Development and validation of multimodal deep learning algorithms for detecting pulmonary hypertension by Wei Zhao, Zhihua Huang, Xiaolin Diao, Zhan Yang, Zhihui Zhao, Yun Xia, Qing Zhao, Zhaohong Sun, Qunying Xi, Yanni Huo, Ou Xu, Jiahui Geng, Xin Li, Anqi Duan, Sicheng Zhang, Luyang Gao, Yijia Wang, Sicong Li, Qin Luo, Zhihong Liu

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Predicting algorithm of attC site based on combination optimization strategy by Zhendong Liu, Xi Chen, Dongyan Li, Xinrong Lv, Mengying Qin, Ke Bai, Zhiqiang He, Yurong Yang, Xiaofeng Li, Qionghai Dai

“…Based on the structural features of attC sites, the prediction algorithm realises the high-precision prediction of the recombination frequencies between sites and the screening of the top 20 important features that play a role in recombination, which are effective for improving the design method of attC sites. …”
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Characterization of lactylation modification subtypes and the promoting role of CCL20 in hepatocellular carcinoma progression by Li-Hong Wu, Liu Yang, Xiang-Xu Wang, Shuang Bai, Xi Yan, Jing Wei, Jun Wang, Fei Tian

“…The CIBERSORT algorithm was utilized to analyze immune cell infiltration. …”
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MLP-UNet: an algorithm for segmenting lesions in breast and thyroid ultrasound images by Tian-feng Dong, Chang-jiang Zhou, Zhen-yi Huang, Hao Zhao, Xue-long Wang, Shi-ju Yan

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Glypican-3 regulated epithelial mesenchymal transformation-related genes in osteosarcoma: based on comprehensive tumor microenvironment profiling by Jiaming Zhang, Wei Wang

“…The least absolute shrinkage and selection operator (LASSO) algorithm was applied to screen candidate genes for developing a prognostic model. …”
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Identification of potential pathogenic genes associated with the comorbidity of rheumatoid arthritis and renal fibrosis using bioinformatics and machine learning by Jiao Qiu, Yalin Xu, Luyuan Tong, Xingchun Yang, Xiao Wu

“…Subsequently, functional enrichment analysis was performed to clarify the biological functions of these genes. Machine learning algorithms were used to screen for the hub RA-RF differential expression genes, and then a Logistic Regression (LR) model was constructed. …”
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Genome-wide expression in human whole blood for diagnosis of latent tuberculosis infection: a multicohort research by Fan Jiang, Fan Jiang, Fan Jiang, Yanhua Liu, Linsheng Li, Linsheng Li, Ruizi Ni, Ruizi Ni, Yajing An, Yajing An, Yufeng Li, Yufeng Li, Lingxia Zhang, Wenping Gong

“…A Naive Bayes (NB) model incorporating these two markers demonstrated robust diagnostic performance: training set AUC: median = 0.8572 (inter-quartile range 0.8002, 0.8708), validation AUC = 0.5719 (0.51645, 0.7078), and subgroup AUC = 0.8635 (0.8212, 0.8946).ConclusionOur multicohort analysis established an NB-based diagnostic model utilizing S100A12/S100A8, which maintains diagnostic accuracy across diverse geographic, ethnic, and clinical variables (including HIV co-infection), highlighting its potential for clinical translation in LTBI/ATB differentiation.…”
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High-throughput screening and machine learning classification of van der Waals dielectrics for 2D nanoelectronics by Yuhui Li, Guolin Wan, Yongqian Zhu, Jingyu Yang, Yan-Fang Zhang, Jinbo Pan, Shixuan Du

“…Here, we employed a topology-scale algorithm to screen vdW materials consisting of zero-dimensional (0D), one-dimensional (1D), and 2D motifs from Materials Project database. …”
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Analysis and Prediction of CET4 Scores Based on Data Mining Algorithm by Hongyan Wang

“…In order to detect potential risk graduating students earlier, this paper proposes an appropriate and timely early warning and preschool K-nearest neighbor algorithm classification model. Taking test scores or make-up exams and re-learning as input features, the classification model can effectively predict ordinary students who have not graduated.…”
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Birdsong Recognition Based on Attention Hash Algorithm Combined with Contrastive Loss by WANG Yuwei, CHEN Aibin, ZHOU Guoxiong, ZHANG Zhiqiang

