Identification of neural outgrowth genes using genome-wide RNAi. by Katharine J Sepp, Pengyu Hong, Sofia B Lizarraga, Judy S Liu, Luis A Mejia, Christopher A Walsh, Norbert Perrimon

“…To assist in the phenotypic analysis of the large data sets, we generated image analysis algorithms that could assess the statistical significance of the mutant phenotypes. …”
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Migraine triggers, phases, and classification using machine learning models by Anusha Reddy, Ajit Reddy

“…Patients affected by these disorders are often unaware of the seriousness of their conditions, as headaches are neither fatal nor contagious. In many cases, patients with migraine are often misdiagnosed as regular headaches.MethodsIn this article, we present a study on migraine, covering known triggers, different phases, classification of migraine into different types based on clinical studies, and the use of various machine learning algorithms such as logistic regression (LR), support vector machine (SVM), random forest (RF), and artificial neural network (ANN) to learn and classify different migraine types. …”
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A Review of Stall Detection in Subsonic Axial Compressors by Kellie N. Wilson, Golam Gause Jaman, Anish Thapa, Amirthavarshini Vivekananda, Mitchell Lowe, Zachary Grima, Marco P. Schoen

“…The detection of the onset of stall, and in many cases the precursor of the onset of stall, have been of interest in the axial compressor community for many decades. …”
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Advances in Skeleton-Based Fall Detection in RGB Videos: From Handcrafted to Deep Learning Approaches by Van-Ha Hoang, Jong Weon Lee, Md. Jalil Piran, Chun-Su Park

“…To overcome these challenges, many researchers propose extracting skeleton data from RGB videos and using it for fall detection. …”
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A systematic review of ulcer detection methods in wireless capsule endoscopy by Ahmmad Musha, Rehnuma Hasnat, Abdullah Al Mamun, Md Sohag Hossain, Md Jakir Hossen, Tonmoy Ghosh

“…Background: Ulcers are one of the most prevalent disorders in the gastrointestinal (GI) tract, affecting many people worldwide. Wireless capsule endoscopy (WCE) emerges as the most non-invasive way to diagnose ulcers in the GI tract. …”
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Explainable AI supported hybrid deep learnig method for layer 2 intrusion detection by Ilhan Firat Kilincer

“…There is a large network structure behind many applications provided to users by organizations. …”
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Gravity experiments with radio pulsars by Paulo C. C. Freire, Norbert Wex

“…New telescopes, instrumentation, timing and search algorithms promise a significant improvement of the existing tests and the discovery of (qualitatively) new, more relativistic binary systems.…”
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LUNGINFORMER: A Multiclass of lung pneumonia diseases detection based on chest X-ray image using contrast enhancement and hybridization inceptionresnet and transformer by Hanafi Hanafi

“…To address the problem, many researchers have employed deep learning algorithms to develop an automated detection system for pneumonia. …”
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Artificial intelligence in automation and graphic design by Esam Ibrahim Mohammed Al-Kubisy

“… Artificial intelligence has entered many aspects of our lives, and design is by no means an exception. …”
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A Framework for Real-Time Crop Monitoring and Yield Optimisation: Improving Precision Agriculture with IoT-Driven Sensor Networks and Data Analytics by Shnain Ammar H., Mohammed G., Kumar Yalla Jeevan Nagendra

“…To solve these challenges, CM-IoT-SN combines a network of IoT-enabled sensors continuously monitoring key environmental factors such as soil moisture, temperature, and nutrient levels. Advanced algorithms then utilize the realtime data acquired to provide farmers expected insights and quick advise.CM-IoT-SNs adoption across many test locations has proved its effectiveness in producing superior decision-making in crop management by means of exact, real-time monitoring and predictive analytics. …”
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Determining optimal strategies for primary prevention of cardiovascular disease: a synopsis of an evidence synthesis study by Olalekan A Uthman, Lena Al-Khudairy, Chidozie Nduka, Rachel Court, Jodie Enderby, Seun Anjorin, Hema Mistry, G J Melendez-Torres, Sian Taylor-Phillips, Aileen Clarke

