Research on Optimization of Railway Obstacle Detection Model Based on Neural Architecture Search by YAO Weiwei, LYU Yu, ZHANG Huiyuan, XIONG Minjun, DONG Wenbo, LI Chen

“…The subsequent utilization of a zero-cost neural architecture search algorithm allows for quickly predicting the practical performance of various architectures, without the need for tedious and time-consuming actual training. …”
Get full text

A Dynamic Short-Turning Bus Control for Uncertain Demand by Hu Zhang, Shuzhi Zhao, Huasheng Liu, Jin Li

“…An unfixed rolling horizon was implemented to choose the best dynamic approach. Real-time control predicts two discrete variables (arrival time and bus position) and determines the space-time point of buses. …”
Get full text

Siamese Denoising Autoencoders for Enhancing Adversarial Robustness in Medical Image Analysis by Jaesung Shim, Kyuri Jo

“…This method addresses the reduction in classification accuracy caused by the denoising process. …”
Get full text

Advancing lakes algal chlorophyll estimation in the contiguous USA: A comparative study of machine learning models and satellite data by Md Mamun, Xiao Yang

“…We assess the performance of four ML algorithms (random forest, extra tree regressor, bagging regressor, and xgboost model), discern the most influential spectral bands and indices, and compare these methods to established remote sensing techniques for CHL-a prediction. …”
Get full text

Clinical applications of artificial intelligence and machine learning in neurocardiology: a comprehensive review by Jade Basem, Racheed Mani, Scott Sun, Kevin Gilotra, Neda Dianati-Maleki, Reza Dashti

“…In this review, we identify some of the widely utilized and upcoming AI/ML algorithms for some of the most common cardiac sources of stroke, strokes of undetermined etiology, and cardiac disease secondary to stroke. …”
Get full text

Pre-Hospital Point-of-Care Troponin: Is It Possible to Anticipate the Diagnosis? A Preliminary Report by Cristian Lazzari, Sara Montemerani, Cosimo Fabrizi, Cecilia Sacchi, Antoine Belperio, Marilena Fantacci, Giovanni Sbrana, Agostino Ognibene, Maurizio Zanobetti, Simone Nocentini

“…The rationale of the HEART POCT study is to propose the application of the 0/1 h European Society of Cardiology (ESC) algorithm in the pre-hospital setting using a POCT device (Atellica VTLi). …”
Get full text

Identification of a PANoptosis-related long noncoding rna risk signature for prognosis and immunology in colon adenocarcinoma by Yuekai Cui, Jie Mei, Shengsheng Zhao, Bingzi Zhu, Jianhua Lu, Hongzheng Li, Binglong Bai, Weijian Sun, Wenyu Jin, Xueqiong Zhu, Shangrui Rao, Yongdong Yi

“…Long noncoding RNAs (lncRNAs) play crucial roles in PCD. However, the predictive value of PANoptosis-related lncRNAs (PRlncRNAs) for colon adenocarcinoma (COAD) has not been established. …”
Get full text

Multi-Modal Social Robot Behavioural Alignment and Learning Outcomes in Mediated Child–Robot Interactions by Paul Baxter

“…This behavioural alignment is facilitated by a human memory-inspired learning algorithm that adapts in real-time over the course of an interaction. …”
Get full text

Brugia malayi excreted/secreted proteins at the host/parasite interface: stage- and gender-specific proteomic profiling. by Sasisekhar Bennuru, Roshanak Semnani, Zhaojing Meng, Jose M C Ribeiro, Timothy D Veenstra, Thomas B Nutman

“…Moreover, this analysis was able to confirm the presence of 274 "hypothetical" proteins inferred from gene prediction algorithms applied to the B. malayi (Bm) genome. …”
Get full text

Advanced Technologies for Smart Fertilizer Management in Agriculture: A Review by Jian-Jun Liu, Hao Wu, Imran Riaz

“…This article reviews current challenges and examines proposed solutions, with a focus on precision fertilization enabled by advanced technologies such as geographic information systems, global positioning systems, the internet of things, artificial intelligence and machine learning algorithms, and unmanned aerial and ground vehicles for fertilizer management. …”
Get full text

Reinforcement learning in artificial intelligence and neurobiology by Tursun Alkam, Andrew H Van Benschoten, Ebrahim Tarshizi

