Data-driven insights into pre-slaughter mortality: Machine learning for predicting high dead on arrival in meat-type ducks by Chalita Jainonthee, Phutsadee Sanwisate, Panneepa Sivapirunthep, Chanporn Chaosap, Raktham Mektrirat, Sudarat Chadsuthi, Veerasak Punyapornwithaya

“…This classification was performed using machine learning (ML) algorithms such as Least Absolute Shrinkage and Selection Operator (LASSO), Support Vector Machine (SVM), Decision Tree (DT), Random Forests (RF), and Extreme Gradient Boosting (XGBoost). …”
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Identification of standing dead trees in Robinia pseudoacacia plantations across China’s Loess Plateau using multiple deep learning models by Li Zhang, Xiaodong Gao, Shuyi Zhou, Zhibo Zhang, Tianjie Zhao, Yaohui Cai, Xining Zhao

“…These images were then integrated with a comprehensive evaluation of multiple detection algorithms, including Faster R-CNN, EfficientDet, YOLOv4, YOLOv5, YOLOv8, YOLOv9, and a novel model, YOLOv9-ECA. …”
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Unified Mobile App for Streamlining Verbal Autopsy and Cause of Death Assignment in India: Design and Development Study by Harleen Kaur, Stuti Tripathi, Manjeet Singh Chalga, Sudhir K Benara, Amit Dhiman, Shefali Gupta, Saritha Nair, Geetha Menon, B K Gulati, Sandeep Sharma, Saurabh Sharma

“…Although computer-coded algorithms have advanced the COD assignment process, data collection in densely populated countries like India remains a logistical challenge. …”
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AI-Based Advanced Approaches and Dry Eye Disease Detection Based on Multi-Source Evidence: Cases, Applications, Issues, and Future Directions by Mini Han Wang, Lumin Xing, Yi Pan, Feng Gu, Junbin Fang, Xiangrong Yu, Chi Pui Pang, Kelvin Kam-Lung Chong, Carol Yim-Lui Cheung, Xulin Liao, Xiaoxiao Fang, Jie Yang, Ruoyu Zhou, Xiaoshu Zhou, Fengling Wang, Wenjian Liu

“…The research conducts a comprehensive review of datasets, diagnostic evidence, and standards, as well as advanced algorithms in AI-based DED detection over the past five years. …”
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Development of machine learning models for predicting non-remission in early RA highlights the robust predictive importance of the RAID score-evidence from the ARCTIC study by Gaoyang Li, Shrikant S. Kolan, Franco Grimolizzi, Joseph Sexton, Giulia Malachin, Guro Goll, Tore K. Kvien, Tore K. Kvien, Nina Paulshus Sundlisæter, Manuela Zucknick, Siri Lillegraven, Espen A. Haavardsholm, Espen A. Haavardsholm, Bjørn Steen Skålhegg

“…The model employed a super learner algorithm that combine three base algorithms of elastic net, random forest and support vector machine. …”
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Multi-task aquatic toxicity prediction model based on multi-level features fusion by Xin Yang, Jianqiang Sun, Bingyu Jin, Yuer Lu, Jinyan Cheng, Jiaju Jiang, Qi Zhao, Jianwei Shuai

“…Furthermore, in comparison with previous algorithms, ATFPGT-multi outperforms comparative methods, emphasizing that our approach exhibits higher accuracy and reliability in predicting aquatic toxicity. …”
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Optimasi Proses Klasterisasi di MySQL DBMS dengan Mengintegrasikan Algoritme MIC-Kmeans Menggunakan Bahasa SQL dalam Stored Procedure by Issa Arwani

“…With the advantages of the MIC-Kmeans algorithm, the method was chosen as an alternative algorithm to be integrated in the DBMS using SQL  for a clustering. …”
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Comparison of self-collected and healthcare worker-collected rectovaginal swabs for group B streptococcus detection in pregnancy using PCR with a commercial collection-enrichment d... by Iva Kukovica, Neža Omahen, Nika Klobučar, Martina Bučar, Anita Franko Rutar, Tina Perme, Tina Perme, Miha Lučovnik, Miha Lučovnik, Samo Jeverica, Samo Jeverica

“…Performance characteristics were calculated and compared between different diagnostics test algorithms using McNemar’s test for paired samples.ResultsOverall, GBS was detected in 18% (95% CI 13–23%; n = 40) of swabs A and 19% (95% CI 14–25%; n = 43) of swabs B. …”
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A novel gene signature for predicting outcome in colorectal cancer patients based on tumor cell-endothelial cell interaction via single-cell sequencing and machine learning by Lina Pang, Qingxia Sun, Wenyue Wang, Mingjie Song, Ying Wu, Xin Shi, Xiaonan Shi

“…Prognostic signatures were developed using various machine learning algorithms based on marker genes linked to the identified cell subpopulations. …”
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Synthesizing Local Capacities, Multi-Source Remote Sensing and Meta-Learning to Optimize Forest Carbon Assessment in Data-Poor Regions by Kamaldeen Mohammed, Daniel Kpienbaareh, Jinfei Wang, David Goldblum, Isaac Luginaah, Esther Lupafya, Laifolo Dakishoni

“…To improve forest carbon assessment, we employed stacked generalization, combining multiple machine learning algorithms to leverage their complementary strengths and address individual limitations. …”
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Pengukuran Performa Apache Spark dengan Library H2O Menggunakan Benchmark Hibench Berbasis Cloud Computing by Aminudin Aminudin, Eko Budi Cahyono

