Programmed cell death signatures-driven microglial transformation in Alzheimer’s disease: single-cell transcriptomics and functional validation by Mi-Mi Li, Ying-Xia Yang, Ya-Li Huang, Shu-Juan Wu, Wan-Li Huang, Li-Chao Ye, Ying-Ying Xu

“…BackgroundThis study aims to develop and validate a programmed cell death signature (PCDS) for predicting and classifying Alzheimer’s disease (AD) using an integrated machine learning framework. …”
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Distress-Based Pavement Condition Assessment Using Artificial Intelligence: A Case Study of Egyptian Roads by Mostafa M. Radwan, Sundus A. Faris, Ahmed Y. Barakat, Ahmad Mousa

“…The ANN model exhibited greater prediction accuracy than the other developed models and can also reliably forecast PCI values by using only measured distress data.…”
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Point-of-care prognostication in moderate Covid-19: Analytical validation and prognostic accuracy of a soluble urokinase plasminogen activator receptor (suPAR) rapid test. by Arjun Chandna, Raman Mahajan, Priyanka Gautam, Lazaro Mwandigha, Sabine Dittrich, Vikash Kumar, Jennifer Osborn, Pragya Kumar, Constantinos Koshiaris, George M Varghese, Yoel Lubell, Sakib Burza

“…AUC of ELISA = 0.70 [95% CI = 0.63 to 0.76]; p = 0.12) or as part of a published multivariable prediction model (AUC of RDT-based model = 0.74 [95% CI = 0.66 to 0.83] vs. …”
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Cotton Crop Classification using Optical and Microwave Remote Sensing Datasets in Google Earth Engine by B. Meerasha, M. Sagayam

“…To make well-informed decisions, farmers, governments, scientists, and agricultural organizations need accurate information on crop prediction. However, automated crop type mapping remains challenging due to the limited availability of field-level crop labels required to train supervised classification models. …”
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Accurate and affordable multi-cancer early detection and localization via plasma cfDNA multi-omic profiling by Pin Cui, Weihuang He, Mingji Feng, Hanming Lai

“…By combining cfDNA cleavage profile of CpG sites with machine learning algorithms, we have identified specific CpG cleavage profile as biomarkers to predict the methylation status of individual CpG sites, based on which we built in silico classifiers for prediction of each of the four groups previously mentioned, achieving considerable performance of AUC ranging from 0.8896 to 0.959. …”
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Deep reinforcement learning Lane-Change Decision-Making for autonomous vehicles based on motion primitives library in hierarchical action space by Guizhe Jin, Zhuoren Li, Bo Leng, Minhua Shao

“…In addition, model predictive control method (MPC) based on the vehicle kinematics model is used to optimize the motion primitives instantly. …”
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Concise and Accessible Representations for Multidimensional Datasets: Introducing a Framework Based on the nD-EVM and Kohonen Networks by Ricardo Pérez-Aguila, Ricardo Ruiz-Rodríguez

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Classification of English Words into Grammatical Notations Using Deep Learning Technique by Muhammad Imran, Sajjad Hussain Qureshi, Abrar Hussain Qureshi, Norah Almusharraf

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Edge-level multi-constranint graph pattern matching with lung cancer knowledge graph by Houdie Tu, Lei Li, Lei Li, Zhenchao Tao, Zhenchao Tao, Zan Zhang, Zan Zhang

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IMPLEMENTATION OF LEARNING MANAGEMENT SYSTEMS WITH GENERATIVE ARTIFICIAL INTELLIGENCE FUNCTIONS IN THE POST-PANDEMIC ENVIRONMENT by Denis-Cătălin Arghir

“…The selected system emerged as the most favorable, offering a robust framework for the development and delivery of educational content. To demonstrate the system's effectiveness, a curriculum was crafted for a specialized field of study - Artificial Intelligence (AI), with a specific focus on the practical application of Machine Learning algorithms. …”
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A Comparison Between the Use of an Infrared Contact Mat and an IMU During Kinematic Analysis of Horizontal Jumps by Bjørn Johansen, Jono Neville, Roland van den Tillaar

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SD-YOLOv8: Automated Motion Detection System for Aerobics Students by Lian Tang, Ya Li, Qing Du, Jincheng Liang

“…Existing object detection algorithms are often constrained by the high computational costs associated with large network structures in practical applications. …”
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Maximizing YOLOv2 efficiency: A study on multiclass detection of indoor objects by G Divya Deepak, Subraya Krishna Bhat

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Deep learning for COVID-19 by X-ray images Analysis and Designing Diagnostic Application by Thamer Khaleel, Ali Kalakech

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Multi-View Collaborative Training and Self-Supervised Learning for Group Recommendation by Feng Wei, Shuyu Chen

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Adaptive FPGA-Based Accelerators for Human–Robot Interaction in Indoor Environments by Mangali Sravanthi, Sravan Kumar Gunturi, Mangali Chinna Chinnaiah, Siew-Kei Lam, G. Divya Vani, Mudasar Basha, Narambhatla Janardhan, Dodde Hari Krishna, Sanjay Dubey

“…This study addresses the challenges of human–robot interactions in real-time environments with adaptive field-programmable gate array (FPGA)-based accelerators. Predicting human posture in indoor environments in confined areas is a significant challenge for service robots. …”
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Risk assessment of oral leukoplakia by DNA content enhanced by machine learning models by Matheus Henrique Lopes Dominguete, Vera Cavalcanti de Araújo, Fernanda Viviane Mariano, Carmen Silvia Passos Lima, João Figueira Scarini, Paulo de Camargo Moraes, Victor Angelo Martins Montalli, Larissa Agatti, Zuraiza Mohamad Zaini, Luíza Hellmeister, Marcelo Sperandio

“…A 3-step algorithm using these two parameters to classify lesions into low risk and high risk resulted in 52% positive predictive value (PPV) and 93% negative predictive value (NPV). …”
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Big data and AI for gender equality in health: bias is a big challenge by Anagha Joshi, Anagha Joshi, Anagha Joshi

“…Despite these promises, machine learning applications are not widely adapted in clinical care due to many issues including ethical concerns, patient privacy, informed consent, algorithmic biases, data quality and availability, and education and training of health care professionals. …”
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Control system design for azimuth position of earth station antennas by Auday Al-Mayyahi, Ammar Aldair, Zainab A. Khalaf, William Wang

“…It also introduces a new methodology based on model predictive control (MPC). The manuscript provides the core design for each of these controllers and provides insight into the performance of each controller even in the presence of disturbance. …”
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Dosiomic predictors of biochemical failure in patients with localized prostate cancer treated with Iodine-125 low-dose-rate brachytherapy by Masahiro Nakano, Shizuo Kaji, Shogo Kawakami, Hideyasu Tsumura, Toshikazu Imae, Yuichi Tanaka, Kyohei Fujii, Takuro Kainuma, Ryosuke Yamazaki, Ayaka Uchida, Hijiri Kaneko, Mako Fujino, Chizu Hata, Yu Murakami, Masatoshi Hashimoto, Hiromichi Ishiyama

“…In analysis B, the AUC of the logistic regression prediction models using S, H, and all four features were 0.81, 0.77, and 0.86, respectively. …”
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