Mechanistic Learning for Predicting Survival Outcomes in Head and Neck Squamous Cell Carcinoma by Kevin Atsou, Anne Auperin, Jôel Guigay, Sébastien Salas, Sebastien Benzekry

“…This model demonstrated unbiased OS4 prediction, suggesting its potential for improving HNSCC treatment evaluation. …”
Get full text

Enhancing Image Annotation With Object Tracking and Image Retrieval: A Systematic Review by Rodrigo Fernandes, Alexandre Pessoa, Marta Salgado, Anselmo De Paiva, Ishak Pacal, Antonio Cunha

“…Effective image and video annotation is a fundamental pillar in computer vision and artificial intelligence, crucial for the development of accurate machine learning models. Object tracking and image retrieval techniques are essential in this process, significantly improving the efficiency and accuracy of automatic annotation. …”
Get full text

Image-based yield prediction for tall fescue using random forests and convolutional neural networks by Sarah Ghysels, Bernard De Baets, Dirk Reheul, Steven Maenhout

“…RGB images of tall fescue individuals were processed by two types of predictive models: a random forest and convolutional neural network. …”
Get full text

VTGAN based proactive VM consolidation in cloud data centers using value and trend approaches by Aya I. Maiyza, Hanan A. Hassan, Walaa M. Sheta, Karim Banawan, Noha O. Korany

“…Additionally, incorporating VTGAN into the VM placement algorithm to disregard hosts predicted to become overloaded further improves performance. …”
Get full text

Machine Learning–Based Prediction of Early Complications Following Surgery for Intestinal Obstruction: Multicenter Retrospective Study by Pinjie Huang, Jirong Yang, Dizhou Zhao, Taojia Ran, Yuheng Luo, Dong Yang, Xueqin Zheng, Shaoli Zhou, Chaojin Chen

“…A risk predictive model based on machine learning is helpful for early diagnosis and timely intervention. …”
Get full text

Explainable Boosting Machines Identify Key Metabolomic Biomarkers in Rheumatoid Arthritis by Fatma Hilal Yagin, Cemil Colak, Abdulmohsen Algarni, Ali Algarni, Fahaid Al-Hashem, Luca Paolo Ardigò

“…EBM, LightGBM, and AdaBoost algorithms were applied to generate a discriminatory model between RA and controls. …”
Get full text

A Cross-Stage Focused Small Object Detection Network for Unmanned Aerial Vehicle Assisted Maritime Applications by Gege Ding, Jiayue Liu, Dongsheng Li, Xiaming Fu, Yucheng Zhou, Mingrui Zhang, Wantong Li, Yanjuan Wang, Chunxu Li, Xiongfei Geng

“…The CFSD-UAVNet model was evaluated on the publicly available SeaDronesSee maritime dataset and compared with other cutting-edge algorithms. …”
Get full text

Strategies and Challenges in Detecting XSS Vulnerabilities Using an Innovative Cookie Collector by Germán Rodríguez-Galán, Eduardo Benavides-Astudillo, Daniel Nuñez-Agurto, Pablo Puente-Ponce, Sonia Cárdenas-Delgado, Mauricio Loachamín-Valencia

“…The results highlight the system’s effectiveness in detecting security threats and improving navigation through adaptive recommendations. …”
Get full text

Development of intelligent tools to predict neuroblastoma risk stratification and overall prognosis based on multiphase enhanced CT and clinical features by Wei Zhao, Yahui Han, Xiaokun Yu, Jianing Liu, Jiao Zhang, Juan Li

“…The aim of this study was to develop a deep learning model based on multiphase enhanced CT images and clinical features to improve the accuracy of risk stratification and prognostic assessment of NB.MethodsMulti-phase enhanced CT images and clinical features from 202 NB patients were collected. …”
Get full text

Application of artificial intelligence technologies for the detection of early childhood caries by Priyanka A, Rishi Sreekumar, S Namasivaya Naveen

“…This study examined various approaches, datasets, methodologies, and algorithms. The inclusion criteria are the accuracy of models, the investigation of different risk factors, and the applicability of ML and DL in caries prediction. …”
Get full text

