Liquid chromatography-mass spectrometry-based metabolic panels characteristic for patients with prostate cancer and prostate-specific antigen levels of 4–10 ng/mL by Chen Wang, Ting Chen, Teng-Fei Gu, Sheng-Ping Hu, Yong-Tao Pan, Jie Li

“…Based on the identified metabolites, LASSO regression was applied for variable selection, and logistic regression and support vector machine models were developed. Results: The LASSO algorithm’s ability to select variables effectively reduced redundant features and minimized model overfitting. …”
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Validation of artificial intelligence algorithm LuxIA for screening of diabetic retinopathy from a single 45° retinal colour fundus images: the CARDS study by Juan Donate-Lopez, Rodrigo Abreu-Gonzalez, Sandro De Zanet, Jose Juan Escobar-Barranco, Carlos Ciller, Stefanos Apostolopoulos, Gabriela Susanna-González, Joseph P M Blair, Romina M Lasagni Vitar, José Natán Rodríguez Martín, Carlos Bermúdez, Alfonso Luis Calle Pascual, Elena Rigo, Enrique Cervera Taulet, Rosario Cobo-Soriano

“…Objective This study validated the artificial intelligence (AI)-based algorithm LuxIA for screening more-than-mild diabetic retinopathy (mtmDR) from a single 45° colour fundus image of patients with diabetes mellitus (DM, type 1 or type 2) in Spain. …”
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Preference-based expensive multi-objective optimization without using an ideal point by Peipei Zhao, Liping Wang, Qicang Qiu

“…The Gaussian process model is built on the objective functions. In the model-based optimization, the projection distance with upper confidence bound (UCB) is developed as the fitness of solutions for each subproblem. …”
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Treatment decision algorithms for tuberculosis screening and diagnosis in children below 5 years hospitalised with severe acute malnutrition: a cost-effectiveness analysisResearch... by Marc d’Elbée, Nyashadzaishe Mafirakureva, Chishala Chabala, Minh Huyen Ton Nu Nguyet, Martin Harker, Clémentine Roucher, Gerald Businge, Perfect Shankalala, Bwendo Nduna, Veronica Mulenga, Maryline Bonnet, Eric Wobudeya, Olivier Marcy, Peter J. Dodd

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Global miniaturization of broadband antennas by prescreening and machine learning by Slawomir Koziel, Anna Pietrenko-Dabrowska, Ubaid Ullah

“…Our technique includes parameter space pre-screening and the iterative refinement of kriging surrogate models using the predicted merit function minimization as an infill criterion. …”
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Applications of Artificial Intelligence in Drug Repurposing by Zhaoman Wan, Xinran Sun, Yi Li, Tianyao Chu, Xueyu Hao, Yang Cao, Peng Zhang

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The Bridge between Screening and Assessment: Establishment and Application of Online Screening Platform for Food Risk Substances by Kang Hu, Shaoming Jin, Hong Ding, Jin Cao

“…The screening comparison algorithm, the core of the screening model, is obtained through the improvement of the existing spectral library search algorithm. …”
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Screening for endometriosis: A scoping review of screening measures that could support early diagnosis by Brittany N. Rosenbloom, Tania Di Renna, Adriano Nella, Mathew Leonardi, Maggie Tiong, Seungmin Lee, Rachael Bosma

“…Despite reporting symptoms, women wait around 11 years before receiving a diagnosis, further interfering with their mental and physical health. Patient reported screening measures can promote faster diagnosis, however their measurement quality remains unknown. …”
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Advancements in biomarkers and machine learning for predicting of bronchopulmonary dysplasia and neonatal respiratory distress syndrome in preterm infants by Hanieh Talebi, Seyed Alireza Dastgheib, Maryam Vafapour, Reza Bahrami, Mohammad Golshan-Tafti, Mahsa Danaei, Sepideh Azizi, Amirhossein Shahbazi, Melina Pourkazemi, Maryam Yeganegi, Amirmasoud Shiri, Ali Masoudi, Heewa Rashnavadi, Hossein Neamatzadeh

“…For nRDS, biomarkers such as the lecithin/sphingomyelin (L/S) ratio and oxidative stress indicators have been effectively used in innovative diagnostic methods, including attenuated total reflectance Fourier transform infrared spectroscopy (ATR-FTIR) and high-content screening for ABCA3 modulation. Machine learning algorithms like Partial Least Squares Regression (PLSR) and C5.0 have shown potential in accurately identifying critical health indicators. …”
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基于脑影像及临床特征的机器学习模型预测缺血性卒中后心房颤动 A Machine Learning Model Based on Brain Imaging and Clinical Features for Predicting Atrial Fibrillation Detected after Stroke... by 张栗源1，刘涛2，姜勇1，李子孝1，3，王拥军1，3，杨晓萌1，3(ZHANG Liyuan1, LIU Tao2, JIANG Yong1, LI Zixiao1,3, WANG Yongjun1,3, YANG Xiaomeng1,3 )

