MFPSP: Identification of fungal species-specific phosphorylation site using offspring competition-based genetic algorithm. by Chao Wang, Quan Zou

“…The comparison results shown that MFPSP achieves a more advanced and balanced performance to several state-of-the-art available toolkits. …”
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Precision Measurement and Feature Selection in Medical Diagnostics using Hybrid Genetic Algorithm and Support Vector Machine by Gowri Subadra K, Sathish Babu P

“…This study contributes to the development of more accurate and efficient breast cancer screening tools to help healthcare providers make informed diagnostic decisions.…”
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Deep Learning Algorithm for Keratoconus Detection from Tomographic Maps and Corneal Biomechanics: A Diagnostic Study by Wiyada Quanchareonsap, Ngamjit Kasetsuwan, Usanee Reinprayoon, Yonrawee Piyacomn, Thitima Wungcharoen, Monthira Jermjutitham

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A recurrent neural network and parallel hidden Markov model algorithm to segment and detect heart murmurs in phonocardiograms. by Andrew McDonald, Mark J F Gales, Anurag Agarwal

“…These properties make the algorithm a promising tool for screening of abnormal heart murmurs.…”
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Predicting Early-Onset Colorectal Cancer in Individuals Below Screening Age Using Machine Learning and Real-World Data: Case Control Study by Chengkun Sun, Erin Mobley, Michael Quillen, Max Parker, Meghan Daly, Rui Wang, Isabela Visintin, Ziad Awad, Jennifer Fishe, Alexander Parker, Thomas George, Jiang Bian, Jie Xu

“…Accurate early prediction and a thorough understanding of the risk factors for early-onset colorectal cancer (EOCRC) are vital for effective prevention and treatment, particularly for patients below the recommended screening age. ObjectiveOur study aims to predict EOCRC using machine learning (ML) and structured electronic health record data for individuals under the screening age of 45 years, with the aim of exploring potential risk and protective factors that could support early diagnosis. …”
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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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Development and Internal Validation of a Machine Learning-Based Colorectal Cancer Risk Prediction Model by Deborah Jael Herrera, Daiane Maria Seibert, Karen Feyen, Marlon van Loo, Guido Van Hal, Wessel van de Veerdonk

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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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Prediction of Coiled Tubing Erosion Rate Based on Sparrow Search Algorithm Back-Propagation Neural Network Model by Yinping Cao, Fengying Fang, Guowei Wang, Wenyu Zhu, Yijie Hu

“…However, with the increase in fracturing, drilling, and sand-washing operations, the erosion of coiled tubing walls caused by solid particles has become one of the main failure modes. To accurately predict the erosion rate of coiled tubing, this study studied the influence law of erosion rate through experiments, screened the main influencing factors of erosion rate by grey relational analysis (GRA), and established a back-propagation neural network (BPNN) model optimized by the sparrow search algorithm (SSA) to predict the erosion rate. …”
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Software with artificial intelligence-derived algorithms for detecting and analysing lung nodules in CT scans: systematic review and economic evaluation by Julia Geppert, Peter Auguste, Asra Asgharzadeh, Hesam Ghiasvand, Mubarak Patel, Anna Brown, Surangi Jayakody, Emma Helm, Dan Todkill, Jason Madan, Chris Stinton, Daniel Gallacher, Sian Taylor-Phillips, Yen-Fu Chen

“…Although more data were available to populate the screening population model, there was substantial uncertainty across all models. …”
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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

“…These findings open new possibilities for accurate prediction of NIHL based on SNP locus screening in the future, and provide a more scientific basis for decision-making in occupational health management.…”
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Construction of risk prediction model of sentinel lymph node metastasis in breast cancer patients based on machine learning algorithm by Qianmei Yang, Cuifang Liu, Yongyue Wang, Guifang Dong, Jinghuan Sun

“…Subsequently, five ML algorithms, namely LOGIT, LASSO, XGBOOST, RANDOM FOREST model and GBM model were employed to train and develop an ML model. …”
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Design of low-carbon planning model for vehicle path based on adaptive multi-strategy ant colony optimization algorithm by Qi Guo, Rui Li, Changjiang Zheng, Gwanggil Jeon

“…Moreover, comparative analyses of various optimization methods on the custom-built dataset reveal that the ant colony optimization algorithm markedly outperforms the simulated annealing algorithm (SA) and particle swarm optimization algorithm (PSO). …”
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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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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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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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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

“…It is urgent to develop a safer and more efficient therapeutic alternative. Herein, utilizing the methodologies of Deep Learning (DL) and Natural Language Processing (NLP), we proposed a paradigm algorithm that amalgamates Word2vec with a TF-IDF variant, TF-IIDF, to deftly discern potential pro-angiogenic peptides from intrinsically disordered regions (IDRs) of 262 related proteins, where are fertile grounds for developing safer and highly promising bioactive peptides. …”
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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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Diagnostic accuracy of artificial intelligence models in detecting congenital heart disease in the second-trimester fetus through prenatal cardiac screening: a systematic review an... by Lies Dina Liastuti, Lies Dina Liastuti, Yosilia Nursakina, Yosilia Nursakina

“…Nevertheless, prospective studies with bigger datasets and more inclusive populations are needed to compare AI algorithms to conventional methods.Systematic Review Registrationhttps://www.crd.york.ac.uk/prospero/display_record.php?…”
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Using data science to diagnose and characterize heterogeneity of Alzheimer's disease by Ting F.A. Ang, Ning An, Huitong Ding, Sherral Devine, Sanford H. Auerbach, Joseph Massaro, Prajakta Joshi, Xue Liu, Yulin Liu, Elizabeth Mahon, Rhoda Au, Honghuang Lin

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