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Showing 20 of 967 academic articles

Comparing deep learning and pathologist quantification of cell-level PD-L1 expression in non-small cell lung cancer whole-slide images

Leander van Eekelen, Joey Spronck, Monika Looijen-Salamon, Shoko Vos et al. • Scientific Reports (2024)

Abstract Programmed death-ligand 1 (PD-L1) expression is currently used in the clinic to assess eligibility for immune-checkpoint inhibitors via the tumor proportion score (TPS), but its efficacy is limited by high interobserver variability...

DOAJ Open Access (DOAJ) DOI: 10.1038/s41598-024-57067-1

A novel network-level fused deep learning architecture with shallow neural network classifier for gastrointestinal cancer classification from wireless capsule endoscopy images

Muhammad Attique Khan, Usama Shafiq, Ameer Hamza, Anwar M. Mirza et al. • BMC Medical Informatics and Decision Making (2025)

Abstract Deep learning has significantly contributed to medical imaging and computer-aided diagnosis (CAD), providing accurate disease classification and diagnosis. However, challenges such as inter- and intra-class similarities, class imba...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12911-025-02966-0

A comprehensive construction of deep neural network‐based encoder–decoder framework for automatic image captioning systems

Md Mijanur Rahman, Ashik Uzzaman, Sadia Islam Sami, Fatema Khatun et al. • IET Image Processing (2024)

Abstract This study introduces a novel encoder–decoder framework based on deep neural networks and provides a thorough investigation into the field of automatic picture captioning systems. The suggested model uses a “long short‐term memory”...

DOAJ Open Access (DOAJ) DOI: 10.1049/ipr2.13287

Fast iterative reconstruction for photoacoustic tomography using learned physical model: Theoretical validation

Ko-Tsung Hsu, Steven Guan, Parag V. Chitnis • Photoacoustics (2023)

Iterative reconstruction has demonstrated superior performance in medical imaging under compressed, sparse, and limited-view sensing scenarios. However, iterative reconstruction algorithms are slow to converge and rely heavily on hand-craft...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.pacs.2023.100452

Automated segmentation of brain metastases in T1-weighted contrast-enhanced MR images pre and post stereotactic radiosurgery

Hemalatha Kanakarajan, Wouter De Baene, Patrick Hanssens, Margriet Sitskoorn • BMC Medical Imaging (2025)

Abstract Background and purpose Accurate segmentation of brain metastases on Magnetic Resonance Imaging (MRI) is tedious and time-consuming for radiologists that could be optimized with deep learning (DL). Previous studies assessed several ...

DOAJ Open Access (DOAJ) DOI: 10.1186/s12880-025-01643-y

Evaluating early predictive performance of machine learning approaches for engineering change schedule – A case study using predictive process monitoring techniques

Ognjen Radišić-Aberger, Peter Burggräf, Fabian Steinberg, Alexander Becher et al. • Supply Chain Analytics (2024)

By applying machine learning algorithms, predictive business process monitoring (PBPM) techniques provide an opportunity to counteract undesired outcomes of processes. An especially complex variation of business processes is the engineering...

DOAJ Open Access (DOAJ) DOI: 10.1016/j.sca.2024.100087

Machine learning insight in quality control and maintenance management of drilling mud pumps

Xiaoming Wu, Jingxuan Chang, Chengcheng Long, Hamzeh Ghorbani • Journal of Big Data (2026)

Abstract This study proposes a machine learning-based framework for predictive maintenance and quality control of drilling mud pumps, targeting critical operational challenges such as equipment failure, downtime, and high maintenance costs....

DOAJ Open Access (DOAJ) DOI: 10.1186/s40537-026-01475-9

Introduction to Machine Learning

Richard J. Roiger • Chapman & Hall/CRC eBooks (2020)

R is one of the top-rated problem-solving tools for machine learning, data science, data analytics, data mining, and statistical analysis. R ’s popularity has resulted in the development of thousands of tutorials. Unfortunately, it’s easy t...

OPENALEX DOI: https://doi.org/10.1201/9781003006695-1

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

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

Exploring Traffic Patterns Through Network Programmability: Introducing SDNFLow, a Comprehensive OpenFlow-Based Statistics Dataset for Attack Detection

Jorge Buzzio-Garcia, Jaime Vergara, Santiago Rios-Guiral, Christian Garzon et al. • IEEE Access (2024)

In the contemporary cybersecurity landscape, robust attack detection mechanisms are important for organizations. However, the current state of research in Software-Defined Networking (SDN) suffers from a notable lack of recent SDN-OpenFlow-...

DOAJ Open Access (DOAJ) DOI: 10.1109/ACCESS.2024.3378271

A State-of-the-Art Review on Machine Learning-based Methods for Prostate Cancer Diagnosis

Ari Mohammed ali Ahmed, Aree Ali Mohammed, Professor • UHD Journal of Science and Technology (2021)

Prostate cancer can be viewed as the second most dangerous and diagnosed cancer of men all over the world. In the past decade, machine and deep learning methods play a significant role in improving the accuracy of classification for both bi...

DOAJ Open Access (DOAJ) DOI: https://doi.org/10.21928/uhdjst.v5n2y2021.pp41-47

Source apportionment and stochastic evaluation of soil contamination and human health risks of potentially toxic elements in Nangodi, northern Ghana

Samuel Dzidefo Sagoe, Raymond Webrah Kazapoe, Daniel Kwayisi, Seidu Alidu et al. • Discover Soil (2026)

Abstract Artisanal and Small-Scale Mining (ASM) is a critical driver of soil contamination in West Africa, yet quantifying the relative contributions of natural and anthropogenic sources remains a major challenge. This study presents an int...

DOAJ Open Access (DOAJ) DOI: 10.1007/s44378-026-00229-6

Perceptual-Preference-Based Touring Routes in Xishu Gardens Using Panoramic Digital-Twin Modeling

Xueqian Gong, Zhanyuan Zhu, Li Guo, Yong Zhong et al. • Land (2025)

Xishu Gardens, an exemplary narrative of classical Chinese gardens, faces challenges in preserving its commemorative spatial structures while accommodating modern visitors’ needs. While trajectory analysis is critical, existing studies stru...

DOAJ Open Access (DOAJ) DOI: 10.3390/land14050932