita Ambadekar, Deepesh M. Dhanvijay, Mrinai M. Dhanvijay, Manisha A. Dudhedia, Varsha Gaikwad, Bhavana Kanawade, J. R. Pansare, Balaji Bodkhe, S. H. Gawande

“…This survey will compare the study’s algorithms or frameworks on sensitivity, specificity, interpretability, computational efficiency, and clinical transnationality concerning early detection and monitoring progression. …”
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Data Mining Classification Techniques for Diabetes Prediction by Hindreen Rashid Abdulqadir, Adnan Mohsin Abdulazeez, Dilovan Assad Zebari

“…Many analyses include multiple Machine Learning algorithms for various disease assessments and predictions to improve overall issues. …”
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Technological advances and the use of IoT in monitoring Diaphorina citri in citrus cultivation by Eduardo Goiano da Silva, Franciely da Silva Ponce, Silvia Graciele Hulse de Souza

“…These technological advances, combined with biological strategies and traditional methods such as insecticides and physical traps, create a multifaceted approach to D. citri management. Integrating data from satellite images, field sensors, and machine learning algorithms makes developing more comprehensive and predictive monitoring of agricultural conditions possible. …”
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Adaptive Anomaly Detection Framework Model Objects in Cyberspace by Hasan Alkahtani, Theyazn H. H. Aldhyani, Mohammed Al-Yaari

“…In particular, an adaptive anomaly detection framework model was developed using deep and machine learning algorithms to manage automatically-configured application-level firewalls. …”
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Domain Adaptation for Satellite-Borne Multispectral Cloud Detection by Andrew Du, Anh-Dzung Doan, Yee Wei Law, Tat-Jun Chin

“…The advent of satellite-borne machine learning hardware accelerators has enabled the onboard processing of payload data using machine learning techniques such as convolutional neural networks (CNNs). …”
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Integrated Intelligent System for Rail Flaw Detection Vehicle by Xiangyang ZHANG, Jiangping LUO

“…After verification and comparison, on the premise that the average false alarm rate of injury was basically the same, the average artificial damage detection rate of the system using the deep learning algorithm was increased by more than 4% compared with the existing system; the synchronization error between the systems was within 1m, and the positioning accuracy of the actual review of the injury was within 3 m.…”
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Access and benefit sharing biological materials for machines: Artificial intelligence, machine learning and deep learning by Charles Lawson, Elizabeth Englezos, Michelle Rourke

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Domain Adaptation for Pedestrian Detection Based on Prediction Consistency by Yu Li-ping, Tang Huan-ling, An Zhi-yong

“…Experimental results show that our approach can improve the detection rate, especially with the insufficient labeled data in target scene.…”
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Automated detection of complex zebrafish seizure behavior at scale by Paige Whyte-Fagundes, John Efromson, Anjelica Vance, Samuel Carpenter, Aurélien Bègue, Aloe Carroll, Thomas Jedidiah Jenks Doman, Mark Harfouche, Scott C. Baraban

“…Here, we employed a high-resolution multi-camera array microscope with high-speed video acquisition and custom supervised machine learning (ML) for automated detection of larval zebrafish between 3- and 7-days post-fertilization (dpf). …”
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Naive Bayes Analysis for Nutritional Fulfillment Prediction in Children by Satrio Agung Wicaksono, Satrio Hadi Wijoyo, Fatmawati Fatmawati, Tri Afirianto, Diva Kurnianingtyas, Mochammad Chandra Saputra

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