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Immunogenic cell death-related macrophage gene model for prognostic prediction in glioblastoma

Yiming Mao, Ting Li, Wenqiang Lu, Chunhong Li et al. • Discover Oncology (2025)

Abstract Glioblastoma (GBM) is an extremely aggressive and diverse type of brain tumor that is associated with a poor prognosis. Immunogenic cell death (ICD) is a particular form of cellular demise that is closely linked to antineoplastic i...

DOAJ Open Access (DOAJ) DOI: 10.1007/s12672-025-03557-1

Prediction of emergency department revisits among child and youth mental health outpatients using deep learning techniques

Simran Saggu, Hirad Daneshvar, Reza Samavi, Paulo Pires et al. • BMC Medical Informatics and Decision Making (2024)

Abstract Background The proportion of Canadian youth seeking mental health support from an emergency department (ED) has risen in recent years. As EDs typically address urgent mental health crises, revisiting an ED may represent unmet menta...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12911-024-02450-1

A review of the application of machine learning in water quality evaluation

Mengyuan Zhu, Jiawei Wang, Xiao Yang, Yu Zhang et al. • Eco-Environment & Health (2022)

With the rapid increase in the volume of data on the aquatic environment, machine learning has become an important tool for data analysis, classification, and prediction. Unlike traditional models used in water-related research, data-driven...

OPENALEX cc-by-nc-nd DOI: https://doi.org/10.1016/j.eehl.2022.06.001 PMC: 10702893

Bayesian machine learning-based method for prediction of slope failure time

Jie Zhang, Zipeng Wang, Jinzheng Hu, Shihao Xiao et al. • Journal of Rock Mechanics and Geotechnical Engineering (2022)

The data-driven phenomenological models based on deformation measurements have been widely utilized to predict the slope failure time (SFT). The observational and model uncertainties could lead the predicted SFT calculated from the phenomen...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.jrmge.2021.09.010

Design of a Forest Fire Early Alert System through a Deep 3D-CNN Structure and a WRF-CNN Bias Correction

Alejandro Casallas, Camila Jiménez-Saenz, Victor Torres, Miguel Quirama-Aguilar et al. • Sensors (2022)

Throughout the years, wildfires have negatively impacted ecological systems and urban areas. Hence, reinforcing territorial risk management strategies against wildfires is essential. In this study, we built an early alert system (EAS) with ...

DOAJ Open Access (DOAJ) DOI: 10.3390/s22228790

Ultra-broadband and polarization-insensitive metasurface absorber with behavior prediction using machine learning

Shobhit K. Patel, Juveriya Parmar, Vijay Katkar, Fahad Ahmed Al-Zahrani et al. • Alexandria Engineering Journal (2022)

The solar spectrum energy absorption is very important for designing any solar absorber. The need for absorbing visible, infrared, and ultraviolet regions is increasing as most of the absorbers absorb visible regions. We propose a metasurfa...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.aej.2022.03.080

Evaluation of the indirect tensile strength (ITS) of cement-treated clayey soils using XGBoost prediction model

Van-Ngoc Pham, Huu-Dao Do, Thi Phuong Khue Nguyen, Van-Khanh Tran et al. • Tạp chí Khoa học và Công nghệ (2026)

This study develops a data-driven framework using Extreme Gradient Boosting (XGBoost) to predict the Indirect Tensile Strength (ITS) of cement-treated clayey soils. Using 180 specimens with five input variables - cement content, curing time...

DOAJ Open Access (DOAJ) DOI: 10.31130/ud-jst.2026.24(7B).582E

Machine Learning‐Driven Biomaterials Evolution

Ady Suwardi, Fuke Wang, Kun Xue, Ming‐Yong Han et al. • Advanced Materials (2021)

Biomaterials is an exciting and dynamic field, which uses a collection of diverse materials to achieve desired biological responses. While there is constant evolution and innovation in materials with time, biomaterials research has been ham...