“…Aiming at the problems of length misalignment, redundancy, noise and large intra-class differences in birdsong data collected in the natural environment, an automatic birdsong recognition model composed of a two-stage hash algorithm based on multi- level attention and a lightweight classifier based on fusion contrastive loss is proposed. …”
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Machine learning prediction model with shap interpretation for chronic bronchitis risk assessment based on heavy metal exposure: a nationally representative study by Tiansheng Xia, Kaiyu Han

“…Methods Weighted logistic regression was used to assess the association of 14 blood and urine heavy metals with CB based on nationally representative samples from the 2005–2015 National Health and Nutrition Examination Survey (NHANES). The Boruta algorithm was further applied to screen the characteristic variables and construct 10 ML models. …”
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Analysis of imaging differences between high-resolution CT and digital radiography chest films in pneumoconiosis screening by Lijuan LIU, Fenghong WANG

“…HRCT enables systematic observation of the evolution and progression of pneumoconiosis, providing reliable evidence for diagnosis.ObjectiveTo provide reliable evidences for the early screening of pneumoconiosis, By analyzing the imaging difference between HRCT and DR chestfilms in pneumoconiosis screening.MethodsSix casting workers in a casting forging company suspected of early stage of pneumoconiosis through regular occupational health examination screening were recruited , and 64 rows of spiral CT thin layer were scanned and reconstructed by high-resolution bone algorithm. …”
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Cost-effectiveness of advanced hepatic fibrosis screening in individuals with suspected MASLD identified by serologic noninvasive tests by Huiyul Park, Eileen L. Yoon, Mimi Kim, Ji-hyeon Park, Ramsey Cheung, Jeong-Yeon Cho, Hye-Lin Kim, Dae Won Jun

“…We applied a decision tree and Markov model from a healthcare system perspective to estimate life-years, quality-adjusted life-years (QALYs), costs, and the incremental cost-effectiveness ratio (ICER) for screening versus no screening in the United States. …”
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Virtual Screening of Conjugated Polymers for Organic Photovoltaic Devices Using Support Vector Machines and Ensemble Learning by Fang-Chung Chen

“…Additionally, the predictive performance could be further improved by “blending” the results of the SVM and random forest models. The resulting ensemble learning algorithm might open up a new opportunity for more precise, high-throughput virtual screening of conjugated polymers for OPV devices.…”
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Mitochondrial autophagy-related gene signatures associated with myasthenia gravis diagnosis and immunity by Shan Jin, Junbin Yin, Wei Li, Ni Mao

“…Multiple machine learning algorithms were applied to screen and verify the diagnostic genes of intersection genes. …”
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Machine Learning-Assisted NIR Spectroscopy for Dynamic Monitoring of Leaf Potassium in Korla Fragrant Pear by Mingyang Yu, Weifan Fan, Junkai Zeng, Yang Li, Lanfei Wang, Hao Wang, Feng Han, Jianping Bao

“…By measuring leaf potassium content at the fruit setting, expansion, and maturity stages (decreasing from 1.60% at fruit setting to 1.14% at maturity), this study reveals its dynamic change pattern and establishes a high-precision prediction model by combining near-infrared spectroscopy (NIRS) with machine learning algorithms. …”
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Review of Josh Simons’ Book "Algorithms for the People – Democracy in the Age of AI" by Thomas Klikauer

“… Increasingly, artificial intelligence, algorithms and machine learning models guide what Internet users see and read on their screens. …”
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Prediction of hypertensive disorders in pregnant women in the «gray» risk zone following combined first-trimester screening by N. V. Mostova, V. V. Kovalev, E. V. Kudryavtseva

“…Aim: to develop a prognostic model for risk stratification in female patients with borderline to high developing PE risk based on combined first-trimester screening.   …”
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Changed definition of disease and broader screening criteria had little impact on prevalence of gestational diabetes mellitus by Lina Grønvall, Finn Egil Skjeldestad

“…Conclusions The introduction of broader screening criteria and a more liberal case definition increased the population eligible for GDM screening by 45%. …”
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AI-based Assessment of Risk Factors for Coronary Heart Disease in Patients With Diabetes Mellitus and Construction of a Prediction Model for a Treatment Regimen by Zhen Gao, Qiyuan Bai, Mingyu Wei, Hao Chen, Yan Yan, Jiahao Mao, Xiangzhi Kong, Yang Yu

“…Conclusions: Using machine-learning algorithms, we built a prediction model of a treatment plan for patients with concomitant DM and CHD by integrating patients' information and screened the best feature set containing 15 features, which provides help and strategies to develop the best treatment plan for patients with concomitant DM and CHD.…”
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