Accuracy of Rhythm Diagnostic Systems’ MultiSense^® in Detection of Arterial Oxygen Saturation and Respiratory Rate During Hypoxia in Humans: Effects of Skin Color and De... by Charles Evrard, Amina El Attaoui, Cristina Pistea, Irina Enache, Mark Marriott, Louis Mayaud, Anne Charloux, Bernard Geny

“…The average root mean square error (ARMS) of SpO₂ for Multisense^® placed on the back and chest was 2.94% and 2.98%, respectively, with permutation testing confirming a significant ARMS below 3.5% for both positions and no statistically significant difference in the ARMS between patch placements. …”
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An Artificial Intelligence Solution for Automated Dental Inspection and Charting by M.A. Moufti, M. Abu Talib, S. Al Mokdad, A. Alhouria, M. Alsaffarini, N. Almahmeed, S. Eldessouky, W. Kharoufah, Q. Nasir

“…Background: Visual inspection and documentation (charting) of findings are critical components in dental practice. …”
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Machine learning frameworks to accurately estimate the adsorption of organic materials onto resin and biochar by Raouf Hassan, Mohammad Reza Kazemi

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Robust development of data-driven models for methane and hydrogen mixture solubility in brine by Kashif Saleem, Abhinav Kumar, K. D. V. Prasad, Ahmad Alkhayyat, T. Ramachandran, Protyay Dey, Navdeep Kaur, R. Sivaranjani, I. B. Sapaev, Mehrdad Mottaghi

“…The results indicate that Ensemble Learning and AdaBoost yield the highest accuracy algorithms in prediction capability as they tend to illustrate the lowest values of mean squared error and mean absolute relative error (%) and highest R-squared values. …”
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Performance Evaluation of Four Deep Learning-Based CAD Systems and Manual Reading for Pulmonary Nodules Detection, Volume Measurement, and Lung-RADS Classification Under Varying Ra... by Sifan Chen, Lingqi Gao, Maolu Tan, Ke Zhang, Fajin Lv

“…<b>Background:</b> Optimization of pulmonary nodule detection across varied imaging protocols remains challenging. …”
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Structure-guided deep learning for back acupoint localization via bone-measuring constraints by Yulong Wang, Tian Lan, Wenjian Dou, Zhi Chen, Song Zhang, Gong Chen, Gong Chen

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On-Road Evaluation of an Unobtrusive In-Vehicle Pressure-Based Driver Respiration Monitoring System by Sparsh Jain, Miguel A. Perez

“…The experimental results indicate that the system reliably detects the respiration rate despite the dynamic environment, achieving a mean absolute error of 1.5 breaths per minute with a standard deviation of 1.87 breaths per minute (9.2% of the mean true respiration rate), thereby bridging the gap between controlled laboratory tests and real-world automotive deployment. …”
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Precise prediction of choke oil rate in critical flow condition via surface data by Qing Wang, Muntadher Abed Hussein, Bhavesh Kanabar, Anupam Yadav, Asha Rajiv, Aman Shankhyan, Sachin Jaidka, Mehul Manu, Issa Mohammed Kadhim, Zainab Jamal Hamoodah, Fadhil Faez, Mohammad Mahtab Alam, Hojjat Abbasi

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Assessing Geometry Perception of Direct Time-of-Flight Sensors for Robotic Safety by Jakob Gimpelj, Marko Munih

“…Quantitative metrics including the root mean square error, mean absolute error, area difference, and others were used to evaluate measurement accuracy. …”
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Macroepidemiological trends of Influenza A virus detection through reverse transcription real-time polymerase chain reaction (RT-rtPCR) in porcine samples in the United States over... by Daniel C. A. Moraes, Guilherme A. Cezar, Edison S. Magalhães, Rafael R. Nicolino, Kinath Rupasinghe, Srijita Chandra, Gustavo S. Silva, Marcelo N. Almeida, Bret Crim, Eric R. Burrough, Phillip C. Gauger, Darin Madson, Joseph Thomas, Michael A. Zeller, Rodger Main, Mary Thurn, Paulo Lages, Cezar A. Corzo, Mattew Sturos, Hemant Naikare, Rob McGaughey, Franco Matias Ferreyra, Jamie Retallick, Jordan Gebhardt, Sara McReynolds, Jon Greseth, Darren Kersey, Travis Clement, Angela Pillatzki, Jane Christopher-Hennings, Beth S. Thompson, Melanie Prarat, Dennis Summers, Craig Bowen, Joseph Boyle, Kenitra Hendrix, James Lyons, Kelli Werling, Andreia G. Arruda, Mark Schwartz, Mark Schwartz, Paul Yeske, Deborah Murray, Brigitte Mason, Peter Schneider, Samuel Copeland, Luc Dufresne, Daniel Boykin, Corrine Fruge, William Hollis, Rebecca C. Robbins, Thomas Petznick, Kurt Kuecker, Lauren Glowzenski, Megan Niederwerder, Daniel C. L. Linhares, Giovani Trevisan

