Pri-DDQN: learning adaptive traffic signal control strategy through a hybrid agent by Yanliu Zheng, Juan Luo, Han Gao, Yi Zhou, Keqin Li

“…With the goal of minimizing the waiting time and queue length at intersections, we use double DQN to train the agent, incorporate traffic state and reward into the loss function, and update the target network parameters asynchronously, to improve the agent’s learning ability. …”
Get full text

Effect of a single ultra processed meal on myocardial endothelial function, adenosine mediated effects and cognitive performances by Yousif A. Lucinian, Christine Gagnon, Élise Latour, Virginie Hamel, Josep Iglesies-Grau, Anil Nigam, Francois Harel, Anna Nozza, Martin Juneau, Jean-Claude Moubarac, Louis Bherer, Matthieu Pelletier-Galarneau

Get full text

Deep-learning based multi-modal models for brain age, cognition and amyloid pathology prediction by Chenxi Wang, Weiwei Zhang, Ming Ni, Qiong Wang, Chang Liu, Linbin Dai, Mengguo Zhang, Yong Shen, Feng Gao

“…In this study, we aimed to develop a deep-learning framework that processes and integrates MRI images to more accurately predict brain age, cognitive function, and amyloid pathology. …”
Get full text

Association between insecticide exposomics and cognitive function in older adults: an observational study based on NHANES 2011–2014 by Mengfan Zhang, Xiaofang Guo, Yuanjun Chen, Xinghua Liu, Xingdong Lin

“…ObjectiveThis study aims to investigate the association between exposure to insecticide exposomics and cognitive function, among adults aged 60 and above.MethodsWe employed a multi-stage probability sampling method to analyze data derived from the National Health and Nutrition Examination Survey (NHANES) conducted between 2011 and 2014. …”
Get full text

Detection and position evaluation of chest percutaneous drainage catheter on chest radiographs using deep learning. by Duk Ju Kim, In Chul Nam, Doo Ri Kim, Jeong Jae Kim, Im-Kyung Hwang, Jeong Sub Lee, Sung Eun Park, Hyeonwoo Kim

“…The association between the position and function of the catheter during chest PCD was evaluated.…”
Get full text

Exercise-induced Nogo-A influences rodent motor learning in a time-dependent manner. by Jörg H Stehle, Zhiyuan Sheng, Laura Hausmann, Philipp Bechstein, Oliver Weinmann, Juha Hernesniemi, Joseph S Neimat, Martin E Schwab, Ajmal Zemmar

“…In a skilled motor task (forelimb-reaching), administration of Nogo-A function-blocking antibodies over the course of the first training week led to improved motor learning. …”
Get full text

Elucidating the role of KLRD1 in coronary atherosclerosis: harnessing bioinformatics and machine learning to advance understanding by Huan Liang, Xiao Liang, Man Zheng, Shoudong Wang

Get full text

Enhancing Fault Detection in AUV-Integrated Navigation Systems: Analytical Models and Deep Learning Methods by Huibao Yang, Bangshuai Li, Xiujing Gao, Bo Xiao, Hongwu Huang

Get full text

An air combat maneuver decision-making approach using coupled reward in deep reinforcement learning by Jian Yang, Liangpei Wang, Jiale Han, Changdi Chen, Yinlong Yuan, Zhu Liang Yu, Guoli Yang

“…Specifically, we propose a novel coupled-weight reward function for DRL within the air combat framework. The novel reward function integrates angle and distance so that our DRL maneuver decision model can be trained faster and perform better compared to that of the models use conventional reward functions. …”
Get full text

Federated stochastic gradient averaging ring homomorphism based learning for secure data aggregation in WSN by Saravanakumar Pichumani, T. V. P. Sundararajan, S. M. Ramesh

“…First, the copies of the model or data packets are shared between sensor nodes for performing training using the Federated Averaging learning model. Following which fine tune weights are generated using Stochastic Gradient Averaging function. …”
Get full text

Retinal fundus imaging as biomarker for ADHD using machine learning for screening and visual attention stratification by Hangnyoung Choi, JaeSeong Hong, Hyun Goo Kang, Min-Hyeon Park, Sungji Ha, Junghan Lee, Sangchul Yoon, Daeseong Kim, Yu Rang Park, Keun-Ah Cheon

