Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys by Uma Maheshwera Reddy Paturi, Muhammad Ishtiaq, Pasupuleti Lakshmi Narayana, Anoop Kumar Maurya, Seong-Woo Choi, Nagireddy Gari Subba Reddy

“…This study evaluates the predictive capabilities of various machine learning (ML) algorithms for estimating the hardness of AlCoCrCuFeNi high-entropy alloys (HEAs) based on their compositional variables. …”
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Incident duration prediction through integration of uncertainty and risk factor evaluation: A San Francisco incidents case study. by Amirreza Salehi, Ardavan Babaei, Majid Khedmati

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Non-Destructive Testing and Evaluation of Hybrid and Advanced Structures: A Comprehensive Review of Methods, Applications, and Emerging Trends by Farima Abdollahi-Mamoudan, Clemente Ibarra-Castanedo, Xavier P. V. Maldague

“…The transformative role of NDE 4.0 in enabling automated, real-time, and predictive structural assessment is also discussed. …”
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Evaluating Diverse Meta-modeling Approaches for Predicting Performance Characteristics of a Twin Air Intake Based on Experimental Data by Human AMIRI, U. C. Kucuk, O. Kucukoglu, Y. F. Kuscu, O. V. Ozdemır

“…The results reveal that the Random Forest Regression (RFR) model outperforms all other models across all evaluated metrics, demonstrating its superior effectiveness in predicting the performance characteristics of the twin air intake system.…”
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Deep Inspiratory Breath-Hold Technique for Patients with Left-Sided Breast Cancer: Dosimetric Analysis, Clinical Evaluation, and Prediction by Jing Shen MD, Kun Zhang MD, Xiangyin Meng PhD, Bo Yang PhD, Jiabin Ma MD, Ke Hu MD, Fuquan Zhang MD, Xiaorong Hou MD

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Evaluating machine learning algorithms for predicting HIV status among young Thai men who have sex with men by Krittaka Soha, Sadiporn Phuthomdee, Thanapat Srichai, Lanchakorn Kittiratanawasin, Win Min Han, Sirinya Teeraananchai

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Evaluation of Sentinel-2 Deep Resolution 3.0 Data for Winter Crop Identification and Organic Barley Yield Prediction by Milen Chanev, Ilina Kamenova, Petar Dimitrov, Lachezar Filchev

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Early Evaluation of the Short Physical Performance Battery in Hospitalized Patients with Chronic Kidney Disease Predicts Long-Term Hospitalization by Takashi Amari, Eiji Kubo, Yota Kuramochi, Shota Onoda, Kyosuke Fukuda, Emi Yokoyama, Masami Kimura, Tomoyuki Arai

“…This study aimed to determine whether assessment of physical function one week after hospitalization can predict the length of stay in patients with CKD. Methods: A retrospective study was conducted on hospitalized patients with CKD who underwent rehabilitation between March 2019 and March 2020. …”
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How to use learning curves to evaluate the sample size for malaria prediction models developed using machine learning algorithms by Sophie G. Zaloumis, Megha Rajasekhar, Julie A. Simpson

“…Methods To illustrate the approach, training dataset sizes were evaluated to inform the design of a “mock” prediction modelling study aimed to predict the artemisinin resistance status of Plasmodium falciparum malaria isolates from gene expression data. …”
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Humanoid robots for psychological assessment in mild cognitive impairment: from evaluation to the future of AI-driven data prediction systems by Caterina Formica, Fabio Mauro Giambò, Desiree Latella, Lilla Bonanno, Marco Lombardo, Orazio Tomarchio, Angela Marra, Antonella Alagna, Carmen Bonanno, Angelo Quartarone, Silvia Marino

“…This study explores the feasibility of using the humanoid robot Pepper to administer cognitive assessments for Mild Cognitive Impairment (MCI). Specifically, it evaluates the usability, accuracy, and patient experience of robot-administered cognitive testing compared to traditional assessments conducted by neuropsychologists.MethodsA total of 100 MCI patients were randomly assigned to two groups: one undergoing the Mini-Mental State Examination (MMSE) with Pepper and the other receiving the same test administered by a neuropsychologist. …”
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Evaluation of the ATRIA and CHA2DS2-VASc Scores and Their Performance on Predicting Mortality in Patients with Acute Pulmonary Embolism by Ozge Ozcan Abacioglu, Arafat Yildirim, Mine Karadeniz, Ferhat Dindas, Serkan Abacioglu, Nermin Yildiz Koyunsever, Mustafa Dogdus

