Molecular Docking: Methodological Approaches of Risk Assessment by A. Kh. Taldaev, I. D. Nikitin, R. P. Terekhov, I. A. Selivanova

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Optimization of a Coupled Neuron Model Based on Deep Reinforcement Learning and Application of the Model in Bearing Fault Diagnosis by Shan Wang, Jiaxiang Li, Xinsheng Xu, Ruiqi Wu, Yuhang Qiu, Xuwen Chen, Zijian Qiao

“…Using the SNR as the evaluation metric, the algorithm performs data screening on the replay buffer parameters before training the deep network for predicting coupled neuron model performance. …”
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Risk prediction of QTc prolongation occurrence in cancer patients treated with commonly used oral tyrosine kinase inhibitors: machine learning modeling or conventional statistical... by Hsiang-Wen Lin, Tien-Chao Lin, Chien-Ning Hsu, Tzu-Pei Yeh, Yu-Chieh Chen, Liang-Chih Liu, Chen-Yuan Lin

“…The backward LR method and seven ML algorithms were applied to train and test the prediction models. …”
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A network-based method using a random walk with restart algorithm and screening tests to identify novel genes associated with Menière's disease. by Lin Li, YanShu Wang, Lifeng An, XiangYin Kong, Tao Huang

“…To make the identified genes more reliable, a series of screening tests, including a permutation test, an interaction test and an enrichment test, were designed to select essential genes from those obtained by the RWR algorithm. …”
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A Blockchain Solution for the Internet of Vehicles with Better Filtering and Adaptive Capabilities by Xueli Shen, Runyu Ma

“…To solve this problem, we propose a gradually accelerating environment adaptive consensus algorithm, AE-PBFT, that can be applied to IoV. It includes a trust management model that achieves gradual acceleration by recording the historical continuous behavior of nodes, thereby improving the efficiency of screening nodes with different intentions, accelerating the consensus process, and reducing latency. …”
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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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Research of color models in digital graphics by Hetman Oksana, Shpetna Svitlana

“…The study focuses on a detailed examination of the RGB, CMYK, HSL/HSV, and LAB color models. It is established that the RGB model is an additive system optimized for screens and displays, as it provides a broad and vibrant color range suitable for digital applications. …”
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The use of autofluorescence stomatoscopy in the algorithm of diagnosing of the oral mucosal abnormalities of patients with tuberculosis infection by T. P. Goryacheva, D. A. Zaplutanova, I. P. Goryacheva, O. A. Aleshina

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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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Validation of artificial intelligence algorithm LuxIA for screening of diabetic retinopathy from a single 45° retinal colour fundus images: the CARDS study by Juan Donate-Lopez, Rodrigo Abreu-Gonzalez, Sandro De Zanet, Jose Juan Escobar-Barranco, Carlos Ciller, Stefanos Apostolopoulos, Gabriela Susanna-González, Joseph P M Blair, Romina M Lasagni Vitar, José Natán Rodríguez Martín, Carlos Bermúdez, Alfonso Luis Calle Pascual, Elena Rigo, Enrique Cervera Taulet, Rosario Cobo-Soriano

“…Objective This study validated the artificial intelligence (AI)-based algorithm LuxIA for screening more-than-mild diabetic retinopathy (mtmDR) from a single 45° colour fundus image of patients with diabetes mellitus (DM, type 1 or type 2) in Spain. …”
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COMPUTER- AIDED MODELING AND IMPROVING OF RISOGRAPH PRINTING by P. E. Sulim, V. S. Yudenkov

“…The considered improvement of qualit y of the risofraph print based on a mathematical model in the environment Matlab by using the specialized algorithms and digital filter of the Image Processing Toolbox. …”
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Treatment decision algorithms for tuberculosis screening and diagnosis in children below 5 years hospitalised with severe acute malnutrition: a cost-effectiveness analysisResearch... by Marc d’Elbée, Nyashadzaishe Mafirakureva, Chishala Chabala, Minh Huyen Ton Nu Nguyet, Martin Harker, Clémentine Roucher, Gerald Businge, Perfect Shankalala, Bwendo Nduna, Veronica Mulenga, Maryline Bonnet, Eric Wobudeya, Olivier Marcy, Peter J. Dodd

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Reflective Distributed Denial of Service Detection: A Novel Model Utilizing Binary Particle Swarm Optimization—Simulated Annealing for Feature Selection and Gray Wolf Optimization-... by Daoqi Han, Honghui Li, Xueliang Fu

“…The BPSO-SA algorithm enhances the global search capability of Particle Swarm Optimization (PSO) using the SA mechanism and effectively screens out the optimal feature subset; the GWO algorithm optimizes the hyperparameters of LightGBM by simulating the group hunting behavior of gray wolves to enhance the detection performance of the model. …”
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Screening for endometriosis: A scoping review of screening measures that could support early diagnosis by Brittany N. Rosenbloom, Tania Di Renna, Adriano Nella, Mathew Leonardi, Maggie Tiong, Seungmin Lee, Rachael Bosma

“…Despite reporting symptoms, women wait around 11 years before receiving a diagnosis, further interfering with their mental and physical health. Patient reported screening measures can promote faster diagnosis, however their measurement quality remains unknown. …”
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Efficient Design Optimization Assisted by Sequential Surrogate Models by Emiliano Iuliano

“…The paper proposes a global optimization algorithm employing surrogate modeling and adaptive infill criteria. …”
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QSAR Models for Predicting the Antioxidant Potential of Chemical Substances by Sofia Ghironi, Edoardo Luca Viganò, Gianluca Selvestrel, Emilio Benfenati

“…Different machine learning algorithms were applied to build regression models, and the goodness-of-fit of each model was assessed using the statistical parameters of R squared (R²), the Root-Mean-Squared Error, and the Mean Absolute Error. …”
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The Bridge between Screening and Assessment: Establishment and Application of Online Screening Platform for Food Risk Substances by Kang Hu, Shaoming Jin, Hong Ding, Jin Cao

“…The screening comparison algorithm, the core of the screening model, is obtained through the improvement of the existing spectral library search algorithm. …”
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Algorithm for alerting the unmanned aerial vehicle operator based on the image potential obstacle borders detection on the flight trajectory using the OPEN CV library by V. Yu. Stepanov, E. A. Hvitko

“…Then the conclusion is made about necessity of development of algorithm and software, which can help the operator of the UAV in deciding on necessary trajectory changes of UAV, since, for example, guided solely by the method image of the terrain or another similar method in the planning of the UAV trajectory as preliminary preparation for the flight, however, such methods are fairly static and are not suitable in such situations as, for example, detection of unexpected obstacles. …”
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A Seasonal Fresh Tea Yield Estimation Method with Machine Learning Algorithms at Field Scale Integrating UAV RGB and Sentinel-2 Imagery by Huimei Liu, Yun Liu, Weiheng Xu, Mei Wu, Leiguang Wang, Ning Lu, Guanglong Ou

“…Subsequently, these 26 features were screened using the random forest algorithm and Pearson correlation analysis. …”
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Medical laboratory data-based models: opportunities, obstacles, and solutions by Jiaojiao Meng, Moxin Wu, Fangmin Shi, Ying Xie, Hui Wang, You Guo

“…Abstract Medical Laboratory Data (MLD) models, which combine artificial intelligence with big medical data, have great potential in disease screening, diagnosis, personalized medicine, and health management. …”
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