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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Socially Responsible Investment Portfolio Construction with a Double-Screening Mechanism considering Machine Learning Prediction by Jun Zhang, Xuedong Chen

“…The proposed models consist of two stages, i.e., stock screening and asset allocation. …”
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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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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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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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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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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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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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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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Mortality impact, risks, and benefits of general population screening for ovarian cancer: the UKCTOCS randomised controlled trial by Usha Menon, Aleksandra Gentry-Maharaj, Matthew Burnell, Andy Ryan, Jatinderpal K Kalsi, Naveena Singh, Anne Dawnay, Lesley Fallowfield, Alistair J McGuire, Stuart Campbell, Steven J Skates, Mahesh Parmar, Ian J Jacobs

“…Screening itself did not cause anxiety unless more intense repeat testing was required following abnormal screens. …”
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Discovery, Biological Evaluation and Binding Mode Investigation of Novel Butyrylcholinesterase Inhibitors Through Hybrid Virtual Screening by Lizi Li, Puchen Zhao, Can Yang, Qin Yin, Na Wang, Yan Liu, Yanfang Li

“…This study employed a quantitative structure–activity relationship (QSAR) model based on ECFP4 molecular fingerprints with several machine learning algorithms (XGBoost, RF, SVM, KNN), among which the XGBoost model showed the best performance (AUC = 0.9740). …”
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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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Identifying USP1 Inhibitors with Allosteric Effect on Its Triple Catalytic Center through Virtual Screening by Jinhong Xu, Yongxia Li, Tao Jiang, Yi Zhu, Jinyan Zhu, Tao Xu, Longji Fang, Zujun Hong, Yuying Jia, Fang Bao

“…In this study, we performed virtual screening on a database containing about 1.37 million molecules using the pharmacophore model, multiple precision molecular docking algorithms, molecular mechanics/generalized born surface area (MM/GBSA), strain energy, and ADMET screening methods. …”
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Screening of endoplasmic reticulum stress characteristic genes and immune infiltration manifestations in chronic obstructive pulmonary disease by ZHANG Shuang, LUO Chenyang, HE Zhiyi

“…Three machine learning algorithms, LASSO, SVM-RFE, and RF, were used to screen the characteristic genes, and their diagnostic performance was verified and evaluated in the GSE10006. …”
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Machine Learning Model for Early Detection of COVID-19 by Heart Rhythm Abnormalities by M. S. Mezhov, V. O. Kozitsin, Iu. D. Katser

“…The work aims at creating a mathematical model based on machine learning algorithms to automate the process of detecting covid abnormalities in the heart rhythm. …”
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Development and evaluation of a mobile-optimized daily self-rating depression screening app: A preliminary study. by Kyungmi Chung, Min-Jeong Jeon, Jaesub Park, San Lee, Chang Oh Kim, Jin Young Park

“…Therefore, the K-CESD-R Mobile app using algorithm (B) could be a more potential candidate for a depression screening tool than the K-CESD-R Mobile app using algorithm (A).…”
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A machine learning algorithm to increase COVID-19 inpatient diagnostic capacity. by David Goodman-Meza, Akos Rudas, Jeffrey N Chiang, Paul C Adamson, Joseph Ebinger, Nancy Sun, Patrick Botting, Jennifer A Fulcher, Faysal G Saab, Rachel Brook, Eleazar Eskin, Ulzee An, Misagh Kordi, Brandon Jew, Brunilda Balliu, Zeyuan Chen, Brian L Hill, Elior Rahmani, Eran Halperin, Vladimir Manuel

“…The algorithm was based on basic demographic and laboratory features to serve as a screening tool at hospitals where testing is scarce or unavailable. …”
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Adaptive Estimation Algorithm for Photoplethysmographic Heart Rate Based on Finite State Machine by Ting Lan, Yanan Bie, Dong Hai, Jun Zhong

“…The results of the experiment show that compared with other dominant algorithms, the proposed algorithm estimates heart rate with a smaller mean absolute error and can extract heart rate more effectively.…”
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HMCFormer (hierarchical multi-scale convolutional transformer): a hybrid CNN+Transformer network for intelligent VIA screening by Bo Feng, Chao Xu, Zhengping Li, Chuanyi Zhang

“…This will attract more low-income women to volunteer for regular cervical cancer screening. …”
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