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A Moroccan soil spectral library use framework for improving soil property prediction: Evaluating a geostatistical approach by Tadesse Gashaw Asrat, Timo Breure, Ruben Sakrabani, Ron Corstanje, Kirsty L. Hassall, Abdellah Hamma, Fassil Kebede, Stephan M. Haefele

“…Twelve soil properties were used to evaluate these calibration sample selections to predict soil properties using the near infrared (NIR) and mid infrared (MIR) ranges. …”
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Enhancing landslide disaster prediction by evaluating non landslide area sampling in machine learning models for Spiti Valley India by Devraj Dhakal, Kanwarpreet Singh, Kennedy C. Onyelowe, Steven Alejandro Salazar Cazco, Abhishek Sharma, Nassir Alarifi, Fakhrul Islam, Randeep, Krishna Prakash Arunachalam, Youssef M. Youssef

“…These advancements highlight the capability of the SBSP method to enhance susceptibility predictions and reduce overestimation in areas of high vulnerability. …”
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Evaluation of the Efficacy of a Nomogram to Predict Multidrug-Resistant Pulmonary Infections Based on Data from Neurosurgery Ward Patients by Zhou R, Chen X, Jia H, Duan W

“…Ran Zhou,1,* Xiaolong Chen,2,* Hengmin Jia,3 Wen Duan4 1Department of Pharmacy, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230001, People’s Republic of China; 2Department of Pharmacy, The Second People’s Hospital of Chizhou, Chizhou, Anhui, 247100, People’s Republic of China; 3Department of Infection Office, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230001, People’s Republic of China; 4Department of Orthopedics, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, Anhui, 230001, People’s Republic of China*These authors contributed equally to this workCorrespondence: Wen Duan, Department of Orthopedics, The First Affiliated Hospital of USTC, Division of Life Sciences and Medicine, University of Science and Technology of China, Hefei, 230001, People’s Republic of China, Email duanwen1717@gmail.comObjective: This study aimed to construct and evaluate a nomogram based on data from neurosurgery ward patients to predict the probability of multidrug-resistant (MDR) pneumonia occurrence.Methods: We retrospectively collected clinical data, early laboratory test results, and physician prescriptions for 35 variables from patients. …”
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Construction and evaluation of a nomogram model for predicting the risk of hospital-acquired pneumonia in elderly patients with acute ischemic stroke by Man Huang, Wan Wang, Wu-lin Li, Yan-qing Chen, Xian-ting Chen, Ye Liu, Yan Li, Dong-mei Ren, Fei Wang

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Evaluating the radiosensitivity of the oral microbiome to predict radiation-induced mucositis in head and neck cancer patients: A prospective trial by Andreas R. Thomsen, Elsa Beatriz Monroy Ordonez, Michael Henke, Benedikt Luka, Jörg Sahlmann, Henning Schäfer, Vivek Verma, Nadine Schlueter, Anca-Ligia Grosu, Tanja Sprave

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Evaluation of statistical models of carriage to predict the impact of the 10-valent pneumococcal conjugate vaccine on invasive pneumococcal disease in Nigeria by Aishatu L. Adamu, John. Ojal, Caroline Mburu, Katherine E. Gallagher, Stefan Flasche, Kofo Odeyemi, Christy A.N. Okoromah, Isa S. Abubakar, Musa M. Bello, Victor Inem, Angela Karani, Boniface Karia, Donald Akech, Ifedayo M.O. Adetifa, J. Anthony G. Scott

“…Methods: We applied external data, with assumptions, to empirical carriage prevalence data to predict IPD incidence rate ratios (IRRs). …”
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Deep learning and genomic best linear unbiased prediction integration: An approach to identify potential nonlinear genetic relationships between traits by F. Shokor, P. Croiseau, H. Gangloff, R. Saintilan, T. Tribout, T. Mary-Huard, B.C.D. Cuyabano

“…ABSTRACT: Genomic prediction (GP) aims to predict the breeding values of multiple complex traits, usually assumed to be multivariate normally distributed by the largely used statistical methods, thus imposing linear genetic relationships between traits. …”
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Assessing the robustness of VIS-NIR spectroscopy-based soil organic carbon prediction against four wet chemistry methods by Cho-Yin Wu, Po-Hui Wu, Zeng-Yei Hseu

“…Nevertheless, model reliability has mostly been evaluated statistically, with limited explanation from a soil science perspective or validation against various wet lab methods, which differ in reliable. …”
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Detection and Prediction of Wind and Solar Photovoltaic Power Ramp Events Based on Data-Driven Methods: A Critical Review by Jie Zhang, Xinchun Zhu, Yigong Xie, Guo Chen, Shuangquan Liu

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