Construction and value of a vestibular function calibration test recognition model based on dual-stream ViT and ConvNeXt architecture by Xu LUO, Peixia WU, Weiming HAO, Yinhong QU, Han CHEN

Subjects: “…vestibular function…”
Get full text

A classification model for power corridors based on the improved PointNet++ network by Li Bo, Liu Siyuan, Wang Xiangfeng, Zou Cunyu

Subjects: “…Deep learning…”
Get full text

AI-based automatic estimation of single-kidney glomerular filtration rate and split renal function using non-contrast CT by Yiwei Wang, Feng Xu, Qiuyue Han, Daoying Geng, Xin Gao, Bin Xu, Wei Xia

Subjects: “…Renal function…”
Get full text

MIMOSNN: Software implementation for MIMO sampling neural network by Lingyan Wu, Gang Cai

Subjects: “…Trainable activation function…”
Get full text

HSoMLSDP: A Hybrid Swarm-Optimized Machine Learning Framework for Software Defect Prediction by Madhusmita Das, Biju R. Mohan, Ram Mohana Reddy Guddeti

Subjects: Get full text

COSMIC-Based Early Software Size Estimation Using Deep Learning and Domain-Specific BERT by Yohannes Sefane Molla, Esubalew Alemneh, Samuel Temesgen Yimer

Subjects: Get full text

YOLOv11-GSF: an optimized deep learning model for strawberry ripeness detection in agriculture by Haoran Ma, Qian Zhao, Runqing Zhang, Chunxu Hao, Wenhui Dong, Xiaoying Zhang, Fuzhong Li, Xiaoqin Xue, Gongqing Sun

Get full text

Deep Learning- and Multi-Point Analysis-Based Systematic Deformation Warning for Arch Dams by Tao Zhou, Xiubo Niu, Ning Ma, Futing Sun, Shilin Gong

“…To this end, this study innovatively proposes a systematic early warning method for arch dams based on deep learning and a multi-measurement point analysis strategy. …”
Get full text

AI post-intervention operational and functional outcomes prediction in ischemic stroke patients using MRIs by Emily Wittrup, John Reavey-Cantwell, Aditya S. Pandey, Dennis J. Rivet II, Kayvan Najarian

“…Machine learning approaches have increasingly aimed to bridge this gap, often utilizing admission-based clinical features; yet, the integration of imaging biomarkers remains underexplored, especially regarding whole 2.5D image fusion using advanced deep learning techniques. …”
Get full text

Combining first principles and machine learning for rapid assessment response of WO3 based gas sensors by Ran Zhang, Guo Chen, Shasha Gao, Lu Chen, Yongchao Cheng, Xiuquan Gu, Yue Wang

Subjects: “…Machine learning…”
Get full text

CIRCUMSTANTIAL ELEMENTS ANALYSIS OF LYDIA MACHOVA’S SPEECH IN THE SECRETS OF LEARNING A NEW LANGUAGE TED TALKS: A SYSTEMIC FUNCTIONAL LINGUISTICS STUDY by Apriliasih Setiawati, Erni Hastuti, Teddy Oswari

“…Systematic Functional Linguistic (SFL) views language as a sign system that can be analysed based on language structure and language use. …”
Get full text

A machine learning-based framework for predicting metabolic syndrome using serum liver function tests and high-sensitivity C-reactive protein by Bahareh Behkamal, Fatemeh Asgharian Rezae, Amin Mansoori, Rana Kolahi Ahari, Sobhan Mahmoudi Shamsabad, Mohammad Reza Esmaeilian, Gordon Ferns, Mohammad Reza Saberi, Habibollah Esmaily, Majid Ghayour-Mobarhan

Subjects: Get full text

Hippocampal Functional Radiomic Features for Identification of the Cognitively Impaired Patients from Low-Back-Related Pain: A Prospective Machine Learning Study by Yang Z, Liang X, Ji Y, Zeng W, Wang Y, Zhang Y, Zhou F

“…After feature selection, machine learning models were trained. Finally, we further analyzed the relationship between the hippocampal functional radiomic features and clinical measures, to explore the clinical significance of these features.Results: The combined radiomic features model logistic regression algorithm superior performance in distinguishing cognitively impaired patients from LBLP (AUC = 0.970, accuracy = 92.3%, sensitivity = 92.3%, specificity = 92.3%) compared to the other models. …”
Get full text

Intelligent rehabilitation in an aging population: empowering human-machine interaction for hand function rehabilitation through 3D deep learning and point cloud by Zhizhong Xing, Zhizhong Xing, Zhizhong Xing, Zhijun Meng, Gengfeng Zheng, Guolan Ma, Lin Yang, Lin Yang, Xiaojun Guo, Li Tan, Yuanqiu Jiang, Huidong Wu

“…Human-machine interaction and computational neuroscience have brought unprecedented application prospects to the field of medical rehabilitation, especially for the elderly population, where the decline and recovery of hand function have become a significant concern. Responding to the special needs under the context of normalized epidemic prevention and control and the aging trend of the population, this research proposes a method based on a 3D deep learning model to process laser sensor point cloud data, aiming to achieve non-contact gesture surface feature analysis for application in the field of intelligent rehabilitation of human-machine interaction hand functions. …”
Get full text

Diagnostic potential of salivary microbiota in persistent pulmonary nodules: identifying biomarkers and functional pathways using 16S rRNA sequencing and machine learning by Xiao Zeng, Qiong Ma, Chun-Xia Huang, Jun-Jie Xiao, Xi Fu, Yi-Feng Ren, Yu-Li Qu, Hong-Xia Xiang, Mao Lei, Ru-Yi Zheng, Yang Zhong, Ping Xiao, Xiang Zhuang, Feng-Ming You, