Protocol to generate dual-target compounds using a transformer chemical language model by Sanjana Srinivasan, Jürgen Bajorath

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Klasifikasi Aktivitas Manusia Menggunakan Metode Long Short-Term Memory by Latansa Nurry Izza Afida, Fitra Abdurrachman Bachtiar, Imam Cholissodin

“…Selain tingginya dimensi, pada penelitian sebelumnya, banyaknya jumlah label dengan menerapkan machine learning tradisional tidak mampu melebihi akurasi 88%. …”
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Flight Delay Classification Prediction Based on Stacking Algorithm by Jia Yi, Honghai Zhang, Hao Liu, Gang Zhong, Guiyi Li

“…There are five supervised machine learning algorithms in the first-level learner of Stacking including KNN, Random Forest, Logistic Regression, Decision Tree, and Gaussian Naive Bayes. …”
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A CNN-Based Microwave Imaging System for Detecting Watermelon Ripeness by Zachary M. Choffin, Lingyan Kong, Yu Gan, Nathan Jeong

“…The integration of a non-invasive microwave imaging system with a machine learning algorithm could improve food quality and food safety. …”
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Software Defect Prediction For Quality Evaluation Using Learning Techniques Ensemble Stacking by Muhammad Romadhona Kusuma, Windu Gata, Sigit Kurniawan, Dedi Dwi Saputra, Supriadi Panggabean

“…We performed hyperparameter tuning with grid search CV on Machine Learning algorithms such as Ada Boost and Gradient Boosting. …”
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The Construction of Corporate Financial Management Risk Model Based on XGBoost Algorithm by Rongyuan Qin

“…With the continuous development of intelligent algorithms and machine learning algorithms, new ideas have been brought to enterprise financial risk assessment. …”
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A spatial interpolation method based on 3D-CNN for soil petroleum hydrocarbon pollution. by Sheng Miao, Guoqing Ni, Guangze Kong, Xiuhe Yuan, Chao Liu, Xiang Shen, Weijun Gao

“…The results indicate that compared with traditional Kriging3D methods (R2 = 0.318) and other machine learning methods such as support vector regression (R2 = 0.582), the proposed 3DCNN based method can achieve better accuracy (R2 = 0.954). …”
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Automated and Reproducible Detection of Vascular Endothelial Growth Factor (VEGF) in Renal Tissue Sections by Nayana Damiani Macedo, Aline Rodrigues Buzin, Isabela Bastos de Araujo, Breno Valentim Nogueira, Tadeu Uggere Andrade, Denise Coutinho Endringer, Dominik Lenz

“…Light microscopy images of renal tissue sections stained for VEGF were analyzed. Subsequently, machine learning classified the cells as VEGF+ and VEGF- cells. …”
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Application of an improved LightGBM hybrid integration model combining gradient harmonization and Jacobian regularization for breast cancer diagnosis by Xiaoyan Sun

“…In recent years, intelligent medical assistants supported by data mining and machine learning algorithms have provided necessary support for doctors’ diagnosis. …”
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Application of Internet of Things Based on Big Data Ecosystem in Factory Energy Consumption Analysis Model by Ang Li, Chen Zhang, Lei Li

“…In 2019, the average ratio of decision tree algorithm, machine learning algorithm, and machine learning algorithm was 36.8%, 37.4%, and 43.5%, respectively. …”
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Unleashing the Power of Artificial Intelligence-Driven Drug Discovery in Streptomyces by Wei-Shan Ang, Jodi Woan-Fei Law, Yatinesh Kumari, Vengadesh Letchumanan, Loh Teng-Hern Tan

“…Graphical abstract: The role of machine learning in drug discovery from Streptomyces. …”
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A Comprehensive Review of Facial Beauty Prediction Using Multi-task Learning and Facial Attributes by Ali H. Ibrahem, Adnan M. Abdulazeez

“… Beauty multi-task prediction from facial attributes is a multidisciplinary challenge at the intersection of computer vision, machine learning, and psychology. Despite the centrality of beauty in human perception, its subjective nature—shaped by individual, social, and cultural influences—complicates its computational modeling. …”
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Framework for Holistic Online Optimization of Milling Machine Conditions to Enhance Machine Efficiency and Sustainability by Alexander Bott, Simon Anderlik, Robin Ströbel, Jürgen Fleischer, Andreas Wortmann

“…The research method involved the development of the framework for the realisation and analysis of measurement data from milling machines, focusing on six machine parts and employing a machine learning system for optimization and evaluation. …”
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A toolkit for quantifying individual response to herbal extracts in metabolic and inflammatory stress by Soo-yeon Park, Oran Kwon, Tim van den Broek, Jildau Bouwman, Ji Yeon Kim

“…This study integrated a health space model and machine learning to quantify and visualize the impact of herbal extracts on inflammatory and metabolic health at the individual level. …”
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Estimating Compressive Strength of High Performance Concrete with Gaussian Process Regression Model by Nhat-Duc Hoang, Anh-Duc Pham, Quoc-Lam Nguyen, Quang-Nhat Pham

“…This machine learning approach is utilized to establish the nonlinear functional mapping between the compressive strength and HPC ingredients. …”
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An algorithm to Detect Overlapping Red Blood Cells for Sickle Cell Disease Diagnosis. by Mabirizi, Vicent, Kawuma, Simon, Safari, Yonasi

“…To facilitate early detection of sickle cell anemia, medical experts employ machine learning algorithms to detect sickle cell abnormality. …”
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PCA and PSO based optimized support vector machine for efficient intrusion detection in internet of things by Mutkule Prasad Raghunath, Shyam Deshmukh, Poonam Chaudhari, Sunil L. Bangare, Kishori Kasat, Mohan Awasthy, Batyrkhan Omarov, Rajesh R. Waghulde

“…Evaluating the veracity, exactness, and retrieval rate of different machine learning algorithms is crucial for choosing the most effective ones. …”
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Baseline [18F]FDG PET/CT radiomics for predicting interim efficacy in follicular lymphoma treated with first-line R-CHOP by Zeying Wen, Xiaohe Gao, Qingxia Wu, Jianwei Yang, Jian Sun, Keliu Wu, Hongfei Zhao, Ruihua Wang, Yanmei Li

“…Abstract Objective To investigate the predictive value of machine learning-based PET/CT radiomics and clinical risk factors in predicting interim efficacy in patients with follicular lymphoma (FL). …”
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Toward Integrating ChatGPT Into Satellite Image Annotation Workflows: A Comparison of Label Quality and Costs of Human and Automated Annotators by Jacob Beck, Lukas Malte Kemeter, Konrad Durrbeck, Mohamed Hesham Ibrahim Abdalla, Frauke Kreuter

“…High-quality annotations are a critical success factor for machine learning (ML) applications. To achieve this, we have traditionally relied on human annotators, navigating the challenges of limited budgets and the varying task-specific expertise, costs, and availability. …”
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An Interpretable Model for Salinity Inversion Assessment of the South Bank of the Yellow River Based on Optuna Hyperparameter Optimization and XGBoost by Xia Liu, Yu Hu, Xiang Li, Ruiqi Du, Youzhen Xiang, Fucang Zhang

“…It has been a mainstream trend to use machine-learning methods to achieve monitoring of large-scale salinized soil quickly. …”
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