“…In order for Apache Spark to be able to do machine learning processes, in this paper an experiment will be conducted that integrates Apache Spark which acts as a large data processing environment and the concept of parallel computing will be combined with H2O libraries specifically for handling data processing using machine learning algorithms . Based on the results of testing Apache Spark in a cloud computing environment, Apache Spark is able to process weather data obtained from the largest weather data archive, namely NCDC data with data sizes up to 6GB. …”
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Evaluating the level of digitalization of the innovation process with artificial intelligence approach in the digital transformation of knowledge-based companies by ali Bagheri, reza radfar, sepehr ghazinoory

“…The scientific study of algorithms and statistical models are used by computer systems that use patterns and inference to perform tasks rather than using clear instructions. …”
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Machine-learning versus traditional methods for prediction of all-cause mortality after transcatheter aortic valve implantation: a systematic review and meta-analysis by Clara K Chow, Aravinda Thiagalingam, Rohan Jayasinghe, Sarah Zaman, Stephen Bacchi, Justin Chan, Aashray Gupta, Shaun Evans, Pramesh Kovoor, Brandon Stretton, Jayme Bennetts, Ammar Zaka, Naim Mridha, Joshua Kovoor, Gopal Sivagangabalan, Cecil Mustafiz, Daud Mutahar, Shreyans Sinhal, James Gorcilov, Benjamin Muston, Fabio Ramponi, Dale J Murdoch

“…While integration of ML algorithms into electronic healthcare systems may improve periprocedural risk stratification, immediate implementation in the clinical setting remains uncertain. …”
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ER-GMMD: Cross-Scene Remote Sensing Classification Method of <italic>Tamarix chinensis</italic> in the Yellow River Estuary by Liying Zhu, Yabin Hu, Guangbo Ren, Na Qiao, Ziyue Meng, Jianbu Wang, Yajie Zhao, Shibao Li, Yi Ma

“…Key results include: 1) The proposed model, trained with only 5&#x0025; of the source domain samples, achieves an overall classification accuracy of 96.52&#x0025; on the target domain samples, which is a 17.61&#x0025; improvement compared with the traditional network U-Net without domain adaptation. 2) Compared with domain adaptation algorithms DAN and S-DMM, the proposed ER-GMMD model demonstrates higher accuracy on the constructed dataset, indicating its potential for high-precision classification of mixed vegetation in coastal wetlands.…”
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Validation Indicator Identification and Customer Ranking in Microloans: A Study at Middle East Bank in Iran by Azadeh Ahmadi Kousha, Faegh Ahmadi, Mohammad Hossein Ranjbar, Hamidreza Kordlouie

“…Naive Bayes, Meta, Attribute Selected Classifier, and j48 algorithms were implemented and WEKA software was used to classify criteria and create patterns. …”
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Beyond identification of familial hypercholesterolemia: Improving downstream visits and treatments in a large health care system by Harin Lee, Tarun Kadaru, Ruth Schneider, Taylor Triana, Carol Tujardon, Colby Ayers, Mujeeb Basit, Zahid Ahmad, Amit Khera

“…Several electronic health record (EHR) algorithms have been developed to improve identification of patients with FH. …”
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Mitochondrial dysfunction-driven AMPK-p53 axis activation underpins the anti-hepatocellular carcinoma effects of sulfane sulfur by Xue Zheng, Yuhua Luo, Rui Huo, Yiwen Wang, Youbang Chen, Mianrong Chen, Qi Zhao, Kexin Li, Hanyi Zhang, Xiaotong Li, Xiang Li, Hui Zhang, Zaopeng He, Li Huang, Chun-tao Yang

“…We utilized bioinformatics algorithms for clustering, function enrichment, feature screening and survival analysis on proteomic data from the Cancer Proteome Atlas (CPTAC) and transcriptomic data from the Cancer Genome Atlas (TCGA). …”
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An optimized approach for predicting water quality features and a performance evaluation for mapping surface water potential zones based on Discriminant Analysis (DA), Geographical... by Abhijeet Das

“…Again, this research used a strong methodology by incorporating Machine learning (ML) algorithms, such as: Artificial Neural Network (ANN), Gaussian Process Regression (GPR), Support Vector Machine (SVM), and Linear Regression Model (LRM), were applied to forecast and confirm the quality of the water. …”
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Comprehensive Analysis of Programmed Cell Death-Related Genes in Diagnosis and Synovitis During Osteoarthritis Development: Based on Bulk and Single-Cell RNA Sequencing Data by Zhou J, Jiao S, Huang J, Dai T, Xu Y, Xia D, Feng Z, Chen J, Li Z, Hu L, Meng Q

“…Using machine learning algorithms, Hub PCD-related differentially expressed genes (Hub PCD-DEGs) were identified. …”
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Informatization of the processes of administration of the quality of medical services in surgical hospitals by Ya.S. Bereznytskyi, V.Ya. Bereznytskyi, O.V. Hudoshyna, N.D. Chuhrienko, G.V. Bereznytska, Ye.V. Zalyhina, Yu.B. Dianova, E.A. Rynska, L.N. Ksykevich

“…Currently, there is no comprehensive information technology and algorithm for recording data on the provision of medical services and determining their quality. …”
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