Machine Learning Prediction of Left Ventricular Assist Device Thrombosis from Acoustic Harmonic Power by Kent D. Carlson, Dan Dragomir-Daescu, Barry A. Boilson

“…This study explored the use of machine learning algorithms to predict thrombosis from harmonic power values determined from the acoustic signatures of a cohort of HVAD patients (<i>n</i> = 11). …”
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HCVNet: Binocular Stereo Matching via Hybrid Cost Volume Computation Module With Attention by Chenglin Dai, Qingling Chang, Tian Qiu, Xinglin Liu, Yan Cui

“…Though recent study brings an awareness of the convolution neural networks and the attention algorithms used in this field can make great progress, it is still difficult to satisfy the demand of high-precision applications due to many reasons. …”
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YConvFormer: A Lightweight and Robust Transformer for Gearbox Fault Diagnosis with Time–Frequency Fusion by Yihang Peng, Jianjie Zhang, Songpeng Liu, Mingyang Zhang, Yichen Guo

“…Current diagnostic algorithms often struggle with balancing computational efficiency and diagnostic accuracy, particularly in noisy and variable operating conditions. …”
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Signal Mining and Analysis of Drug-Induced Myelosuppression: A Real-World Study From FAERS by Kaiyue Xia MM, Shupeng Chen MD, Yingjian Zeng MD, Nana Tang MD, Meiling Zhang MD

“…However, early identification of DIM remains challenging, as many associated drugs do not explicitly list this risk, complicating clinical monitoring. …”
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Issues, Challenges, and Solution Options for On-Grid Multi-Microgrid Game Theory: A Systematic Review by Dimas Jalaluddin Ahmad, Nanang Hariyanto, Umar Khayam

“…Many studies have been conducted on the implementation of game theory approaches in optimizing energy trading and scheduling in multi-microgrid (MMG) systems, both in cooperative and non-cooperative games. …”
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Investigating Trends and Costs Associated with Designing Concrete Mixes Using Different Methods by Computer Programs by Mohammed Abdul Qader, Ahmed Ibrahim, Al-Badr Alaidaros, Abdul Kareem Abdulkareem, Abdullah Alwuayl, Abdullah Alsaluli, Mamdooh Alwetaishi, Mishal Alsehli, Saleh Alghamdi

“…Concrete mixes can be designed using many methods such as the British method (DOE) and the American method (ACI). …”
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CareNexus: Integrated solutions for Healthcare Communication by Alexandru Ioan BULZAN

“…A secure authentication based on multiple factors and the use of encryption algorithms, an interface based on different user roles and a prediction system based on model training had been implemented. …”
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Energy Distribution Optimization in Heterogeneous Networks with Min–Max and Local Constraints as Support of Ambient Intelligence by Alessandro Aloisio, Domenico D. Bloisi, Marco Romano, Cosimo Vinci

“…Additionally, we examine the computational complexity of this model and propose two solution algorithms grounded in fixed-parameter tractability theory for specific network classes.…”
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GPU Assisted Brute Force Cryptanalysis of GPRS, GSM, RFID, and TETRA by Cihangir Tezcan, Gregor Leander

“…While nowadays at least 128-bit keys are recommended, there are many standards and real-world applications that use shorter keys. …”
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Artificial Intelligence in Digital Marketing: Towards an Analytical Framework for Revealing and Mitigating Bias by Catherine Reed, Martin Wynn, Robin Bown

“…Artificial intelligence (AI) affects many aspects of modern life, and most predictions are that the impact of AI on business and society will only increase. …”
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Oversampling based on generative adversarial networks to overcome imbalance data in predicting fraud insurance claim by Ranu Agastya Nugraha, Hilman Ferdinandus Pardede, Agus Subekti

“…The problem of data imbalance would affect machine learning capabilities which tend to be biased towards the majority class. Recently, many efforts have been employed to use deep learning for data augmentation. …”
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Comparing Machine Learning-Based Crime Hotspots Versus Police Districts: What&#x2019;s the Best Approach for Crime Forecasting? by Eugenio Cesario, Paolo Lindia, Andrea Vinci

“…This study examines the impact of various partitioning techniques on crime forecasting performance, comparing the traditional static division of the city into police districts with machine learning approaches, specifically density clustering algorithms, for detecting crime hotspots. The experimental evaluation, conducted on two real-world case studies, i.e. …”
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Research Progress on Sequence Recommendation Based on Deep Learning and Large Language Model by XU Fengru, LI Bohan, XU Shuai

“…The sequence recommendation system analyzes user behavior sequences, captures the dynamic changes of user preferences, and provides accurate personalized recommendation services for many fields such as e-commerce, social media and online videos. …”
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Enhancing Machine Learning Models Through PCA, SMOTE-ENN, and Stochastic Weighted Averaging by Youngjin Han, Inwhee Joe

“…An ensemble model combining seven machine learning algorithms—Logistic Regression, Support Vector Machine, KNN, Random Forest, XGBoost, LightGBM, and CatBoost—was applied to predict survival outcomes. …”
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Identifying the optimal number of topics in text mining: a case study on reindeer pastoralism literature by Barbara Contiero, Øystein Holand, Giulio Cozzi

“…Text mining and topic analysis algorithms which group textual contents in the most efficient way, are becoming increasingly useful to summarise the main information contained in large data corpus of complex scientific fields. …”
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Multi-View Collaborative Training and Self-Supervised Learning for Group Recommendation by Feng Wei, Shuyu Chen

“…One of the key challenges facing recommendation algorithms is data sparsity, a limitation that is even more severe in group recommendation than in traditional recommendation tasks. …”
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A systematic review of UAV and AI integration for targeted disease detection, weed management, and pest control in precision agriculture by Iftekhar Anam, Naiem Arafat, Md Sadman Hafiz, Jamin Rahman Jim, Md Mohsin Kabir, M.F. Mridha

“…Unmanned aerial vehicles (UAV), often unmanned aerial systems, are increasingly used in many industries, such as agriculture, forestry, the military, and disaster management. …”
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Sparse Linear Discriminant Analysis With Constant Between-Class Distance for Feature Selection by Shuangle Guo, Yongxia Li, Jianguang Zhang, Yue Liu, Tian Tian, Mengchen Guo

“…Due to its ability to effectively maintain the discriminability of extracted features, Trace Ratio Linear Discriminant Analysis (TR-LDA) has become the foundation for many feature selection algorithms. As is known, TR-LDA is a challenging problem to solve because of its trace-ratio form, and it also faces the scale invariance problem. …”
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A systematic review of machine learning and deep learning approaches in plant species detection by Deepti Barhate, Sunil Pathak, Bhupesh Kumar Singh, Amit Jain, Ashutosh Kumar Dubey

“…Classifiers and other machine learning and deep learning algorithms that can accurately categorize and extract data can be further developed. …”
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Mapping Polyclonal HIV-1 Antibody Responses via Next-Generation Neutralization Fingerprinting. by Nicole A Doria-Rose, Han R Altae-Tran, Ryan S Roark, Stephen D Schmidt, Matthew S Sutton, Mark K Louder, Gwo-Yu Chuang, Robert T Bailer, Valerie Cortez, Rui Kong, Krisha McKee, Sijy O'Dell, Felicia Wang, Salim S Abdool Karim, James M Binley, Mark Connors, Barton F Haynes, Malcolm A Martin, David C Montefiori, Lynn Morris, Julie Overbaugh, Peter D Kwong, John R Mascola, Ivelin S Georgiev

“…Specifically, the next-generation NFP algorithms detected multiple specificities in twice as many samples of simulated sera. …”
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