SARS-CoV-2 Prediction Strategy Based on Classification Algorithms from a Full Blood Examination by C. F. Choukhan, I. Lasri, R. El Hatimi, M. R. Lemnaouar, M. Esghir

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Comparison between logistic regression and machine learning algorithms on prediction of noise-induced hearing loss and investigation of SNP loci by Jie Lu, Xinhao Lu, Yixiao Wang, Hengdong Zhang, Lei Han, Baoli Zhu, Boshen Wang

“…The SNP loci screened by these models are pivotal in the process of NIHL prediction, which further improves the prediction accuracy of the model. …”
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Non-Destructive Detection of Silage pH Based on Colorimetric Sensor Array Using Extended Color Components and Novel Sensitive Dye Screening Method by Kai Zhao, Haiqing Tian, Jue Zhang, Yang Yu, Lina Guo, Jianying Sun, Haijun Li

“…Extended color components, a novel sensitive dye screening method, and a feature screening method were integrated and applied to enhance pH detection. …”
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Analytical screening of polymorphic variants of 20S proteasome genes when planning a study of pathogenetic effects of modification of NFKB1 post-translational processing by A. V. Meyer, M. V. Ulyanova, D. O. Imekina, A. D. Padyukova, T. A. Tolochko, E. A. Astafieva, M. B. Lavryashina

“…To calculate the genetic distances between populations, we used the methord of comparing the populations by frequencies of polymorphic marker alleles proposed by Ney, the obtained matrices are illustrated by the method of multidimensional scaling in space using Statistica v.8.0.Results. Discussion of the algorithm and results of analytical screening of polymorphic variants of 14 genes (PSMA1-PSMA7, PSMB1–PSMB7) encoding proteasome subunits 20S. …”
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Personalised Prostate Cancer Diagnosis: Evaluating Biomarker-based Approaches to Reduce Unnecessary Magnetic Resonance Imaging and Biopsy Procedures by Timo F.W. Soeterik, Xiaobo Wu, Roderick C.N. Van den Bergh, Claudia Kesch, Fabio Zattoni, Ugo Falagario, Alberto Martini, Marcin Miszczyk, Vittorio Fasulo, Martina Maggi, Veeru Kasivisvanathan, Pawel Rajwa, Giancarlo Marra, Giorgio Gandaglia, Peter K.F. Chiu

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Machine Learning-Based Prediction of First Trimester Down Syndrome Risk in East Asian Populations by Chen YT, Chen GJ, Lin YS

“…Fourteen features (including maternal age, nuchal translucency thickness, serum markers, etc.) were input into the twelve machine learning models, along with seven data-balancing algorithms, to explore the risk prediction outcomes. …”
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Estimation of Daylily Leaf Area Index by Synergy Multispectral and Radar Remote-Sensing Data Based on Machine-Learning Algorithm by Minhuan Hu, Jingshu Wang, Peng Yang, Ping Li, Peng He, Rutian Bi

“…Because of low estimation accuracy of empirical models based on single-source data, we proposed a machine-learning algorithm combining optical and microwave remote-sensing data as well as the random forest regression (RFR) importance score to select features. …”
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Rapid diagnosis of latent and active pulmonary tuberculosis by autofluorescence spectroscopy of blood plasma combined with artificial neural network algorithm by Fengjiao Yue, Si Li, Lijuan Wu, Xuerong Chen, Jianhua Zhu

“…This study demonstrates the possibility of using blood plasma autofluorescence spectroscopy and Artificial Neural Network (ANN) algorithm for the rapid and accurate diagnosis of latent and active pulmonary TB from healthy subjects. …”
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Recent advances in AI-based toxicity prediction for drug discovery by Hyundo Lee, Jisan Kim, Ji-Woon Kim, Yoonji Lee, Yoonji Lee

“…The advent of computational approaches has accelerated a shift toward in silico modeling, virtual screening, and, notably, artificial intelligence (AI) to identify potential toxicities earlier in the pipeline. …”
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Throw out an oligopeptide to catch a protein: Deep learning and natural language processing-screened tripeptide PSP promotes Osteolectin-mediated vascularized bone regeneration by Yu Chen, Long Chen, Jinyang Wu, Xiaofeng Xu, Chengshuai Yang, Yong Zhang, Xinrong Chen, Kaili Lin, Shilei Zhang

“…In summary, our study established a precise and efficient composite model of DL and NLP to screen bioactive peptides, opening an avenue for the development of various peptide-based therapeutic strategies applicable to a broader range of diseases.…”
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Data stewardship and curation practices in AI-based genomics and automated microscopy image analysis for high-throughput screening studies: promoting robust and ethical AI applicat... by Asefa Adimasu Taddese, Assefa Chekole Addis, Bjorn T. Tam

