Table 1_Exploring fecal microbiota signatures associated with immune response and antibiotic impact in NSCLC: insights from metagenomic and machine learning approaches.docx by Wenjie Han (1812673)

“…Among eight machine learning algorithms evaluated, the optimal model was selected to construct a predictive framework for immunotherapy response.…”

Particle swarm optimization method for energy management of the hybrid system of an electric vehicle charging station by Olukorede Adenuga (20139099)

“…The developed PSO methods and algorithms can be useful for the resolution of numerous energy management problems in smart grid applications, provincial and national control centers, and research and educational institutions.…”

Supplementary file 1_Multimodal data-driven prognostic model for predicting long-term outcomes in older adult patients with sarcopenia: a retrospective cohort study.pdf by Mengdie Liu (21416774)

“…Feature selection was performed using Lasso Regression, XGBoost, and Random Forest machine learning algorithms, and a nomogram model was developed using univariate and multivariate Cox regression analyses, with validation of its accuracy, concordance, and clinical applicability.…”

Figures for heart attack prediction using ML by Krishnaraj Chadaga (20563994)

“…<p dir="ltr">Heart attack prediction using machine learning involves analyzing biomarkers such as cholesterol levels, blood pressure, heart rate, glucose levels, and inflammatory markers like C-reactive protein to assess risk. Advanced algorithms, including logistic regression, decision trees, random forests, and deep learning models, process this data to identify patterns linked to heart attacks. …”

Chemical Composition-Driven Machine Learning Models for Predicting Ionic Conductivity in Lithium-Containing Oxides (Supporting Information) by Yudai IWAMIZU (20747538)

“…Thus, new models demonstrating improved prediction ability must be developed. This study presents the development of machine learning models for the accurate prediction of ionic conductivity in lithium-containing materials based solely on their chemical composition. …”

Verification and Validation for Trustworthy Scientific Machine Learning by Lorena A. Barba (97553)

“…This work aims to catalyze community dialogue toward consensus-based standards for predictive SciML, providing researchers with practical guidance for developing models that can be trusted for high-consequence scientific and engineering applications.…”

Source codes for cancer diagnosis and prognosis by Fatih Gurcan (18117955)

“…<p dir="ltr">This code is developed to analyze the performance of various classification algorithms and resampling methods on cancer diagnostic and prognostic datasets, encompassing data preprocessing, model training, and evaluation processes.…”

Comprehensive Dataset for Event Classification Using Distributed Acoustic Sensing (DAS) Systems by Adrian Tomasov (19664054)

“…This dataset is ideal for researchers developing and validating machine learning algorithms for DAS-based applications, including structural health monitoring and perimeter security.…”

Figure 2 from Autofluorescence Virtual Staining System for H&E Histology and Multiplex Immunofluorescence Applied to Immuno-Oncology Biomarkers in Lung Cancer by Jessica Loo (20526803)

“…<p>pIHC and segmentation algorithms were developed for mIF model development and evaluation. …”

Tactile, Audio, and Visual Dataset During Bare Finger Interaction with Textured Surfaces by Alexis Devillard (17000451)

“…Through carefully designed data collection protocols, encompassing both controlled and free exploration scenarios, this dataset lays the groundwork for understanding human multi-sensory integration and supports the development of algorithms for texture recognition based on multi-modal inputs. …”

N0.1 ChinaCUI: Long-term Spatiotemporal Distribution Dataset of Cropland Cultivation Intensity in China (1982–Present)​ by Bingwen QIU (17449565)

“…<p dir="ltr">This dataset is developed based on a series of robust Cropland Utilization Intensity (CUI) algorithms, enabling the automatic acquisition of large-scale agricultural cropping pattern information. …”

N0.2 ChinaCUI: Long-term Spatiotemporal Distribution Dataset of Cropland Cultivation Intensity in China (1982–Present) by Bingwen QIU (17449565)

“…<p dir="ltr">This dataset is developed based on a series of robust Cropland Utilization Intensity (CUI) algorithms, enabling the automatic acquisition of large-scale agricultural cropping pattern information. …”

DATA SHEET.csv by Dola Saha (20556497)

“…Its ability to improve accuracy, efficiency, and consistency in diagnosis makes it an indispensable tool for early detection efforts.This study focuses on developing a machine learning-based predictive model for the early detection and classification of breast cancer, utilizing the Wisconsin Breast Cancer Diagnostic dataset. …”

Microscopic Detection and Quantification of Microplastic Particles in Environmental Water Samples by Derek Lam (11944213)

“…To address this gap, we developed an imaging-based approach for detecting and quantifying microplastic particles in environmental water samples, offering a complementary method for enhanced water quality monitoring.…”

A Radiograph Dataset for the Classification, Localization, and Segmentation of Primary Bone Tumors by Shunhan Yao (20296506)

“…This publicly available dataset can support the development and evaluation of deep learning algorithms for the diagnosis of primary bone tumors.…”

Preprocessed Spatial Dynamic Wind Power Forecasting (SDWPF) Dataset from Baidu KDD Cup 2022 Challenge by Yuan Shi (22779782)

“…</p><p dir="ltr">This processed dataset is suitable for research and development in wind power forecasting models, offering a clean and standardized input for machine learning algorithms.…”

Behavioral raw data recorded by HABITS autonomously by bowen yu (19822908)

“…Supported by the microcontroller-based general programming framework, we have not only replicated established paradigms in current neuroscience research but also developed several novel paradigms previously unexplored in mice, resulting in more than 300 mice tested in various cognition functions. …”

pointpairs.json by Juan Wang (115708)

“…This data represents the pairwise correspondence of single reflections traced via OptiX, specifically recording the point-to-point mapping relationships generated by single reflection events in the optical simulation process, which can support the verification and optimization of specular surface reconstruction algorithms.…”

Coupling machine learning and group contribution method to predict density and viscosity of ionic liquid-inorganic solvent-water ternary mixtures by Sulei Ma (18629684)

“…<p>Accurate prediction of the physical properties of mixed systems is essential for efficient industrial design and process optimization. This study explores the use of a hybrid approach that combines the group contribution (GC) method with advanced machine learning (ML) algorithms to predict the density and viscosity of ternary mixtures comprising ionic liquids (ILs), inorganic solvents (ICs), and water. …”

Image 1_Biological and prognostic insights into the prostaglandin D2 signaling axis in lung adenocarcinoma.pdf by Qiang Liu (166143)

“…Furthermore, we found that a risk model developed based on this signaling axis could predict responses to immune therapy in hot and cold tumors, suggesting potential drugs that may benefit low-risk patients. …”