A Robust Conformal Framework for IoT-Based Predictive Maintenance by Alberto Moccardi, Claudia Conte, Rajib Chandra Ghosh, Francesco Moscato

“…At its core, this paper leverages the commercial modular aero-propulsion system simulation (CMAPSS) dataset to evaluate different artificial intelligence (AI) prognostic algorithms for remaining useful life (RUL) forecasting while supporting the estimation of a robust confidence interval (CI). …”
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Assessing the Cause of Death for Men with Prostate Cancer Using Official Mortality Statistics or a Dedicated Cause of Death Committee: Results from 30-year ERSPC Rotterdam Data by Sebastiaan Remmers, Ivo I. de Vos, Frederique B. Denijs, Renée C.A. Leenen, Tycho M.T.W. Lock, Arjen Noordzij, Wim J. Kirkels, Chris H. Bangma, Monique J. Roobol

“…For men with prostate cancer (PCa) within the European Randomized Study of Screening for Prostate Cancer (ERSPC), the cause of death is determined by a Cause of Death Committee (CODC) that evaluates all medical records using a fixed algorithm. …”
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Impacts of air fraction increase on Arctic sea ice density, freeboard, and thickness estimation during the melt season by E. Salganik, O. Crabeck, O. Crabeck, N. Fuchs, N. Hutter, N. Hutter, P. Anhaus, P. Anhaus, J. C. Landy

“…This increase in air volume substantially affected FYI density and freeboard. Due to differences in sea ice thermodynamic state (such as salinity and temperature), the air volume expansion is less pronounced in second-year ice (SYI) and has a smaller impact on the density evolution of SYI and ridges. …”
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Spatiotemporal Characteristics of Public Attention Level on the 2022 Extreme Drought in Yangtze River Basin Based on Weibo Text Analysis by LI Zhe, CHEN Zhe, XIANG Da-xiang, CUI Chang-lu

“…Utilizing texts from Weibo, a mainstream social media platform in China, as data sources, this study used machine learning and artificial intelligence algorithms to collect Weibo text data throughout the drought progression process. …”
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Influence disabling the cylynders of internal combustion engine on working process earthmovers machines by S. S. Zhuravlev

“…The article considers the effects of disabling the cylinder to change the characteristics of the engine earth-moving machines in various operating modes, calculated the diesel engines with subsequent analysis of their performance under different algorithms disable cylinders, evaluated the possibility of using additional flywheel to increase the technological parameters of the machine during operation.…”
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Effectiveness of machine learning models in diagnosis of heart disease: a comparative study by Waleed Alsabhan, Abdullah Alfadhly

“…By subjecting the ML models to exhaustive experimentation, this study evaluates the effects of different feature scaling, namely standardization, minmax scaling, and normalization technique on their performance. …”
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Machine Learning-Based Classification for Crop-Type Mapping Using the Fusion of High-Resolution Satellite Imagery in a Semiarid Area by Aicha Moumni, Abderrahman Lahrouni

“…The monitoring of cultivated crops and the types of different land covers is a relevant environmental and economic issue for agricultural lands management and crop yield prediction. …”
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Automated Vertebral Bone Quality Determination from T1-Weighted Lumbar Spine MRI Data Using a Hybrid Convolutional Neural Network–Transformer Neural Network by Kristian Stojšić, Dina Miletić Rigo, Slaven Jurković

“…These methods use different algorithms for CSF extraction from the segmentation of the spinal canal using T1- and T2-weighted image data and applying erosion to the vertebral ROI to avoid a sharp change in SI at the edge of the vertebral body.…”
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An efficient interpretable framework for unsupervised low, very low and extreme birth weight detection. by Ali Nawaz, Amir Ahmad, Shehroz S Khan, Mohammad Mehedy Masud, Nadirah Ghenimi, Luai A Ahmed

“…We employed fourteen different anomaly detection algorithms and evaluated their performance using Area Under the Receiver Operating Characteristics (AUCROC) and Area Under the Precision-Recall Curve (AUCPR) metrics. …”
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Airport-FOD3S: A Three-Stage Detection-Driven Framework for Realistic Foreign Object Debris Synthesis by Hanglin Cheng, Yihao Li, Ruiheng Zhang, Weiguang Zhang

“…The image quality of different blending methods was quantitatively evaluated using metrics such as structural similarity index and peak signal-to-noise ratio, as well as Depthanything. …”
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Forage biomass estimation using UAV-based remote sensing and machine learning: A tool for assessing management practices by Biquan Zhao, Jeremy Hiller, Tala Awada, Brian Wardlow, Galen Erickson, Yeyin Shi