OPENALEX DOI: https://doi.org/10.1002/adma.202102703

GAUSSIAN PROCESSES FOR MACHINE LEARNING

Matthias Seeger • International Journal of Neural Systems (2004)

Gaussian processes (GPs) are natural generalisations of multivariate Gaussian random variables to infinite (countably or continuous) index sets. GPs have been applied in a large number of fields to a diverse range of ends, and very many dee...

OPENALEX Open Access DOI: https://doi.org/10.1142/s0129065704001899

Machine Learning with TensorFlow

Nishant Shukla • CERN Document Server (European Organization for Nuclear Research) (2018)

Summary Machine Learning with Tensor Flow gives readers a solid foundation in machine-learning concepts plus hands-on experience coding Tensor Flow with Python. Purchase of the print book includes a free eBook in PDF, Kindle, and ePub forma...

OPENALEX

Machine learning in cardiovascular medicine: are we there yet?

Khader Shameer, Kipp W. Johnson, Benjamin Scott Glicksberg, Joel T. Dudley et al. • Heart (2018)

Artificial intelligence (AI) broadly refers to analytical algorithms that iteratively learn from data, allowing computers to find hidden insights without being explicitly programmed where to look. These include a family of operations encomp...

OPENALEX DOI: https://doi.org/10.1136/heartjnl-2017-311198

Benchmarking Assessment of Supervised Machine Learning Algorithms of K-Nearest Neighbor, Random Forest, Decision Tree and Its Variants Based On Efficiency and Performance Metrics

Y. Y. Abdullahi, A. S. Nur, A. Sale • Journal of Applied Sciences and Environmental Management (2025)

Machine learning provides more verbose algorithms capable of accurately predicting, classifying groups as needed. Consequently, the objective of this paper is to assess the benchmarking of Supervised Machine Learning Algorithms of K-Nearest...

DOAJ Open Access (DOAJ)

Optimization of Operational Parameters for Bio‑Oil Production from Municipal Solid Waste via Microwave Pyrolysis

Mazen Kadhim Shekedl, Farhad Salimi, Neda Azimi • Journal of Renewable Energy and Environment (2026)

The efficiency of bio-oil production from municipal solid waste was investigated using microwave-assisted pyrolysis. The effects of temperature, pyrolysis time, and microwave power on bio-oil yield were evaluated using Response Surface Meth...

DOAJ Open Access (DOAJ) DOI: 10.30501/jree.2026.563599.2716

Application of Machine Learning for Predicting Progression‐Free and Overall Survival in Patients With Renal Cell Carcinoma

Caroline W. Grant, Jerry Li, Swan Lin, Dana Nickens et al. • Clinical and Translational Science (2025)

ABSTRACT Patient outcomes in advanced renal cell carcinoma (RCC) remain poor, with five‐year survival rates ranging from ~10% to 30%. Early projections of therapeutic outcomes could optimize precision medicine and accelerate drug developmen...

DOAJ Open Access (DOAJ) DOI: 10.1111/cts.70348

A diagnostic model based on clinical indicators and radiomics features for superior labral anterior and posterior lesions in the shoulder joint

Hongyu Wang, Lin Wang, Lei Shi, Fei Wang et al. • Journal of Orthopaedic Surgery (2026)

Background Superior labrum anterior and posterior (SLAP) lesions are a common cause of shoulder pain and instability. Accurate diagnosis remains challenging in clinical practice. This study aims to develop and evaluate radiomics models and ...

DOAJ Open Access (DOAJ) DOI: 10.1177/10225536261418429

Artificial Neural Network (ANN) Approach to Predict Tensile Properties of Longitudinally Placed Fiber Reinforced Polymeric Composites including Interphase

Sagar Chokshi, Piyush Gohil, Vijay Parmar, Vijaykumar Chaudhary • Mechanics of Advanced Composite Structures (2025)

Machine Learning has become prevalent nowadays for predicting data on the mechanical properties of various materials and is widely used in various polymeric applications. In the present study, Artificial Neural Network (ANN), a computationa...

DOAJ Open Access (DOAJ) DOI: 10.22075/macs.2024.33874.1664