Targeted Detection of 76 Carnitine Indicators Combined with a Machine Learning Algorithm Based on HPLC-MS/MS in the Diagnosis of Rheumatoid Arthritis by Rui Zhang, Juan Wang, Xiaonan Zhai, Yuanbing Guo, Lei Zhou, Xiaoyan Hao, Liu Yang, Ruiqing Xing, Juanjuan Hu, Jiawei Gao, Fengjuan Wang, Jun Yang, Jiayun Liu

“…Methods: Using high-performance liquid chromatography–mass spectrometry (HPLC-MS/MS) targeted detection, we evaluated 76 carnitine indicators (55 carnitines and 21 corresponding ratios) in the serum of patients with RA to investigate the role of carnitine in RA. …”
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Postoperative outcome analysis of chronic rhinosinusitis using transfer learning with pre-trained foundation models based on endoscopic images: a multicenter, observational study by Wentao Gong, Keguang Chen, Xiao Chen, Xueli Liu, Zhen Li, Li Wang, Yuxuan Shi, Quan Liu, Xicai Sun, Xinsheng Huang, Xu Luo, Hongmeng Yu

“…Conclusion The transfer learning algorithm model based on pre-trained foundation models can provide accurate and reproducible analysis of postoperative outcomes in CRS, effectively addressing the issue of high subjectivity in postoperative evaluation. …”
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Predicting low birth weight risks in pregnant women in Brazil using machine learning algorithms: data from the Araraquara cohort study by Audêncio Victor, Francielly Almeida, Sancho Pedro Xavier, Patrícia H.C. Rondó

“…This study aimed to develop and evaluate predictive models for LBW using machine learning algorithms, including Random Forest, XGBoost, Catboost, and LightGBM. …”
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Exploring machine learning algorithms to predict short birth intervals and identify its determinants among reproductive-age women in East Africa by Tirualem Zeleke Yehuala, Bezawit Melak Fente, Sisay Maru Wubante

“…Four machine learning models, including logistic regression, decision trees, random forests, and some machine learning models, including logistic regression, decision trees, random forests, and naive Bayes, are trained and evaluated to predict short birth intervals. …”
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Comparison of a machine learning model with a conventional rule-based selective dry cow therapy algorithm for detection of intramammary infections by S.M. Rowe, E. Zhang, S.M. Godden, A.K. Vasquez, D.V. Nydam

“…ABSTRACT: We trained machine learning models to identify IMI in late-lactation cows at dry-off to guide antibiotic treatment, and compared their performance to a rule-based algorithm that is currently used on dairy farms in the United States. …”
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Prediction of zero-dose children using supervised machine learning algorithm in Tanzania: evidence from the recent 2022 Tanzania Demographic and Health Survey by Beminate Lemma Seifu, Angwach Abrham Asnake, Alemayehu Kasu Gebrehana

“…After training the models, the testing data were used to evaluate their performance. …”
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Prediction of Insulator ESDD Based on Meteorological Feature Mining and AdaBoost-MEA-ELM Model by Yaoping WANG, Te LI, Kaihua JIANG, Wenhui LI, Qiang WU, Yu WANG

“…The meteorological features that are more closely related to insulator pollution degree are mined, and the importance of each meteorological feature is evaluated by the random forest algorithm. Combined with the sequential forward search method, the optimal subset of meteorological features for ESDD prediction model could be determined. …”
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Evaluating the efficiency of teaching basic cardiopulmonary resuscitation among medical university students in Ukraine by H.Yu. Tsymbaliuk, A.M. Chervatiuk, V.O. Krylyuk

“…Structured testing was also conducted to assess the level of theoretical knowledge of the adult BCPR algorithm. Results. In the sample studied, most students had BCPR training for the first time in the second year, while 11.7 % had not such training by the time of testing (third year). …”
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Multiphase Computed Tomography Scan Findings for Artificial Intelligence Training in the Differentiation of Hepatocellular Carcinoma and Intrahepatic Cholangiocarcinoma Based on In... by Nakarin Inmutto, Suwalee Pojchamarnwiputh, Wittanee Na Chiangmai

“…<b>Conclusions:</b> Cirrhosis and lymph node metastasis could be ancillary and adopted in future AI training algorithms.…”
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Impact of SARS CoV-2 / Influenza A &amp; B / RSV Multiplex PCR Screening Algorithm on Patient Management and Antimicrobial Use by Sultan Gülbahçe Orhan, Ayse Esra Karakoç, Burcu Ceylan Cura Yayla, Medine Ayşin Taşar

