AI-Guided Delineation of Gross Tumor Volume for Body Tumors: A Systematic Review by Lea Marie Pehrson, Jens Petersen, Nathalie Sarup Panduro, Carsten Ammitzbøl Lauridsen, Jonathan Frederik Carlsen, Sune Darkner, Michael Bachmann Nielsen, Silvia Ingala

“…The algorithms with the highest DSC deployed an encoder–decoder architecture. …”
Get full text

A hybrid framework for heart disease prediction using classical and quantum-inspired machine learning techniques by Ankur Kumar, Sanjay Dhanka, Abhinav Sharma, Rohit Bansal, Mochammad Fahlevi, Fazla Rabby, Mohammed Aljuaid

“…Subsequently, both classical and quantum-inspired models are trained and optimized. The classical models utilized Genetic Algorithms (CGA) and Particle Swarm Optimization (CPSO) for hyperparameter tuning, while the quantum-inspired models employed Quantum Genetic Algorithms (QGAs) and Quantum Particle Swarm Optimization (QPSO). …”
Get full text

Application of artificial intelligence in modern healthcare for diagnosis of autism spectrum disorder by Abdullah H. Al-Nefaie, Abdullah H. Al-Nefaie, Theyazn H. H. Aldhyani, Theyazn H. H. Aldhyani, Sultan Ahmad, Eidah M. Alzahrani

“…The assessment of these models used a dataset obtained from Kaggle, consisting of 2,940 face images.ResultsThe suggested Inception-V3 model surpassed current transfer learning algorithms, achieving a 98% accuracy rate.DiscussionRegarding performance assessment, the suggested technique demonstrated advantages over the latest models. …”
Get full text

Enhanced Fishing Monitoring in the Central-Eastern North Pacific Using Deep Learning with Nightly Remote Sensing by Jiajun Li, Jinyou Li, Kui Zhang, Xi Li, Zuozhi Chen

“…The results showed that YOLO-based computer vision models effectively detected dense small fishing targets, with original YOLOv8 achieving a precision (P) of 89% and a recall (R) of 79%, while refined versions improved these metrics to 93% and 99%, respectively. …”
Get full text

MTGNet: Multi-Agent End-to-End Motion Trajectory Prediction with Multimodal Panoramic Dynamic Graph by Yinfei Dai, Yuantong Zhang, Xiuzhen Zhou, Qi Wang, Xiao Song, Shaoqiang Wang

“…This approach not only captures global relationships but also enhances the focus on local features within the scene, thereby improving the model’s sensitivity to local information. …”
Get full text

Explainability Feature Bands Adaptive Selection for Hyperspectral Image Classification by Jirui Liu, Jinhui Lan, Yiliang Zeng, Wei Luo, Zhixuan Zhuang, Jinlin Zou

“…Aiming at the problems of poor interpretability of feature classification algorithms for hyperspectral images, multiple feature dimensions, and difficulty in effectively improving classification accuracy, this paper proposes a feature band adaptive selection method for hyperspectral images. …”
Get full text

Urban heat island classification through alternative normalized difference vegetation index by N. Chanpichaigosol, C. Chaichana, D. Rinchumphu

“…The findings contribute to a deeper understanding of urban heat island effects and provide a basis for enhancing machine Learning models and urban planning frameworks. Future studies could expand to other urban areas, incorporate additional variables, and refine predictive algorithms for broader applications. …”
Get full text

Forecasting motion trajectories of elbow and knee joints during infant crawling based on long–short-term memory (LSTM) networks by Jieyi Mo, Qiliang Xiong, Ying Chen, Yuan Liu, Xiaoying Wu, Nong Xiao, Wensheng Hou

“…It experimentally explores how different input and output time-frames affect prediction accuracy and sets the stage for future research focused on optimizing models and developing effective control strategies to improve assistive crawling devices.…”
Get full text

Fish Detection Using Deep Learning by Suxia Cui, Yu Zhou, Yonghui Wang, Lujun Zhai

“…Because most of the embedded systems have been improved by fast growing computing and sensing technologies, which makes them possible to incorporate more and more complicated algorithms. …”
Get full text

A robot process automation based mobile application for early prediction of chronic kidney disease using machine learning by Md. Hasan Imam Bijoy, Md. Jueal Mia, Md. Mahbubur Rahman, Mohammad Shamsul Arefin, Pranab Kumar Dhar, Tetsuya Shimamura