“…Here, we explored the machine learning (ML) analysis of retinal fundus photographs as a noninvasive biomarker for ADHD screening and stratification of executive function (EF) deficits. …”
Get full text

A construction of heterogeneous transfer learning model based on associative fusion of image feature data by Wen-Fei Tian, Ming Chen, Zhong Shu, Xue-jun Tian

“…Besides, the Gaussian kernel function is employed to control the generated noise in transfer learning. …”
Get full text

Deep Learning Extraction of Tidal Creeks in the Yellow River Delta Using GF-2 Imagery by Bojie Chen, Qianran Zhang, Na Yang, Xiukun Wang, Xiaobo Zhang, Yilan Chen, Shengli Wang

“…Including dice coefficients in the focal loss function improves the model’s gradient and tackles class imbalance within the dataset. …”
Get full text

Human identification via digital palatal scans: a machine learning validation pilot study by Ákos Mikolicz, Botond Simon, Aida Roudgari, Arvin Shahbazi, János Vág

“…Abstract Background This study aims to validate a machine learning algorithm previously developed in a training population on a different randomly chosen population (i.e., test set). …”
Get full text

Integrated multiomics analysis identifies PHLDA1+ fibroblasts as prognostic biomarkers and mediators of biological functions in pancreatic cancer by Rui Wang, Rui Wang, Guan-Hua Qin, Guan-Hua Qin, Yifei Jiang, Fu-Xiang Chen, Fu-Xiang Chen, Zi-Han Wang, Zi-Han Wang, Lin-Ling Ju, Lin Chen, Da Fu, En-Yu Liu, Su-Qing Zhang, Wei-Hua Cai

“…However, the prognostic and functional contributions of distinct CAF subtypes remain inadequately understood. …”
Get full text

Effects of Cerebellar Transcranial Magnetic Stimulation on the Motor Function of Patients With Stroke: A Systematic Review and Meta‐Analysis by Yongxin Zhu, Juncong Yang, Kun Wang, Xianwen Li, Jiahui Ling, Xie Wu, Lianhui Fu, Qi Qi

“…ABSTRACT Background As the core of motor control and learning, the cerebellum is crucial for maintaining posture, regulating muscle tone, and coordinating movement. …”
Get full text

Criteria-calibration approaches to deep learning-based cervical cancer radiation treatment auto-planning by Yongguang Liang, Jingru Yang, Shuoyang Wei, Yanfei Liu, Shumeng He, Kang Zhang, Jie Qiu, Bo Yang

“…A total of three criteria-calibration approaches to solve the data imbalance problem in dose prediction were introduced and compared, including Prediction Tolerance function on uTPS (United Imaging Healthcare Co., Ltd., Shanghai), transfer learning, and mixture density network. …”
Get full text

Differentiating Emphysema From Emphysema-Dominated COPD Patients with CT Imaging Feature and Machine Learning by Guo W, Li M, Li Y, Fan X, Wu L

“…The differing relationships between QCT parameters and lung function in these two groups suggest distinct pathophysiological processes. …”
Get full text

Machine learning applied to mild cognitive impairment: bibliometric and visual analysis from 2015 to 2024 by Huan Liu, Qing Huo, Qing Huo, Qing Huo, Feng Li, Xu Luo, Renli Deng

“…Literature and keyword analysis indicate that MCI prediction, automated monitoring of MCI, continuous evaluation and remote monitoring of cognitive function in individuals with MCI, and interdisciplinary data integration and personalized medicine are current research hotspots and development directions.ConclusionThis study is the first to use bibliometric methods to visualize and analyze the application field of machine learning in MCI, revealing research trends and frontiers in this field. …”
Get full text

Breast lesion classification via colorized mammograms and transfer learning in a novel CAD framework by Abbas Ali Hussein, Morteza Valizadeh, Mehdi Chehel Amirani, Sedighe Mirbolouk

“…In a subsequent step, Machine Learning (ML) algorithms are employed to classify these tumors as malign or benign cases. …”
Get full text