HKA-Net: clinically-adapted deep learning for automated measurement of hip-knee-ankle angle on lower limb radiography for knee osteoarthritis assessment by Young-Tak Kim, Beom-Su Han, Jung Bin Kim, Jason K. Sa, Je Hyeong Hong, Yunsik Son, Jae-Ho Han, Synho Do, Ji Seon Chae, Jung-Kwon Bae

Get full text

Survival Prediction of Esophageal Cancer Using 3D CT Imaging: A Context-Aware Approach With Non-Local Feature Aggregation and Graph-Based Spatial Interaction by Fuce Guo, Chen Huang, Shengmei Lin, Yongmei Dai, Qianshun Chen, Shu Zhang, Xunyu XU

“…Moreover, we found that retaining lymph nodes with major axis <inline-formula> <tex-math notation="LaTeX">$\geq 8$ </tex-math></inline-formula>mm yields the best predictive results (C-index: 0.725), offering valuable guidance on choosing prognostic factors for esophageal cancer.For EC survival prediction using solely 3D CT images, integrating lymph node information with tumor information helps to improve the predictive performance of deep learning models.Clinical impact: The American Joint Committee on Cancer (TNM) classification serves as the primary framework for risk stratification, prognostic evaluation, and therapeutic decision-making in oncology. Nevertheless, this prognostic tool has demonstrated limited predictive accuracy in assessing long-term survival for esophageal carcinoma patients undergoing multimodal therapeutic regimens. …”
Get full text

An Institutional Theory Framework for Leveraging Large Language Models for Policy Analysis and Intervention Design by J. de Curtò, I. de Zarzà, Leandro Sebastián Fervier, Victoria Sanagustín-Fons, Carlos T. Calafate

Get full text

An optimization based framework for water quality assessment and pollution source apportionment employing GIS and machine learning techniques for smart surface water governance by Abhijeet Das

“…Surface water quality assessment sought to determine whether surface water was suitable for drinking using integrated approaches such as: Decision-Making Trial and Evaluation Laboratory (DEMATEL/De)-based water quality index (WQI). …”
Get full text

The influence of an interactive educational approach on advance care planning counseling in individuals with psychiatric disorders by Yi-Chien Chen, Fang-Ying Chu, Ling-Yu Chang, Ming-Yuan Hsieh, Chao-Hsien Lee

“…This leads to a reduction in their autonomy in healthcare decision-making. Advocacy for and experiential understanding of Advance Care Planning (ACP) among individuals with psychiatric disorders are significantly lacking. …”
Get full text

Assessing the utility of the COVID-19 epidemic Situations of Concern classification system in guiding operational responses to the pandemic in the WHO African region: retrospective... by Opeayo Ogundiran, Jessica L. Abbate, Jessica L. Abbate, Sooyoung Kim, Mamadou Saliou Kalifa Diallo, Michel Muteba, Daniel Cardoso Portela Camara, Lucas Bianchi, Thierno Balde, Boniface Oyugi, Ann Fortin, Jayne Baykika-Tusiime, George Sie Williams, Franck Mboussou, Charles Okot, Freddy Mutoka Banza, Kabego Laundry, Ephraim Nonso Ejiofor, Trevor M. Kanyowa, Rashidatu Kamara, Phionah Atuhebwe, Nicksy Gumede, Belinda Loiuse Herring, Solomon Woldetsadik, Joseph Okeibunor, Etien Koua, Dick Chamla, Fiona Braka, Abdou Salam Gueye

Get full text

Factors affecting the design of the management dashboard framework with an emphasis on the components of human resources productivity by Hassan Barmaki, Farshad Faezy Razi, Ehtesham Rashidi

“…Senior managers and middle managers in organizations must make decisions faster and more accurately than before. …”
Get full text

SMART DELAY PREDICTION: SUPERVISED MACHINE LEARNING SOLUTIONS FOR CONSTRUCTION PROJECTS by Pramodini Sahu, Dillip Kumar Bera, Pravat Kumar Parhi, Meenakshi Kandpal

Get full text

Multispectral Semantic Segmentation for Land Cover Classification: An Overview by Leo Thomas Ramos, Angel D. Sappa

