Predictive analytics in gamified education: A hybrid model for identifying at-risk students by Devanshu Sawarkar, Latika Pinjarkar, Pratham Agrawal, Devansh Motghare

Get full text

Optimization of MXene-based aqueous ionic liquids for solar systems using conventional and AI-based techniques by Mohamed Bechir Ben Hamida, Ali B. M. Ali, Narinderjit Singh Sawaran Singh, Loghman Mostafa

Get full text

Study on the Optimized Production Scheduling of Polymetallic Mines Considering the Vehicle Routing Problem by Jianfu Luo, Taosuo Wu, Hongmei Bai, Hui Jie

Get full text

Development of a machine learning prognostic model for early prediction of scrub typhus progression at hospital admission based on clinical and laboratory features by Youguang Lu, Zixu Wang, Junhu Wang, Yingqing Mao, Chuanshen Jiang, Jinpiao Wu, Haizhou Liu, Haiming Yi, Chao Chen, Wei Guo, Liguan Liu, Yong Qi

Get full text

Predicting tilling and seeding operation times in grain production: A comparison of machine learning and mechanistic models by Luca Scheurer, Tobias Zimpel, Joerg Leukel

Get full text

Enhancing healthcare AI stability with edge computing and machine learning for extubation prediction by Kuo-Yang Huang, Ying-Lin Hsu, Che-Liang Chung, Huang-Chi Chen, Ming-Hwarng Horng, Ching-Hsiung Lin, Ching-Sen Liu, Jia-Lang Xu

Get full text

Supervised methods of machine learning for email classification: a literature survey by Muath AlShaikh, Yasser Alrajeh, Sultan Alamri, Suhib Melhem, Ahmed Abu-Khadrah

Get full text

Content oriented 3D-CNN sequence learning architecture for academic activities recognition using a realistic CAD dataset by Muhammad Wasim, Imran Ahmed, Naveed Abbas, Tanzila Saba, Faten S. Alamri, Alex Elyassih, Amjad Rehman

“…One major requirement is to develop lightweight adaptable models capable of recognizing academic activities, enabling effective decision making in various application domains. This research article proposes a lightweight 3D-CNN architecture for recognizing a novel set of academic activities using a realistic campus video dataset. …”
Get full text

Analysis of Traffic Conflicts at Roundabout Entrances and Exits – A Machine Learning Approach for Enhanced Safety by Yuzhou DUAN, Zhipeng LIN, Yulong WANG, Qiaowen BAI

Get full text

Risk Factors and Prediction Model for Postoperative Pneumonia Following Hip Arthroplasty in Older Adults by Xiang B, Zhang J, Deng C, Yang H, Qian L, Zhang W

“…The Brier score of the calibration curve was 0.103 (close to 0), and decision curve analysis indicated that the threshold probability of the model ranged from 0.01 to 0.8, with net benefits greater than 0 across all probabilities, suggesting the model has good accuracy and clinical utility.Conclusion: We identified six important predictors—ASA grade, ICU admission, preoperative anemia, CKMB, BNP, and postoperative AST levels—and developed a risk prediction model for postoperative pneumonia following hip arthroplasty in older adults, providing a valuable reference for its prevention in this population.Keywords: arthroplasty, replacement, hip, pneumonia, risk factors, prediction algorithms, aged…”
Get full text

Optimized feature selection and advanced machine learning for stroke risk prediction in revascularized coronary artery disease patients by Yong Si, Armin Abdollahi, Negin Ashrafi, Greg Placencia, Elham Pishgar, Kamiar Alaei, Maryam Pishgar

Get full text

Distributionally robust microgrid formation for service restoration in distribution systems against extended extreme events by Ran Zhu, Hongzhe Liu, Wenwu Yu, Wei Gu, Jin Zhao

“…Furthermore, to enhance the computational efficiency, a parallel solving strategy is developed, based on the column-and-constraint generation algorithm, the alternating optimization procedure, and the progressive hedging algorithm. …”
Get full text

Optimization of management of patients with critical lower limb ischemia, allowing for risk of gangrene by A. V. Bykov, N. A. Korenevsky, S. A. Parkhomenko, I. I. Khripina

“…For each identified class, confidence in the development of gangrene was determined by an individual treatment strategy, implemented in accordance with the intelligent decision support system by a decision-making algorithm.Results. …”
Get full text

Development of several machine learning based models for determination of small molecule pharmaceutical solubility in binary solvents at different temperatures by Mohammed Alqarni, Ali Alqarni

“…Given the complex, non-linear patterns in solubility behavior, three advanced regression approaches were utilized: Polynomial Curve Fitting, a Bayesian-based Neural Network (BNN), and the Neural Oblivious Decision Ensemble (NODE) method. …”
Get full text

Graph reinforcement learning-driven source-load cooperative scheduling optimization for textile production by Tianhao Tan, Tao Wu, Jie Li, Yuyuan Lan, Jinsong Bao

Get full text

LASSO-derived nomogram prediction model for lymph node metastasis in colorectal cancer: a retrospective analysis by Xiyun Quan, Yi Deng, Zhimin Liu, Zhenqin Gao, Huimei Yi, Ming Li

Get full text

Cross-Domain Fake Review Detection via Orthogonal Counterfactual Representations by Richa Gupta, Vinita Jindal, Indu Kashyap

“…Working of the proposed COAT is divided in three phases: 1) two-step masking to remove source-specific cues, 2) counterfactual generation using BERT, followed by orthogonal alignment via Procrustes algorithm, and 3) training and prediction using a Bi-LSTM classifier in a zero-shot setting. …”
Get full text

Evaluating ChatGPT-4o for ophthalmic image interpretation: From in-context learning to code-free clinical tool generation by Joon Yul Choi, Tae Keun Yoo

“…Methods: We assessed ChatGPT-4o through three clinically relevant tasks: (1) image interpretation without prior examples, using fundus, external ocular, and facial photographs representing key ophthalmic conditions; (2) in-context learning with example-based prompts to improve classification accuracy; and (3) generation of an interactive HTML-based decision-support tool from a clinical diagnostic algorithm. …”
Get full text

Loss profit estimation using association rule mining with clustering by Mandeep Mittal, Sarla Pareek, Reshu Agarwal

Get full text

Water quality index modelling and its application on artificial intelligence (AI) in conjunction with machine learning (ML) methodologies for mapping surface water potential zones... by Abhijeet Das

“…., World Health Organization guidelines is implanted to decipher the values ranging from natural to anthropogenic contribution.In the Mahanadi River Basin, Odisha, however, this study has highlighted the evaluation of surface water quality (WQ) for drinking reasons by the combined use of Machine Learning (ML) methodologies like Genetic Algorithm Particle Swarm Optimization-based WQI (GAPSO-WQI), with dependability-oriented decision-making approaches such as Firefly Algorithm (FA) and Algorithm of Weeds (AW), that have been used for river water quality monitoring and assessment due to their dependability and feasibility. …”
Get full text