“…A machine learning study developed a parallel Convolutional Neural Network algorithm with 96.4% recall and 99.1% precision for study screening. …”
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Clinical applications of artificial intelligence and machine learning in neurocardiology: a comprehensive review by Jade Basem, Racheed Mani, Scott Sun, Kevin Gilotra, Neda Dianati-Maleki, Reza Dashti

“…In the focus of cryptogenic strokes, there is promising research elucidating likely underlying cardiac causes and thus, improved treatment options and secondary stroke prevention. While many algorithms still require a larger knowledge base or manual algorithmic training, AI/ML in neurocardiology has the potential to provide more comprehensive healthcare treatment, increase access to equitable healthcare, and improve patient outcomes. …”
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Enabling 6G Performance in the Upper Mid-Band by Transitioning From Massive to Gigantic MIMO by Emil Bjornson, Ferdi Kara, Nikolaos Kolomvakis, Alva Kosasih, Parisa Ramezani, Murat Babek Salman

“…Finally, we identify open research and standardization challenges that must be overcome to efficiently use gigantic MIMO dimensions in 6G from hardware, cost, and algorithmic perspectives.…”
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Automated design of scaffold-free DNA wireframe nanostructures by Wen Wang, Abdulmelik Mohammed, Rong Chen, Antti Elonen, Silian Chen, Mengfan Tian, Junhao Yang, Ye Xiang, Pekka Orponen, Bryan Wei

“…Unlike in the DNA origami method, scaffold-free designs are not built around a global backbone strand but are constituted entirely of short, locally intertwined oligonucleotides. This overcomes many limitations inherent in scaffolded nanostructure designs, most notably the size constraints imposed by the length of available scaffold strands, and the topological and algorithmic challenges of finding feasible scaffold-strand routings. …”
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Progress in the Clinical Application of Artificial Intelligence for Left Ventricle Analysis in Cardiac Magnetic Resonance by Yinghui Le, Chongshang Zhao, Jing An, Jiali Zhou, Dongdong Deng, Yi He

“…Most recent research has focused on segmentation of the left ventricular myocardium and blood pool. Although many algorithms have shown a level comparable to that of human experts, some problems, such as poor performance of basal and apical segmentation and false identification of myocardial structure, remain. …”
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Network intrusion detection model using wrapper based feature selection and multi head attention transformers by Muhammad Umer, Muhammad Tahir, Muhammad Sardaraz, Muhammad Sharif, Hela Elmannai, Abeer D. Algarni

“…Abstract Nowadays, many fields, such as healthcare, farming, factories, transportation, cities, and homes are connected via network devices. …”
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Classification of Lung Nodule Using Hybridized Deep Feature Technique by Malin Bruntha, Immanuel Alex Pandian, Siril Sam Abraham

“…Deep learning techniques have become very popular among Artificial Intelligence (AI) techniques in many areas of life. Among many types of deep learning techniques, Convolutional Neural Networks (CNN) can be useful in image classification applications. …”
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An Innovative Analysis of Time Series-Based Detection Models for Improved Cancer Detection in Modern Healthcare Environments by Uma Shankari Srinivasan, Venkat Pavithra, Kaliappan Sutha, Sridevi Ramachandiran, Nallathambi Indumathi

“…This enhanced version of time series analysis incorporates multiple layers of data sources and uses advanced machine learning algorithms to identify patterns that could signal the presence of a tumor. …”
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Basic parameters in speech processing. The need for evaluation by Harald HÖGE

“…Taking in account also adverse conditions the performance of many published algorithms to extract those parameters from the speech signal automatically is not known. …”
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How Recent Findings in Electromyographic Analysis and Synergistic Control Can Impact on New Directions for Muscle Synergy Assessment in Sports by Alessandro Scano, Valentina Lanzani, Cristina Brambilla

“…However, despite the fact that it is clear that, in many sports, the assessments based on multi-muscle analysis are crucial for performance, the practical impact of muscle synergies on sports practice has been quite limited. …”
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