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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Iterative sure independence screening EM-Bayesian LASSO algorithm for multi-locus genome-wide association studies. by Cox Lwaka Tamba, Yuan-Li Ni, Yuan-Ming Zhang

“…This method is referred to as ISIS EM-BLASSO algorithm. Monte Carlo simulation studies validated the new method, which has the highest empirical power in QTN detection and the highest accuracy in QTN effect estimation, and it is the fastest, as compared with efficient mixed-model association (EMMA), smoothly clipped absolute deviation (SCAD), fixed and random model circulating probability unification (FarmCPU), and multi-locus random-SNP-effect mixed linear model (mrMLM). …”
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A novel lightweight multi-scale feature fusion segmentation algorithm for real-time cervical lesion screening by Jiahui Yang, Ying Zhang, Wenlong Fan, Jie Wang, Xinhe Zhang, Chunhui Liu, Shuang Liu, Linyan Xue

“…Therefore, a lightweight algorithm segmentation for cervical lesion real-time screening system is urgently needed. …”
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XGBoost Algorithm for Cervical Cancer Risk Prediction: Multi-dimensional Feature Analysis by Sudi Suryadi, Masrizal

“…This study is situated at the intersection of clinical oncology and computational intelligence, exploring the potential of gradient-boosting algorithms to overcome the limitations of conventional screening methodologies. …”
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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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Cost-effectiveness analysis of MASLD screening using FIB-4 based two-step algorithm in the medical check-up by Mimi Kim, Huiyul Park, Eileen L. Yoon, Ramsey Cheung, Donghee Kim, Hye-Lin Kim, Dae Won Jun

“…We constructed a hybrid model of the decision tree model and Markov model to compare expected costs and quality-adjusted life-years (QALYs) between ‘screening’ and ‘no screening’ groups from healthcare system perspectives. …”
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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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Automated Audit and Self-Correction Algorithm for Seg-Hallucination Using MeshCNN-Based On-Demand Generative AI by Sihwan Kim, Changmin Park, Gwanghyeon Jeon, Seohee Kim, Jong Hyo Kim

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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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Exploratory Study on Screening Chronic Renal Failure Based on Fourier Transform Infrared Spectroscopy and a Support Vector Machine Algorithm by Yushuai Yuan, Li Yang, Rui Gao, Cheng Chen, Min Li, Jun Tang, Xiaoyi Lv, Ziwei Yan

“…The samples were input into the SVM after division by the Kennard–Stone (KS) algorithm. Compared with other models, the SVM optimized by a grid search (GS) algorithm performed the best. …”
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Empowering Portable Age-Related Macular Degeneration Screening: Evaluation of a Deep Learning Algorithm for a Smartphone Fundus Camera by Ashish Sharma, Taraprasad Das, Bryan Ong, Florian Mickael Savoy, Divya Parthasarathy Rao, Jun Kai Toh, Anand Sivaraman

“…The model was designed to indicate the presence of referable AMD (intermediate and advanced AMD). …”
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To Determine the Risk-Based Screening Interval for Diabetic Retinopathy: Development and Validation of Risk Algorithm from a Retrospective Cohort Study by Jinxiao Lian, Ching So, Sarah Morag McGhee, Thuan-quoc Thach, Cindy Lo Kuen Lam, Colman Siu Cheung Fung, Alfred Siu Kei Kwong, Jonathan Cheuk Hung Chan

“…Methods The retrospective cohort data from 117,418 subjects who received systematic DR screening in Hong Kong between 2010 and 2016 were included to develop and validate the risk algorithm using a parametric survival model. …”
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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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Suicide Risk Screening in Jails: Protocol for a Pilot Study Leveraging the Mental Health Research Network Algorithm and Health Care Data by Erin B Comartin, Grant Victor, Athena Kheibari, Brian K Ahmedani, Bethany Hedden-Clayton, Richard N Jones, Ted R Miller, Jennifer E Johnson, Lauren M Weinstock, Sheryl Kubiak

“…We hypothesize that a combination of intake screening PAU and the ML model will be the optimal approach, in that the combination will be more accurate and can have practical application in this context. …”
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Improving the performance of machine learning algorithms for detection of individual pests and beneficial insects using feature selection techniques by Rabiu Aminu, Samantha M. Cook, David Ljungberg, Oliver Hensel, Abozar Nasirahmadi

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ALGORITHM OF DIAGNOSTICS AND TREATMENT OF AN AGE-RELATED MACULAR DEGENERATION AT PATIENTS WITH CHRONIC PERIPHERAL UVEITIS by Yu. I. Khoroshikh, O. I. Krivosheina, Ye. V. Melekhin

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Study Design and Rationale for the PHINDER Study: Pulmonary Hypertension Screening in Patients with Interstitial Lung Disease for Earlier Detection by Tejaswini Kulkarni, David A. Zisman, Oksana A. Shlobin, David G. Kiely, Maral DerSarkissian, Eric Shen, Kevin M. Maher, Meredith Broderick, Mary Beth Scholand

“…Planned Outcomes Following study completion, statistical tools will be used to derive a practical model for a screening algorithm using the variables identified in the study as most predictive of PH in patients with ILD. …”
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Computationally assisted screening and design of cell-interactive peptides by a cell-based assay using peptide arrays and a fuzzy neural network algorithm by Chiaki Kaga, Mina Okochi, Yasuyuki Tomita, Ryuji Kato, Hiroyuki Honda

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