Using XBGoost, an interpretable machine learning model, for diagnosing prostate cancer in patients with PSA < 20 ng/ml based on the PSAMR indicator by Dengke Li, Baoyuan Chang, Qunlian Huang

Subjects: “…XGBoost machine learning model…”
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A novel aggregated coefficient ranking based feature selection strategy for enhancing the diagnosis of breast cancer classification using machine learning by E. Sreehari, L. D. Dhinesh Babu

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Prediction of Multiple Organ Failure Complicated by Moderately Severe or Severe Acute Pancreatitis Based on Machine Learning: A Multicenter Cohort Study by Fumin Xu, Xiao Chen, Chenwenya Li, Jing Liu, Qiu Qiu, Mi He, Jingjing Xiao, Zhihui Liu, Bingjun Ji, Dongfeng Chen, Kaijun Liu

“…This study is aimed to use machine learning to predict the risk of MOF in the course of disease. …”
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Developing a semi-automated technique of surface water quality analysis using GEE and machine learning: A case study for Sundarbans by Sheikh Fahim Faysal Sowrav, Sujit Kumar Debsarma, Mohan Kumar Das, Khan Mohammad Ibtehal, Mahfujur Rahman, Noshin Tabassum Hridita, Atika Afia Broty, Muhammad Sajid Anam Hoque

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Major Adverse Kidney Events in Hospitalized Older Patients With Acute Kidney Injury: Machine Learning–Based Model Development and Validation Study by Xiao-Qin Luo, Ning-Ya Zhang, Ying-Hao Deng, Hong-Shen Wang, Yi-Xin Kang, Shao-Bin Duan

“…ObjectiveThis study aimed to develop and validate a machine learning–based model to predict MAKE30 in hospitalized older patients with AKI. …”
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Identification of the Hub Genes Involved in Stem Cell Treatment for Intervertebral Disc Degeneration: A Conjoint Analysis of Single-Cell and Machine Learning by Jianfeng Chen, Fuwei Qi, Guanshen Li, Qiaosong Deng, Chenlin Zhang, Xiaojun Li, Yafeng Zhang

“…In this first-of-a-kind study combining machine learning, stem cell treatment samples and single-cell sequencing data were collected. …”
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Machine learning based compact MIMO antenna array for 38 GHz millimeter wave application with robust isolation and high efficiency performance by Md. Ashraful Haque, Md. Sharif Ahammed, Soeung Socheatra, Redwan A. Ananta, Md. Jamal Hossain Nirob, Narinderjit Singh Sawaran Singh, Noorlindawaty Md. Jizat, Saeed Alsowail, Samir Salem Al-Bawri

“…The performance of wireless 5 G communication networks can be enhanced by combining multiple-input multiple-output (MIMO) antennas with machine learning (ML). The suggested antenna, which is constructed on a Rogers 5880 substrate, is well-suited for usage in the high bands of 5 G applications due to its 27 dB isolation and bandwidth of 35.181–39.689 (4.508) GHz within a -10 dB range. …”
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A Novel Approach for Detection of Pavement Crack and Sealed Crack Using Image Processing and Salp Swarm Algorithm Optimized Machine Learning by Nhat-Duc Hoang, Thanh-Canh Huynh, Xuan-Linh Tran, Van-Duc Tran

“…This method is an integration of feature extraction based on image processing and metaheuristic optimized machine learning. Image processing is used to compute features that characterize visual appearance and texture of the pavement image. …”
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First-principles based data-driven strain engineering for ferroelectrics via active machine learning: A nonlinear piezoelectric constitutive equation by Susumu MINAMI, Yasuaki MARUYAMA, Yoshimasa ABE, Tomohiro NAKAYAMA, Takahiro SHIMADA

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Unraveling pathogenesis and potential biomarkers for autism spectrum disorder associated with HIF1A pathway based on machine learning and experiment validation by Jinru Cui, Heli Li, Cong Hu, Feiyan Zhang, Yunjie Li, Ying Weng, Liping Yang, Yingying Li, Minglan Yao, Hao Li, Xiaoping Luo, Yan Hao

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ACD-ML: Advanced CKD detection using machine learning: A tri-phase ensemble and multi-layered stacking and blending approach by Mir Faiyaz Hossain, Shajreen Tabassum Diya, Riasat Khan

“…This study aims to leverage machine learning algorithms and ensemble models for early detection of CKD using the “Chronic Kidney Disease (CKD15)” and “Risk Factor Prediction of Chronic Kidney Disease (CKD21)” datasets from the UCI Machine Learning Repository. …”
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Evaluation of Prediction Models for the Capping and Breaking Force of Tablets Using Machine Learning Tools in Wet Granulation Commercial-Scale Pharmaceutical Manufacturing by Sun Ho Kim, Su Hyeon Han, Dong-Wan Seo, Myung Joo Kang

Subjects: “…machine learning…”
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Bioinformatics combining machine learning and single-cell sequencing analysis to identify common mechanisms and biomarkers of rheumatoid arthritis and ischemic heart failure by Ziyi Sun, Jianguo Lin, Xiaoning Sun, Zhangjun Yun, Xiaoxiao Zhang, Siyu Xu, Jinlong Duan, Kuiwu Yao

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Coronary health index based on immunoglobulin light chains to assess coronary heart disease risk with machine learning: a diagnostic trial by Wenbo Ren, Zichen Zhang, Yifei Wang, Jiangyuan Wang, Li Li, Lin Shi, Taiyu Zhai, Jing Huang

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Supervised machine learning statistical models for visual outcome prediction in macular hole surgery: a single-surgeon, standardized surgery study by Kanika Godani, Vishma Prabhu, Priyanka Gandhi, Ayushi Choudhary, Shubham Darade, Rupal Kathare, Prathiba Hande, Ramesh Venkatesh

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I caratteri paesaggistici nei giardini all’italiana: Machine Learning e Computer Vision per la ricerca delle simmetrie by Amedeo Ganciu

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AICpred: Machine Learning-Based Prediction of Potential Anti-Inflammatory Compounds Targeting TLR4-MyD88 Binding Mechanism by Lucindah N. Fry-Nartey, Cyril Akafia, Ursula S. Nkonu, Spencer B. Baiden, Ignatus Nunana Dorvi, Kwasi Agyenkwa-Mawuli, Odame Agyapong, Claude Fiifi Hayford, Michael D. Wilson, Whelton A. Miller, Samuel K. Kwofie

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Characterization and Machine Learning-Driven Property Prediction of a Novel Hybrid Hydrogel Bioink Considering Extrusion-Based 3D Bioprinting by Rokeya Sarah, Kory Schimmelpfennig, Riley Rohauer, Christopher L. Lewis, Shah M. Limon, Ahasan Habib

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An ensemble machine learning-based performance evaluation identifies top In-Silico pathogenicity prediction methods that best classify driver mutations in cancer by Subrata Das, Vatsal Patel, Shouvik Chakravarty, Arnab Ghosh, Anirban Mukhopadhyay, Nidhan K. Biswas

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A machine learning-based radiomics approach for differentiating patellofemoral osteoarthritis from non-patellofemoral osteoarthritis using Q-Dixon MRI by Liangjing Lyu, Jing Ren, Wenjie Lu, Jingyu Zhong, Yang Song, Yongliang Li, Weiwu Yao

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