“…After retaining independent features, the least absolute shrinkage and selection operator (LASSO) regression algorithm was used for feature selection and to construct a joint prediction model. …”
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Identification of potential biomarkers for 2022 Mpox virus infection: a transcriptomic network analysis and machine learning approach by Joy Prokash Debnath, Kabir Hossen, Sabrina Bintay Sayed, Md. Sayeam Khandaker, Preonath Chondrow Dev, Saifuddin Sarker, Tanvir Hossain

“…Intriguingly, 13 key DEGs were identified across hubs and clusters, highlighting their aberrant expressions in cell cycle regulation, immune responses, and cancer pathways. Biomarker screening via Random Forest (RF) model (selected with PyCaret from multiple models) and validation through t-distributed stochastic neighbor embedding (t-SNE) algorithm, principal component analysis (PCA), and ROC curve analysis employing Logistic Regression and Random Forest, identified 6 key DEGs (TXNRD1, CCNB1, BUB1, CDC20, BUB1B, and CCNA2) as promising biomarkers (AUC > 0.7) for clade IIb infection. …”
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Design of public space guide system based on augmented reality technology by Pu Jiao, Limin Ran

“…The research is based on imaging techniques using augmented reality technology and camera image capture. Then, it uses screen error algorithms and scale-invariant feature transformation operators to test the quality of scene spatial models. …”
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A Web-Based Interface That Leverages Machine Learning to Assess an Individual’s Vulnerability to Brain Stroke by Divyansh Bhandari, Arnav Agarwal, R. Reena Roy, Rajaram Priyatharshini, Rodriguez Rivero Cristian

“…We compare a range of algorithms-including traditional classifiers and deep learning models-and report comprehensive performance metrics (accuracy, precision, recall, F1-score, and AUC-ROC) for each. …”
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Research on Characteristics and Influencing Factors of High Temperature Disaster Risk in Wuhan Based on Local Climate Zone by Shujing GUO, Li ZHANG

“…Furthermore, highly correlated LCZ types are screened out under the optimal size, the multicollinearity of all LCZ landscape pattern indices is examined and those with multicollinearity are excluded. …”
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CELIAC DISEASE SCREENING IN A LARGE DOWN SYNDROME COHORT: COMPARISON OF DIAGNOSTIC YIELD OF DIFFERENT SEROLOGICAL SCREENING TESTS by Dilek Uludağ Alkaya, Seçil Sözen, Birol Öztürk, Nuray Kepil, Tülay Erkan, Hüseyin Tufan Kutlu, Beyhan Tüysüz

“…This study aimed to estimate the prevalence of CD in DS patients and compare the diagnostic performance of the screening algorithms. Material and Method: A cohort of 1117 DS patients were included. …”
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Glitch(ing)! A refusal and gateway to more caring techno-urban worlds? by Mirjana Mitrović, Maja-Lee Voigt

“…With code connecting to concrete in ‘smart’ cities, oppressive, patriarchal, and binary architectures of the urban have been translated into their algorithmic counterparts, too. This particularly excludes people who do not conform to these inscribed norms. …”
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Visual detection of screen defects in occlusion and missing scenes by YIN Dongfu, DU Mingchen, HU Tianhao, LI Youming, ZHANG Xiaohong, YU Fei Richard

“…The YOLOv8n model is used to detect the position of mobile phone screens in images. …”
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OPTIMIZATION DESIGN OF THE INDEPENDENT WHEEL AXLE-AXLE BASED ON OSF AND RSM by YE Shuang, LIU Qiang, HUANG KunLan, FAN LiZhong, WANG Jie

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Artificial Intelligence–Enabled ECG Screening for LVSD in LBBB by Hak Seung Lee, MD, Sooyeon Lee, MD, Sora Kang, MS, Ga In Han, MS, Ah-Hyun Yoo, MS, Jong-Hwan Jang, PhD, Yong-Yeon Jo, PhD, Jeong Min Son, MD, Min Sung Lee, MD, MS, Joon-myoung Kwon, MD, MS, Kyung-Hee Kim, MD, PhD

“…Although artificial intelligence (AI)–driven ECG analysis shows promise for LVSD screening, it remains unclear if a general AI-ECG model or one tailored for LBBB patients yields better performance. …”
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Kriging-Based Variable Screening Method for Aircraft Optimization Problems with Expensive Functions by Yadong Wang, Xinyao Duan, Jiang Wang, Jin Guo, Minglei Han

“…A genetic algorithm (GA) is employed to achieve the global optimum of the log-likelihood function. …”
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