Get full text

Improved Consistency of Lung Nodule Categorization in CT Scans with Heterogeneous Slice Thickness by Deep Learning-Based 3D Super-Resolution by Dongok Kim, Jae Hyung Park, Chang Hyun Lee, Young-Ju Kim, Jong Hyo Kim

Get full text

The Prediction of Outcomes in Patients Admitted with Traumatic Brain Injury Using the Rotterdam Score by Bikram Shakya, Bidur KC

“…Its strong discriminative ability supports its clinical utility for early risk assessment, aiding decision-making and resource allocation. …”
Get full text

Autonomous and sustainable machine learning: pursuing new horizons of intelligent systems by Witold Pedrycz

“…Autonomous systems including autonomous vehicles, user identification (both using audio and video channels), financial systems (calling for sound mechanisms to quantify risk levels) require the ML system making classification or prediction decisions some level of self-awareness. …”
Get full text

Utilization of artificial intelligence-based pulmonary nodule target reconstruction software in clinical practice education for standardized training residents by Fang Cao, Pingshan Zhao, Yi Lin, Xiren Xu, Zheng Guan, Yanqing Ma

“…Abstract Background The precise evaluation of pulmonary nodules via computed tomography (CT) is pivotal in clinical decision-making and patient prognosis. …”
Get full text

Quality Assessment of Innovation and Entrepreneurship Talent Cultivation in Universities from the Perspective of Collaborative Education Under Triangular Neutrosophic Cubic Linguis... by Qing Tan, Chengcheng Wu, Xuan Li, Yao Yao

Get full text

Exploring Perspectives on Student Engagement and Learning Outcomes in Online-Offline English Teaching: A Structured Assessment Using SuperHyperSoft and PSI Methods by Dongqiao Chu

“…This paper evaluates the impact of online-offline blended teaching modes on student engagement and learning outcomes, utilizing a structured multi-criteria decision-making (MCDM) approach. By assessing key criteria such as participation levels, content retention, and interaction quality, this study aims to provide insights into the most effective teaching methodologies for enhancing language acquisition and student performance in university English courses. …”
Get full text

Internet of Things Enabled Machine Learning-Based Smart Systems: A Bird’s Eye View by Ashish Kumar Rastogi, Swapnesh Taterh, Billakurthi Suresh Kumar

“…The IoT gathers environmental data and automates decision-making using sophisticated methods based on human judgement. …”
Get full text

Advancing flood susceptibility prediction: A comparative assessment and scalability analysis of machine learning algorithms via artificial intelligence in high‐risk regions of Paki... by Mirza Waleed, Muhammad Sajjad

“…The evaluation framework presented is applicable to other flood‐prone regions and highlights that LGBM is superior for accuracy‐focused applications, while XGBoost is optimal for scenarios with computational constraints. The findings of this study can assist in accurate FSM in different regions and can also assist in scaling up the analysis to a larger geographical region which could assist in better decision‐making and informed policy production for flood risk management.…”
Get full text

Coronary artery disease classification using ConvMixer based classifier from CT angiography images by C. Rajeev, Karthika Natarajan

“…Lastly, post-image analysis was conducted using DL heat maps to understand the decisions made by the proposed model. The proposed integrated DL intelligent system enhances the efficiency of illness diagnosis, reduces manual involvement in diagnostic processes, supports medical professionals in diagnostic decision-making, and offers supplementary techniques for future medical diagnostic systems based on coronary angioplasty.…”
Get full text

Agenda setting for health equity assessment through the lenses of social determinants of health using machine learning approach: a framework and preliminary pilot study by Maryam Ramezani, Mohammadreza Mobinizadeh, Ahad Bakhtiari, Hamid R. Rabiee, Maryam Ramezani, Hakimeh Mostafavi, Alireza Olyaeemanesh, Ali Akbar Fazaeli, Alireza Atashi, Saharnaz Sazgarnejad, Efat Mohamadi, Amirhossein Takian

Get full text

Leveraging machine learning models in evaluating ADMET properties for drug discovery and development by Magesh Venkataraman, Gopi Chand Rao, Jeevan Karthik Madavareddi, Srinivas Rao Maddi

“…This review aims to investigate how recent advances in machine learning (ML) models are revolutionizing ADMET prediction by enhancing accuracy, reducing experimental burden, and accelerating decision-making during early-stage drug development. …”
Get full text