“…Using UAV-derived forage dry matter (DM) maps collected over two years from for managed Bromus inermis dominated pastures in eastern Nebraska, we evaluated the impacts of grazing and fertilization management practices on biomass. …”
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Pre-transplant IE1-specific T-cell response and CD8+ T-cell count as predictive markers of treated HCMV reactivation in kidney transplant recipients by Federica Zavaglio, Irene Cassanti, Irene Cassanti, Marilena Gregorini, Marilena Gregorini, Maria Antonietta Grignano, Teresa Rampino, Daniele Lilleri, Fausto Baldanti, Fausto Baldanti

“…Potential cut-off and diagnostics algorithm should be better investigated in a large patients setting.…”
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Prediction of early breast cancer patient survival using ensembles of hypoxia signatures. by Inna Y Gong, Natalie S Fox, Vincent Huang, Paul C Boutros

“…We demonstrate that the best way of merging preprocessing methods varies from signature to signature, and that there is likely no 'best' preprocessing pipeline that is universal across datasets, highlighting the need to evaluate ensembles of preprocessing algorithms. Further, we developed novel signatures for each preprocessing method and the risk classifications from each were incorporated in a meta-random forest model. …”
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Machine-learning model for predicting left atrial thrombus in patients with paroxysmal atrial fibrillation by Wanli Xiong, Qiqi Cao, Lu Jia, Min Chen, Tao Liu, Qingyan Zhao, Yanhong Tang, Bo Yang, Li Li, Shaobo Shi, He Huang, Congxin Huang, China Atrial Fibrillation Center Project Team

“…Calibration analysis indicated no significant difference between predicted and observed values (p = 0.181). …”
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A Synergistic Framework for Coupling Crop Growth, Radiative Transfer, and Machine Learning to Estimate Wheat Crop Traits in Pakistan by Rana Ahmad Faraz Ishaq, Guanhua Zhou, Aamir Ali, Syed Roshaan Ali Shah, Cheng Jiang, Zhongqi Ma, Kang Sun, Hongzhi Jiang

“…The integration of the Crop Growth Model (CGM), Radiative Transfer Model (RTM), and Machine Learning Algorithm (MLA) for estimating crop traits represents a cutting-edge area of research. …”
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Deep LBLS: Accelerated Sky Region Segmentation Using Hybrid Deep CNNs and Lattice Boltzmann Level-Set Model by Fatema A. Albalooshi, M. R. Qader, Yasser Ismail, Wael Elmedany, Hesham Al-Ammal, Muttukrishnan Rajarajan, Vijayan K. Asari

“…The performance of the proposed method is evaluated on the CamVid dataset, which contains images with a wide range of object variations due to factors such as illumination changes, shadow presence, occlusion, scale differences, and cluttered backgrounds. …”
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Evidence of compensatory neural hyperactivity in a subgroup of breast cancer survivors treated with chemotherapy and its association with brain aging by Michele M. Mulholland, Alexa Stuifbergen, Alexa De La Torre Schutz, Oscar Y. Franco Rocha, Douglas W. Blayney, Shelli R. Kesler

“…We also calculated the brain age gap by applying a previously validated algorithm to anatomic MRI.ResultsWe found that neural activity differed across the three CRCI biotypes and controls (F = 13.5, p < 0.001), with Biotype 2 demonstrating significant hyperactivity compared to the other groups (p < 0.004, corrected), primarily in prefrontal regions. …”
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Breast Tumor-Like-Masses Segmentation From Scattering Images Obtained With an Ultrahigh-Sensitivity Talbot-Lau Interferometer Using Convolutional Neural Networks by Ionut-Cristian Ciobanu, Nicoleta Safca, Elena Anghel, Dan Popescu

“…Performance was evaluated based on accuracy, precision, specificity, recall, and F1-score. …”
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Towards a computer-assisted assessment of imitation in children with autism spectrum disorder based on a fine-grained analysis by Rujing Zhang, Jingying Chen, Xiaodi Liu, Yanling Gan, Guangshuai Wang

“…Then, three classic machine-learning algorithms were employed to explore whether the indicators could efficiently classify children with imitation difficulties. …”
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Metabolomic profiling and biomarker identification for early detection and therapeutic targeting of doxorubicin-induced cardiotoxicity by Jingjing Ding, Jingjing Ding, Xianzhen Feng, Zhongqing Xu, Hong Xu

“…Key metabolites were assessed using a random forest algorithm, and ROC curves evaluated diagnostic value. …”
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