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Forest Change Monitoring Based on Block Instance Sampling and Homomorphic Hypothesis Margin Evaluation by Wei Feng, Fan Bu, Puxia Wu, Gabriel Dauphin, Yinghui Quan, Mengdao Xing

“…While remote sensing image classification offers substantial advantages over ground surveys for monitoring changes in forests, it encounters several challenges. Firstly, training samples in classification algorithms are typically selected through pixel-based random sampling or manual regional sampling. …”
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Analyzing the internal resonances and energy exchange between modes of power system considering Frequency – Energy dependence using Pseudo-Arclength and shooting algorithm by Fazad Fallahi, Peyman Naderi

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Evaluating the potential of short-term instrument deployment to improve distributed wind resource assessment by L. M. Sheridan, D. Duplyakin, C. Phillips, H. Tinnesand, H. Tinnesand, R. K. Rai, J. E. Flaherty, L. K. Berg

“…</p> <p>Three algorithms, multivariable linear regression, adaptive regression splines, and regression trees, are evaluated for their skill at correcting long-term wind resource estimates from the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) using months-long periods of observational data from 66 locations across the US. …”
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Validation of Deep Learning–Based Automatic Retinal Layer Segmentation Algorithms for Age-Related Macular Degeneration with 2 Spectral-Domain OCT Devices by Souvick Mukherjee, PhD, Tharindu De Silva, PhD, Cameron Duic, BS, Gopal Jayakar, BS, Tiarnan D.L. Keenan, BM BCh, PhD, Alisa T. Thavikulwat, MD, Emily Chew, MD, Catherine Cukras, MD, PhD

“…Four hundred two SD-OCT scans were used in this study. Methods: We evaluate 2 separate state-of-the-art segmentation algorithms through a training process using images obtained from 1 OCT device (Heidelberg-Spectralis) and subsequent testing using images acquired from 2 OCT devices (Heidelberg-Spectralis and Zeiss-Cirrus). …”
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A Comprehensive Benchmarking Framework for Sentinel-2 Sharpening: Methods, Dataset, and Evaluation Metrics by Matteo Ciotola, Giuseppe Guarino, Antonio Mazza, Giovanni Poggi, Giuseppe Scarpa

“…This dataset features diverse geographical regions, land cover types, and acquisition conditions, ensuring robust training and testing scenarios. The performance of the sharpening methods is assessed using both reference-based and no-reference quality indexes, highlighting strengths, limitations, and open challenges of current state-of-the-art algorithms. …”
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A Mold Damage Monitoring Algorithm for Power Metallurgy Molding Machines Using Bidirectional Long Short-Term Memory on an Internet of Things Platform by Hao-Pu Lin, Yuan-Chieh Chen, Chin-Chuan Han, Yu-Chi Wu, Jin-Yuan Lin

“…In this paper, an analysis and monitoring algorithm is proposed for mold health evaluation using vibration data. …”
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Detection of dental caries under fixed dental prostheses by analyzing digital panoramic radiographs with artificial intelligence algorithms based on deep learning methods by Betül Ayhan, Enes Ayan, Saadet Atsü

“…Deep learning algorithms can analyze datasets of dental images, such as panoramic radiographs to accurately identify and classify carious lesions. …”
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Impact of Channel and System Parameters on Performance Evaluation of Frequency Extrapolation Using Machine Learning by Michael Neuman, Daoud Burghal, Andreas F. Molisch

“…We also consider both complex and magnitude normalized mean-square error (NMSE) as training and evaluation metrics. Physical interpretations of the obtained results are given. …”
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Evaluation of the elastic modulus of pavement layers using different types of neural networks models by M. M.M. Elshamy, A. N. Tiraturyan, E. V. Uglova

“…Based on the performance parameters, it was concluded that among these algorithms, the feed-forward model has a better performance compared to the other three ANN types. …”
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Evaluation and use of in-silico structure-based epitope prediction with foot-and-mouth disease virus. by Daryl W Borley, Mana Mahapatra, David J Paton, Robert M Esnouf, David I Stuart, Elizabeth E Fry

“…To do this we constructed a simple objective metric to measure the sensitivity and discrimination of such algorithms. After optimising the parameters for five methods using an independent training set we used this measure to evaluate the methods. …”
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