Interpretable machine learning for predicting optimal surgical timing in polytrauma patients with TBI and fractures to reduce postoperative infection risk by Xing Han, Jia-Hui Zhang, Xin Zhao, Xi-Guang Sang

“…SHAP and LIME algorithms were utilized for model interpretation, elucidating the importance and predictive thresholds of the variables. …”
Get full text

A Large-Scale Inter-Comparison and Evaluation of Spatial Feature Engineering Strategies for Forest Aboveground Biomass Estimation Using Landsat Satellite Imagery by John B. Kilbride, Robert E. Kennedy

“…We contextualize this improvement model performance by comparing to AGB models developed with multi-temporal features derived from the LandTrendr and Continuous Change Detection and Classification algorithms. …”
Get full text

Short-term prediction of trimaran load based on data driven technology by Haoyun Tang, Rui Zhu, Qian Wan, Deyuan Ren

“…To highlight the trimaran high-frequency load fluctuation and improve the prediction accuracy, the LSTM neural network combines with different signal decomposition algorithms, such as Empirical Mode Decomposition (EMD), Ensemble Empirical Mode Decomposition (EEMD), Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN), and Variational Mode Decomposition (VMD). …”
Get full text

Predicting Alzheimer's Disease onset: A machine learning framework for early diagnosis using biomarker data by Shehu Mohammed, Neha Malhotra

“…Future work will be aimed at increasing the variability of the dataset and the clinical trials to test the model to improve its applicability and performance in actual practice.…”
Get full text

Enhancing Daylight and Energy Efficiency in Hot Climate Regions with a Perforated Shading System Using a Hybrid Approach Considering Different Case Studies by Basma Gaber, Changhong Zhan, Xueying Han, Mohamed Omar, Guanghao Li

“…A hybrid approach integrating parametric modeling, machine learning, multi-criteria decision-making (MCDM), and genetic algorithm (GA) is used to optimize the design incorporating architects’ preferences. …”
Get full text

A shape-controlled non-symmetric quaternary refinement scheme by Pakeeza Ashraf, Samra Younus, Amna Kalsoom, Jihad Younas

“…Abstract The interpolating and approximating refinement schemes are well-studied algorithms to generate smooth curves and surfaces. In this paper, we propose a novel non-symmetric refinement scheme that combines the strengths of interpolating and approximating refinement algorithms. …”
Get full text

Un enfoque de machine learning para apoyar la identificación de la deuda técnica en arquitectura by Boris Rainiero Pérez-Gutiérrez, Darío Ernesto Correal, Fredy Humberto Vera-Rivera

“…Conclusions: The data used to train the model, while appropriate, is susceptible to further improvement. …”
Get full text

Spectral analysis of rotor current of induction motor as indicator of its effectiveness by V. L. Kodkin, A. S. Anikin, A. A. Baldenkov

“…These experiments demonstrating the operation of the drive at low loads corresponding to a slip of 3%, with a load close to the nominal corresponding slip of 8-10%, convincingly demonstrated that the torque generation algorithm implemented in standard frequency inverters (for example, ATV, Schneider Electric) is not the most effective, at the same time, a constructive solution is proposed that improves the dynamics of the drive by almost half, making it close to the dynamics of permanent magnet motors. …”
Get full text

Human-based metaheuristics and non-parametric learning for groundwater-prone area mapping by Seyed Vahid Razavi-Termeh, Abolghasem Sadeghi-Niaraki, Seyedeh Zeinab Shogrkhodaei, Biswajeet Pradhan, Soo-Mi Choi

“…This research introduces a novel approach combining human-based metaheuristics—Teaching Learning Based Optimization (TLBO) and Cultural Algorithms (CA)—with non-parametric Decision Tree (DT) models. …”
Get full text

Integrating UAV-Based Multispectral Data and Transfer Learning for Soil Moisture Prediction in the Black Soil Region of Northeast China by Tong Zhou, Shoutian Ma, Tianyu Liu, Shuihong Yao, Shenglin Li, Yang Gao

“…Among these models, the LSTM model exhibited the most significant performance improvement and the best transferability. …”
Get full text