“…The study also examined specific AI considerations, such as algorithmic bias, model explainability, and the application of advanced cryptographic techniques. …”
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Characterization and feature selection of volatile metabolites in Yangxian pigmented rice varieties through GC-MS and machine learning algorithms by Kaiqi Cheng, Ruonan Dong, Fei Pan, Wen Su, Lingjie Xi, Meng Zhang, Jingzhang Geng, Ruichang Gao, Ruichang Gao, Wengang Jin, A. M. Abd El-Aty, A. M. Abd El-Aty

“…Four machine learning models were further used for the classification of various colored rice varieties, and random forest model was the optimum for predicting classification, with an accuracy of 0.97. …”
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Preliminary study on objective evaluation algorithm of human infrared thermogram seriality and its clinical application in population with metabolic syndrome by Yu Chen, Jia-Yang Guo, Yan-Hong An, Xian-Hui Zhang, Jia-Min Niu, Xiao-Ran Li, Hui-Zhong Xue, Yi-Meng Yang, Lu-Qi Cai, Yu-Chen Xia, Quan-Yi Chen, Bing-Yang Cai, Wen-Zheng Zhang, Yong-Hua Xiao

“…By focusing on temperature sequences rather than absolute temperature values, the algorithm is expected to facilitate a more quantitative evaluation of thermogram features. …”
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A New Computer-Aided Diagnosis System for Breast Cancer Detection from Thermograms Using Metaheuristic Algorithms and Explainable AI by Hanane Dihmani, Abdelmajid Bousselham, Omar Bouattane

“…To achieve these goals, we proposed a new multi-objective optimization approach named the Hybrid Particle Swarm Optimization algorithm (HPSO) and Hybrid Spider Monkey Optimization algorithm (HSMO). …”
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Supervised machine learning algorithms for the classification of obesity levels using anthropometric indices derived from bioelectrical impedance analysis by Rodrigo Yáñez-Sepúlveda, Aldo Vásquez-Bonilla, Rodrigo Olivares, Pablo Olivares, Juan Pablo Zavala-Crichton, Claudio Hinojosa-Torres, Catalina Muñoz-Strale, Frano Giakoni-Ramírez, Josivaldo de Souza-Lima, Jacqueline Páez-Herrera, Jorge Olivares-Arancibia, Tomás Reyes-Amigo, Guillermo Cortés-Roco, Juan Hurtado-Almonacid, Eduardo Guzmán-Muñoz, Nicole Aguilera-Martínez, José Francisco López-Gil, Boryi A. Becerra-Patiño, Juan David Paucar-Uribe, Exal Garcia-Carrillo, Vicente Javier Clemente-Suárez

“…These models can enhance the effectiveness of obesity screening in clinical and community settings.…”
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Combined Prediction of Dust Concentration in Opencast Mine Based on RF-GA-LSSVM by Shuangshuang Xiao, Jin Liu, Yajie Ma, Yonggui Zhang

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Influencing factors and prediction algorithms to estimate public preference for painless medical procedures in China: a national cross-sectional study by Xiangyang Guo, Xiaoxiao Wang, Yanan Song, Chen Luo, Zhengqian Li, Wei You, Sichen Liu, Kaixi Liu

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Swedish regional population-based organised prostate cancer testing: why, what and how? by Ola Bratt, Salma Tunå Butt, Charlotte Carlsson, Lisa Jelf-Eneqvist, Olof Gunnarsson, Alma Ihre, Thomas Jiborn, Anna Lantz, Heide Larsson, Helena Strömqvist, Johan Styrke, Nils-Erik Svedberg, Rebecka Arnsrud Godtman

“…A general experience is that communication and organisational matters have been more challenging than medical decisions. Conclusions: The Swedish population-based OPT programmes provide organisational experiences, diagnostic outcomes, and research results of value for future national prostate cancer screening programmes. …”
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Fault Classification in Power Transformers via Dissolved Gas Analysis and Machine Learning Algorithms: A Systematic Literature Review by Vuyani M. N. Dladla, Bonginkosi A. Thango

“…In this paper, a systematic literature review (SLR) is conducted using the Preferred Reporting Items for Systematic Reviews (PRISMA) framework to record and screen current research work pertaining to the application of machine learning algorithms for DGA-based transformer fault classification. …”
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Prevalence of advanced liver fibrosis in the general population of the Paris region according to FIB-4 score and liver risk score by Henri Tran, Stefano Caruso, Anne-Laure Mazialivoua, Cecile Fargeat, Odile Rousselet, Adrien Ko, Vincent Leroy, Patrick Ingiliz

“…An adapted new pragmatic screening algorithm using LRS should be considered.…”
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