“…Empirical studies reveal neural correlates of RL algorithms in the basal ganglia, prefrontal cortex, and hippocampus, supporting their roles in planning, memory, and decision-making. …”
Get full text

Petri graph neural networks advance learning higher order multimodal complex interactions in graph structured data by Alma Ademovic Tahirovic, David Angeli, Adnan Tahirovic, Goran Strbac

“…The work opens new directions in learning over complex structures, transcending transformer-based and traditional hypergraph-based algorithms. We validate results through theoretical analysis and real-world experiments, while demonstrating superior performance in, e.g., stock market prediction.…”
Get full text

Delineating flood susceptibility zones using novel ensemble models – An application of evidential belief function, relative frequency ratio, and Shannon entropy by Samuel Yaw Danso, Yi Ma, Isaac Yeboah Addo

“…Three bivariate statistical algorithms, namely evidential belief function (EBF), relative frequency ratio (RFR), and Shannon entropy (SE) were combined through basic arithmetic operations to produce nine ensemble scenarios. …”
Get full text

Non-Invasive Monitoring of Cerebral Edema Using Ultrasonic Echo Signal Features and Machine Learning by Shuang Yang, Yuanbo Yang, Yufeng Zhou

“…We utilized support vector machine (SVM), logistic regression (LogR), decision tree (DT), and random forest (RF) algorithms for classifying cerebral edema types, and SVM, RF, linear regression (LR), and feedforward neural network (FNNs) for predicting the cerebral infarction volume ratio. …”
Get full text

Investigation of Underlying Biological Association and Targets between Rejection of Renal Transplant and Renal Cancer by Yinwei Chen, Zhanpeng Liu, Qian Yu, Xu Sun, Shuai Wang, Qingyi Zhu, Jian Yang, Rongjiang Jiang

“…The prognosis model showed excellent performance in prognosis prediction in a ccRCC cohort. In addition, the machine learning algorithms identified 19 rejection-related genes, including PLAC8, involved in ccRCC occurrence. …”
Get full text

Artificial intelligence in pancreatic intraductal papillary mucinous neoplasm imaging: A systematic review. by Muhammad Ibtsaam Qadir, Jackson A Baril, Michele T Yip-Schneider, Duane Schonlau, Thi Thanh Thoa Tran, C Max Schmidt, Fiona R Kolbinger

“…The studies were stratified based on prediction target, underlying data type and imaging modality, patient cohort size, and stage of clinical translation and were subsequently analyzed to identify trends and gaps in the field. …”
Get full text

Chaotic billiards optimized hybrid transformer and XGBoost model for robust and sustainable time series forecasting by Reham H. Mohammed, Asmaa Mohamed El-saieed

“…Abstract Accurate wind speed forecasting plays a key role in supporting renewable energy systems, improving flight safety, and enhancing weather prediction. However, the variability and non-stationary nature of wind patterns make reliable forecasting a difficult task. …”
Get full text

Artificial intelligence derived grading of mustard gas induced corneal injury and opacity by Rajnish Kumar, Devansh M. Sinha, Nishant R. Sinha, Ratnakar Tripathi, Nathan Hesemann, Suneel Gupta, Anil Tiwari, Rajiv R. Mohan

“…The ResNet50-based model demonstrated the best performance, achieving 87% training accuracy, and 85% and 83% prediction accuracies on two independent test sets. …”
Get full text

A Theoretical Study of Structural, Electronic, and Vibration Properties of Acetylcholine Chloride and Bromide by Kirill A. Gordienko, Aleksei B. Gordienko, Yurii N. Zhuravlev

“…The ever-growing capabilities of computing systems and algorithms make the first-principle methods extremely important in such research fields as biologically active compounds and complex biological systems. …”
Get full text

Artificial Intelligence Precision Recognition and Auxiliary Diagnosis of Dental X-ray Panoramic Images Based on Deep Learning by Liu Riming, Gao Zhenshan

“…Objective: This study aims to explore the application of deep learning algorithms in dental X-ray panoramic images, particularly for the automatic segmentation of dental caries and identification of wisdom tooth types, in order to improve the accuracy and efficiency of dental diagnosis and assist doctors in formulating precise treatment plans. …”
Get full text