Leveraging machine learning and rule extraction for enhanced transparency in emergency department length of stay prediction by Waqar A. Sulaiman, Charithea Stylianides, Andria Nikolaou, Andria Nikolaou, Zinonas Antoniou, Ioannis Constantinou, Lakis Palazis, Anna Vavlitou, Theodoros Kyprianou, Theodoros Kyprianou, Efthyvoulos Kyriacou, Antonis Kakas, Antonis Kakas, Marios S. Pattichis, Andreas S. Panayides, Constantinos S. Pattichis, Constantinos S. Pattichis

Subjects: Get full text

Low-Rank Representation-Based Object Tracking Using Multitask Feature Learning with Joint Sparsity by Hyuncheol Kim, Joonki Paik

“…Next, the features represented by the low-rank and sparse property are learned using a modified joint sparsity-based multitask feature learning framework. …”
Get full text

Versatile waste sorting in small batch and flexible manufacturing industries using deep learning techniques by Arso M. Vukicevic, Milos Petrovic, Nebojsa Jurisevic, Marko Djapan, Nikola Knezevic, Aleksandar Novakovic, Kosta Jovanovic

Subjects: Get full text

AI-Driven Mental Health Surveillance: Identifying Suicidal Ideation Through Machine Learning Techniques by Hesham Allam, Chris Davison, Faisal Kalota, Edward Lazaros, David Hua

Subjects: “…machine learning…”
Get full text

Machine Learning-based Prediction of HBV-related Hepatocellular Carcinoma and Detection of Key Candidate Biomarkers by Zeynep KUCUKAKCALI, Sami AKBULUT, Cemil COLAK

“…Objective: This study aimed to classify open-access gene expression data of patients with hepatitis B virus-related hepatocellular carcinoma (HBV + HCC) and chronic HBV without HCC (HBV alone) using the XGBoost method, one of the machine learning methods, and reveal important genes that may cause HCC. …”
Get full text

Design of Interactive Media for Japanese M-Learning Based on Android Using UML and Waterfall Model by Apriade Voutama, Elfina Novalia

Subjects: “…m-learning, japanese, uml, waterfall, android…”
Get full text

Multi-Task Learning for Alzheimer’s Disease Diagnosis and Mini-Mental State Examination Score Prediction by Jin Liu, Xu Tian, Hanhe Lin, Hong-Dong Li, Yi Pan

Subjects: “…multi-task learning…”
Get full text

Learning to Detect Traffic Incidents from Data Based on Tree Augmented Naive Bayesian Classifiers by Dawei Li, Xiaojian Hu, Cheng-jie Jin, Jun Zhou

“…The structure of TAN classifier for incident detection is learned from data. The discretization of continuous attributes is processed using an entropy-based method automatically. …”
Get full text

Retracted: Deep Learning-Based Multitarget Motion Shadow Rejection and Accurate Tracking for Sports Video by null Complexity

Get full text

Improving Autonomous Vehicle Cognitive Robustness in Extreme Weather With Deep Learning and Thermal Camera Fusion by Mehmood Nawaz, Sheheryar Khan, Muhammad Daud, Muhammad Asim, Ghazanfar Ali Anwar, Ali Raza Shahid, Ho Pui Aaron HO, Tom Chan, Daniel Pak Kong, Wu Yuan

“…When integrated with RGB and LiDAR sensors, the thermal sensor becomes highly beneficial for detecting and locating objects in adverse weather conditions. The proposed deep learning-assisted multi-sensor fusion technique consists of two parts: (1) visual information fusion and (2) object detection using LiDAR, RGB, and Thermal sensors. …”
Get full text

Deep learning-based CT-free attenuation correction for cardiac SPECT: a new approach by Pei Yang, Zeao Zhang, Jianan Wei, Lisha Jiang, Liqian Yu, Huawei Cai, Lin Li, Quan Guo, Zhen Zhao

Subjects: “…Deep learning…”
Get full text

Automated classification of elongated styloid processes using deep learning models-an artificial intelligence diagnostics by Anuradha Ganesan, N. Gautham Kumar, Prabhu Manickam Natarajan, Jeevitha Gauthaman

Subjects: “…deep learning…”
Get full text

Using machine learning models to plan HIV services: Emerging opportunities in design, implementation and evaluation by T Dzinamarira, E Mbunge, I Chingombe, D F Cuadros, E Moyo, I Chitungo, G Murewanhema, B Muchemwa, G Rwibasira, O Mugurungi, G Musuka, H Herrera

Subjects: Get full text

Research on PMF Model Based on BP Neural Network Ensemble Learning Bagging and Fuzzy Clustering by Zhengjin Zhang, Guilin Huang, Yong Zhang, Siwei Wei, Baojin Shi, Jiabao Jiang, Baohua Liang

“…Therefore, this paper proposes a probabilistic matrix factorization model based on BP neural network ensemble learning, bagging, and fuzzy clustering. Firstly, the membership function of fuzzy clustering and the selection of cluster center are used to calculate the user-item rating matrix; secondly, BP neural network trains the user-item scoring matrix after clustering, further improving the accuracy of scoring prediction; finally, the bagging method in ensemble learning is introduced, which takes the number of user-item scores as the base learner, trains the base learner through BP neural network, and finally obtains the score prediction through the voting results, which improves the stability of the model. …”
Get full text

An Evaluation of Secondary School Students’ Use and Understanding of Learning Strategies to Study and Revise for Science Examinations by Fatema Sultana, Richard C. Watkins, Tarek Al Baghal, John Carl Hughes

Subjects: Get full text

Broad Learning-Based Optimization and Prediction of Questionnaire Survey: Application to Mind Status of College Students by Lin Yu, Shejiao Ding

“…This paper focused on the data analysis using the recent developed broad learning method to obtain the learning model and then the prediction can be done. …”
Get full text

Machine learning model and nomogram to predict the risk of heart failure hospitalization in peritoneal dialysis patients by Liping Xu, Fang Cao, Lian Wang, Weihua Liu, Meizhu Gao, Li Zhang, Fuyuan Hong, Miao Lin

Subjects: Get full text

Using drawing to learn about figurative language among tertiary EFL English literature students by Clara Boon Ing Ling, Che Aleha Ladin, Jia Wei Lim

Subjects: Get full text

Electrogastrogram-based detection of cybersickness with the application of wavelet transformation and machine learning: A case study by Ilija V. Tanasković, Nenad B. Popović, Jaka J. Sodnik, Sašo J. Tomažič, Nadica S. Miljković

Subjects: Get full text

A Machine Learning-Based Platform for Monitoring and Prediction of Hazardous Gases in Rural and Remote Areas by Edgar F. Ladeira, Bruno M. C. Silva

“…Hence, this paper presents a digital decision support system that uses Machine Learning (ML) for monitoring and prediction of incidents related with indoor hazardous gases. …”
Get full text