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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Improvement of the Diagnostics of the Fetus Heart Anomalies During a Routine Screening Ultrasound Examination by Markin L., Medvjedjeva O.

“…In our opinion, the prenatal detection of congenital heart defects strongly depends on the algorithm of conducting a fetal heart study in the screening regimen. …”
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Short-Term Photovoltaic Power Combined Prediction Based on Feature Screening and Weight Optimization by Liqing Geng, Yadong Yang, Genghuang Yang, Yongfeng Zheng, Xiaocong Liu

“…Aiming at the problem of low prediction accuracy caused by the intermittent and fluctuating characteristics of photovoltaic power, a short-term photovoltaic power combined prediction method based on feature screening and weight optimization is proposed. Firstly, K-means is used to cluster the photovoltaic power; Secondly, CEEMDAN is used to decompose photovoltaic power and wavelet decomposition is used to decompose irradiance, and sample entropy and K-means are used to reconstruct each component of photovoltaic power into high, intermediate, and low frequency terms; Then, Spearman’s correlation coefficient is used to calculate the correlation between each meteorological factor and the decomposed irradiance component and the high, intermediate, and low frequency terms of photovoltaic power, and the feature selection is carried out; Then, CNN-BiLSTM-Attention is used to predict the high frequency term, LSTM is used to predict the intermediate frequency and low frequency terms, and the results are superimposed to obtain the preliminary prediction value; Finally, the dung beetle algorithm is used to optimize the weights of the initial prediction values of the training set of high, intermediate, and low frequency terms, and the optimal weight is substituted into the test set to obtain the final prediction result. …”
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Design and evaluation of screening and self-care (mobile) application for oral and dental problems and emergencies by Sedighe Sadat Hashemikamangar, Aidin Sooratgar, Mina Khayamzadeh, Shayan Momeni, Ali Asghar Safaei, Behnaz Behniafar

“…Results: The evaluation results showed that more than 90 % of specialists had a positive attitude towards application effectiveness. …”
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Lightweight Detection Algorithm for Breast-Mass Features in Ultrasound Images by Taojuan Li, Wen Liu, Mingxian Song, Zheng Gu, Ling Hai

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Domain name generation algorithm based on improved Markov chain by QIAN Zhiye, LI Xue, LI Suogang

“…Then, the improved Markov model algorithm was used to analyze the filtered data, and new subdomain names were generated and added to the result set. …”
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Laryngeal cancer diagnosis based on improved YOLOv8 algorithm by Xin Nie, Xueyan Zhang, Di Wang, Yuankun Liu, Lumin Xing, Wenjian Liu

“…A novel multiscale enhanced convolution module has been introduced to improve the model’s feature extraction capabilities for small-sized targets. …”
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Electricity Load Forecasting Method Based on the GRA-FEDformer Algorithm by Xin Jin, Tingzhe Pan, Heyang Yu, Zongyi Wang, Wangzhang Cao

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Blinded Validation of Breath Biomarkers of Lung Cancer, a Potential Ancillary to Chest CT Screening. by Michael Phillips, Thomas L Bauer, Renee N Cataneo, Cassie Lebauer, Mayur Mundada, Harvey I Pass, Naren Ramakrishna, William N Rom, Eric Vallières

“…Outcome modeling: We modeled the expected effects of combining breath biomarkers with chest CT on the sensitivity and specificity of lung cancer screening.…”
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Application of Artificial Intelligence Algorithms in the Field of Antimicrobial Peptide Prediction by QIAN Yuchen, NIE Ting, HUA Yanming, XU Shiying, GUO Sheng, ZHANG Xin, LUO Xiaohu, LIU Yanan

“…Currently, several specialized databases have been established, providing rich resources for algorithmic model training. Furthermore, multi-source bioinformatics data such as genomics, transcriptomics and proteomics are also widely used to predict antimicrobial peptides, with a view to identifying peptides with potential antimicrobial activity more accurately. …”
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Analysis of E-Commerce Marketing Strategy Based on Xgboost Algorithm by Hong Chen, Wei Wan

“…This paper reviews the current literature on e-commerce marketing and then analyzes the feasibility of precision marketing in e-commerce market in the new media era. In order to screen potential consumers and improve the success rate of precision marketing, this paper establishes a prediction model for precision marketing of bank credit cards. …”
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Leveraging ensemble convolutional neural networks and metaheuristic strategies for advanced kidney disease screening and classification by Abeer saber, Esraa Hassan, Samar Elbedwehy, Wael A. Awad, Tamer Z. Emara

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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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Artificial intelligence for screening and early diagnosis of pancreatic neoplasms in the context of centralization of the laboratory service in the region by S. I. Panin, V. A. Suvorov, A. V. Zubkov, S. A. Bezborodov, A. A. Panina, N. V. Kovalenko, A. R. Donsckaia, I. G. Shushkova, A. V. Bykov, Ya. A. Marenkov

“…Determination of the optimal machine learning model for the creation of software for screening and early diagnosis of pancreatic neoplasms in the context of centralization of the laboratory service in the region. …”
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A Novel Method for Screening the PMU Phase Angle Difference Data Based on Hyperplane Clustering by Ancheng Xue, Shuang Leng, Yecheng Li, Feiyang Xu, Kenneth E. Martin, Jingsong Xu

“…First, we develop the hyperplane cluster method to cluster the phase angle difference data. Second, in order to screen out the right data type, this paper compares the virtual reactance parameters of each data type obtained by voltage mean to the line reactance parameter given by the system model. …”
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The urgency of the androgenic screening for men who underwent preventive medical examination for prostate diseases detection by A. A. Kamalov, M. Ye. Chaly, R. P. Vasilevsky

“…The bad influence of the androgenic insufficiency for men defines the need for obligatory androgenic screening of more than 50 years old patients. Testosterone level was examined. …”
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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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Screening OSA in Chinese Smart Device Consumers: A Real-World Arrhythmia-Related Study by Chen Y, Zhang H, Li J, Xu P, Guo Y, Xie L

“…Our previous study validated an algorithm-based photoplethysmography (PPG) smartwatch for OSA risk detection.Objective: This study aimed to characterize OSA features and assess its association with arrhythmia risk among smart wearable device (SWD) consumers in China in a real-world setting.Methods: Between December 15, 2019, and January 31, 2022, SWD consumers across China were screened for OSA risk using HUAWEI devices. …”
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