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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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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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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Rapid screening and optimization of CO2 enhanced oil recovery operations in unconventional reservoirs: A case study by Shuqin Wen, Bing Wei, Junyu You, Yujiao He, Qihang Ye, Jun Lu

“…Based on the results of model interpretability, the genetic algorithm (GA) was coupled with RF (RF-GA model) to optimize the CO2-EOR process. …”
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Leveraging ECG images for predicting ejection fraction using machine learning algorithms by Abhyuday Kumara Swamy, Vivek Rajagopal, Deepak Krishnan, Paramita Auddya Ghorai, Anagha Choukhande, Santhosh Rathnam Palani, Deepak Padmanabhan, Emmanuel Rupert, Devi Prasad Shetty, Pradeep Narayan

“…Conclusions: Actual images of ECGs with simple pre-processing and model architecture can be used as a reliable tool to screen for LVD. …”
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An improved algorithm of segmented orthogonal matching pursuit based on wireless sensor networks by Xinmiao Lu, Yanwen Su, Qiong Wu, Yuhan Wei, Jiaxu Wang

“…Aiming at the problems of low data reconstruction accuracy in wireless sensor networks and users unable to receive accurate original signals, improvements are made on the basis of the stagewise orthogonal matching pursuit algorithm, combined with sparseness adaptation and the pre-selection strategy, which proposes a sparsity adaptive pre-selected stagewise orthogonal matching pursuit algorithm. …”
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Advancing Diabetic Retinopathy Screening: A Systematic Review of Artificial Intelligence and Optical Coherence Tomography Angiography Innovations by Alireza Hayati, Mohammad Reza Abdol Homayuni, Reza Sadeghi, Hassan Asadigandomani, Mohammad Dashtkoohi, Sajad Eslami, Mohammad Soleimani

“…In comparison to conventional ML techniques, our results indicated that DL algorithms significantly improve the accuracy, sensitivity, and specificity of DR screening. …”
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Machine learning based screening of biomarkers associated with cell death and immunosuppression of multiple life stages sepsis populations by Jie Yang, Fanyan Ou, Binbin Li, Lixiong Zeng, Qiuli Chen, Houyu Gan, Jianing Yu, Qian Guo, Jihua Feng, Jianfeng Zhang

“…Nine machine learning algorithms (Logistic Regression LR, Decision Tree DT, Gradient Boosting Machine GBM, K-Nearest Neighbors KNN, LASSO, Principal Component Analysis PCA, Random Forest RF, Support Vector Machine SVM, and XGBoost) were applied to training and testing datasets with 10-fold cross-validation to select three optimized algorithm models. …”
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