“…For IAV forecasting, a combined model using dynamic regression and a neural network outperformed individual models in 2023, achieving the lowest root mean square error (RMSE) and an improved overall skill score. …”
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Machine Learning-Driven Rapid Flood Mapping for Tropical Storm Imelda Using Sentinel-1 SAR Imagery by Reda Amer

“…., Jefferson and Chambers counties) experienced the most extensive flooding, as confirmed by SAR-based change detection. The proposed approach eliminates the need for manual threshold selection, thereby reducing misclassification errors due to speckle noise and land cover heterogeneity. …”
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Hydrological insights: Comparative analysis of gridded potential evapotranspiration products for hydrological simulations and drought assessment by Mohammed Abdallah, Ke Zhang, Sudhir Kumar Singh, Mukhtar Jibril Abdi, Ayman M. Elameen, Almutaz A.A. Mohammed, Hussam Eldin Elzain

“…Seasonally, GLEAM PET exhibits the highest accuracy and lowest error in streamflow simulation across all three regions. …”
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DeepLASD countermeasure for logical access audio spoofing by Hamed Al-Tairi, Ali Javed, Tasawer Khan, Abdul Khader Jilani Saudagar

“…Extensive experimentation was conducted on the large-scale and diverse ASVspoof 2019 and 2021 datasets. Achieving an Equal Error Rate as low as $$4.98\%$$ and a minimum Tandem Detection Cost Function of 0.1208, along with strong generalization to both VC and TTS spoof types, demonstrate the competency of the proposed method for LA spoofing detection. …”
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Comprehensive analysis on soil nitrogen prediction using near-infrared spectroscopy: Models, methods, and insights for precision agriculture by Xiaoyu Wang, Zhiyou Zhang, Yujiao Li, Jie Li, Qing Yang, Qiqi Liu, Zhijie Gong, Mengling Zhang, Xu Wang, Guanghui Xie

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Study on infrasonic leakage monitoring and signal processing for product oil pipeline by Yuanbo YIN, Yuxing LI, Wen YANG, Shu LU, Chen ZHANG, Cuiwei LIU, Kai YANG, Wuchang WANG

“…At a 91 km monitoring interval along the product oil pipeline, the positioning error was about 800 m, facilitating reliable monitoring up to a leak rate of 0.001 6 m3/s, with the minimum detectable leak rate recorded at 0.000 46 m3/s. …”
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From Accuracy to Vulnerability: Quantifying the Impact of Adversarial Perturbations on Healthcare AI Models by Sarfraz Brohi, Qurat-ul-ain Mastoi

“…Unlike prior studies, we conducted a quantitative evaluation on the impact of a Fast Gradient Sign Method (FGSM) attack on an optimized DL model designed for breast cancer detection to demonstrate how minor perturbations reduced the model’s accuracy from 98% to 53%, and led to a substantial increase in the classification errors, as revealed by the confusion matrix. …”
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An Obstacle Perception Algorithm Based on Multi-Sensor Fusion for Autonomous-Rail Rapid Transit by JIANG Liangyu, PAN Wenbo, HUANG Ruipeng

“…This paper presents an obstacle perception algorithm based on multi-sensor fusion, aimed at addressing omissions and errors, as well as low accuracy in object detection for autonomous-rail rapid transit (ART). …”
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Predictive identification of oral cancer using AI and machine learning by Saraswati Patel, Dheeraj Kumar

“…These findings underscore the importance of normalization in preprocessing for machine learning models, highlighting its role in achieving superior performance in oral cancer detection. …”
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Integrating AI predictive analytics with naturopathic and yoga-based interventions in a data-driven preventive model to improve maternal mental health and pregnancy outcomes by Neha Irfan, Sherin Zafar, Kashish Ara Shakil, Mudasir Ahmad Wani, S. N. Kumar, A. Jaiganesh, K. M. Abubeker

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Tightly coupled integration of vector HD map, LiDAR, GNSS, and INS for precise vehicle navigation in GNSS-challenging environment by Hongjuan Zhang, Chuang Qian, Wenzhuo Li, Bijun Li, Hui Liu

“…But it suffers from severe signal reflections and blockages of GNSS signals and error accumulation of INS with MEMS-IMU in GNSS-challenging environment. …”
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