“…The XAI technique SHAP and model validation on another CKD dataset highlight the superior prediction capabilities of the proposed ensemble methods compared to traditional classification algorithms. …”
Get full text

Real-Time Acoustic Holography for Target Pattern Acoustic Field Reconstruction With Iterative Unsupervised Learning by Minjie Ma, Xuewei Wang, Yang Li, Jia Wang

“…Conventional acoustic field reconstruction algorithms are limited in both speed and accuracy when generating acoustic holograms, which further constrains the practical applications of acoustic holography. …”
Get full text

Synthetic data generation for anomaly detection on table grapes by Ionut M. Motoi, Valerio Belli, Alberto Carpineto, Daniele Nardi, Thomas A. Ciarfuglia

“…Using segmentation masks provided by the Segment Anything Model, we then select and seamlessly blend anomalous berries onto normal ones. …”
Get full text

An exploratory study of high-educated poverty through machine learning approach: a case study of East Java, Indonesia by Dias Satria, Risti Permani, Kodrad Winarno, David Kaluge, Citra Rahayu Indraswari, Radityo Putro Handrito

“… Purpose – the purpose of the article is to compare the importance factors for high-educated poverty modeling in the four cultural regions of East Java.  …”
Get full text

Optimization of Cleaning and Hygiene Processes in Healthcare Using Digital Technologies and Ensuring Quality Assurance with Blockchain by Semra Tebrizcik, Süleyman Ersöz, Elvan Duman, Adnan Aktepe, Ahmet Kürşad Türker

“…The proposed Quality Assurance Model utilizes digital technologies and IoT-based RFID devices to ensure the transparent and reliable monitoring of cleaning processes. …”
Get full text

Analysis of minimum safe approach distances based on vessels navigation safety domain by Igor Burmaka, Olga Petrychenko, Bohdan Alieksieichuk, Alla Vynohradova

“…The results create a foundation for further improvement of collision avoidance algorithms and contribute to increasing the level of automation in navigation processes and overall maritime safety, especially in conditions of heavy traffic or restricted waterways. …”
Get full text

Bearing Fault Diagnosis Grounded in the Multi-Modal Fusion and Attention Mechanism by Jianjian Yang, Haifeng Han, Xuan Dong, Guoyong Wang, Shaocong Zhang

“…The experimental results show that compared to mainstream algorithms such as Vision Transformer, Swin Transformer, and ConvNeXt, the Fusion Attention Network for Bearing Diagnosis (FAN-BD) achieves higher accuracy and robustness in fault diagnosis tasks, providing an efficient and reliable solution for bearing fault diagnosis.The proposed model outperforms ViT, Swin Transformer, ConvNeXt, and CBMA-ViT in terms of classification accuracy, achieving an accuracy of 97.5%. …”
Get full text

Voltage Control Nonlinearity in QZSDMC Fed PMSM Drive System with Grid Filtering by Przemysław Siwek, Konrad Urbanski

“…The structure and control algorithms enabling regulation of the converter’s output voltage in both step-down and step-up modes are presented. …”
Get full text

3D Reconstruction of the Human Colon From Capsule Endoscope Video by Pal Anders Floor, Ivar Farup, Marius Pedersen

“…In this paper, we investigate the possibility of constructing 3D models of whole sections of the human colon using image sequences from wireless capsule endoscope video, providing improved visualization as well as position localization of pathologies for gastroenterologists. …”
Get full text

Sex bias consideration in healthcare machine-learning research: a systematic review in rheumatoid arthritis by Coziana Ciurtin, Shruti Turner, Anahita Talwar, Claudia Maw, Georgina Quayle, Thomas N Watt, Sunir Gohil, Emma Duckworth

“…Only three papers assessed bias in model performance by sex disaggregating their results. …”
Get full text

Calibration of Integrated Low-Cost Environmental Sensors for Urban Air Temperature Based on Machine Learning by Fang Nan, Chao Zeng, Huanfeng Shen, Liupeng Lin

“…Multiple linear regression (MLR) and light gradient boosting machine (LightGBM) algorithms were employed for calibration, with leave-one-out cross-validation (LOOCV) being used for model evaluation. …”
Get full text