Single-index logistic model for high-dimensional group testing data by Changfu Yang, Wenxin Zhou, Wenjun Xiong, Junjian Zhang, Juan Ding

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The Utility of Follow-up Transthoracic Echocardiogram to Screen for Severe Portopulmonary Hypertension (POPH) in Patients Granted POPH Model for End-stage Liver Disease (MELD) Exce... by Kathryn T. del Valle, MD, Dana Kay, MD, Michael J. Krowka, MD, James R. Runo, MD, Corey Sadd, MD, Julie K. Heimbach, MD, Rodrigo Cartin-Ceba, MD, Hector R. Cajigas, MD, Charles D. Burger, MD, John E. Moss, MD, Hilary M. DuBrock, MD

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i-DENV: development of QSAR based regression models for predicting inhibitors targeting non-structural (NS) proteins of dengue virus by Sakshi Gautam, Anamika Thakur, Manoj Kumar

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Retrospective validation of the postnatal growth and retinopathy of prematurity criteria in a Chinese cohort by Li Li, Yanlin Gao, Yuhan Lu, Wei Chen, Mei Han

“…Application of the G-ROP prediction model can improve the sensitivity and specificity of ROP screening. …”
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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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Screening risk factors for the occurrence of wedge effects in intramedullary nail fixation for intertrochanteric fractures in older people via machine learning and constructing a p... by Zhe Xu, Qiuhan Chen, Zhi Zhou, Jianbo Sun, Guang Tian, Chen Liu, Guangzhi Hou, Ruguo Zhang

“…The purpose of this study was to screen risk factors for the intraoperative V-effect in intertrochanteric fractures and to develop a clinical prediction model. …”
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Preventing Stillbirth: A Review of Screening and Prevention Strategies by Laure Noël, Conrado Milani Coutinho, Basky Thilaganathan, Yiyuan Jiang, Dandan Shi

“…More recently, the first-trimester combined screening algorithm developed by the Fetal Medicine Foundation has emerged as a better tool to predict and prevent early-onset placental dysfunction and its main outcomes of preterm preeclampsia, fetal growth restriction and stillbirth by the appropriate use of Aspirin therapy, serial growth scans and induction of labour from 40 weeks for women identified at high-risk by such screening. …”
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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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Comprehensive quality assessment of 296 sweetpotato core germplasm in China: A quantitative and qualitative analysis by Chaochen Tang, Yi Xu, Rong Zhang, Xueying Mo, Bingzhi Jiang, Zhangying Wang

“…Near-infrared spectroscopy, combined with a random forest algorithm, enabled rapid screening of superior germplasm, achieving prediction accuracies of 97 % for stem tips and 98 % for roots. …”
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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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Synergistic coupling of ultrasonic cavitation with tailored deep eutectic solvent systems for intensified extraction of Scutellaria Radix flavonoids: Modelling and optimization by... by Qi Cui, Jia-Yi Shi, Le-Le Wen, Wei-Hua Kong, Li-Jie Jiang, Ju-Zhao Liu

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New Perspectives on Lung Cancer Screening and Artificial Intelligence by Leonardo Duranti, Luca Tavecchio, Luigi Rolli, Piergiorgio Solli

“…Integrating AI and biomarker-driven methods offers significant promise for transforming lung cancer screening. These technologies could enable earlier, more accurate detection, ultimately improving survival outcomes. …”
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Diagnostic accuracy of artificial intelligence models in detecting congenital heart disease in the second-trimester fetus through prenatal cardiac screening: a systematic review an... by Lies Dina Liastuti, Lies Dina Liastuti, Yosilia Nursakina, Yosilia Nursakina

“…Nevertheless, prospective studies with bigger datasets and more inclusive populations are needed to compare AI algorithms to conventional methods.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?…”
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SCREENING FOR OVARIAN CANCER: REALITY AND PROSPECTS. REVIEW OF THE LITERATURE by E. V. Gerfanova, L. A. Ashrafyan, I. B. Antonova, O. I. Aleshikova, S. V. Ivashina

“…A review article presents the modern methods of screening and early diagnosis of primary ovarian cancer (OC). …”
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A machine learning based prediction model for short term efficacy of nasopharyngeal carcinoma by Qiulu Zhong, Xiangde Li, Qinghua Du, Qianfu Liang, Danjing Luo, Jiaying Wen, Haiying Yue, Wenqi Liu, Xiaodong Zhu, Jian Li

“…Three machine learning algorithms were used to construct predictive models for the short-term efficacy of LANPC. …”
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Development and validation of a predictive model for new HIV infection screening among persons 15 years and above in primary healthcare settings in Kenya: a study protocol by Simon Karanja, Amos Otieno Olwendo, Gideon Kikuvi

“…Introduction This study seeks to determine incidence, comorbidities and drivers for new HIV infections to develop, test and validate a risk prediction model for screening for new cases of HIV.Methods and analysis The study has two components: a cross-sectional study to develop the prediction model using the HIV dataset from the Kenya AIDS and STI Control Programme and a 15-month prospective study for the validation of the model. …”
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Research on the optimization model of anti-breast cancer candidate drugs based on machine learning by Zhou Dong, Hong Chen, Yuchen Yang, Hairong Hao

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RETRACTED ARTICLE: A combined microfluidic deep learning approach for lung cancer cell high throughput screening toward automatic cancer screening applications by Hadi Hashemzadeh, Seyedehsamaneh Shojaeilangari, Abdollah Allahverdi, Mario Rothbauer, Peter Ertl, Hossein Naderi-Manesh

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Unlocking The Potential of Hybrid Models for Prognostic Biomarker Discovery in Oral Cancer Survival Analysis: A Retrospective Cohort Study by Leila Nezamabadi Farahani, Anoshirvan Kazemnejad, Mahlagha Afrasiabi, Leili Tapak

“…Concordance index (C-index), mean absolute error (MAE), mean squared error (MSE) and R-squares, were used to evaluate the performance of the models using selected features. Functional enrichment analysis was performed using DAVID database, and external validation utilized three independent datasets (GSE9844, GSE75538, GSE37991, GSE42743).Results: The findings indicated that the PSO-based method outperformed the GA-based method, achieving a smaller MAE (0.061) and MSE (0.005), R-square (0.99) and C-index (0.973), selecting 291 probes from 1069 screened. …”
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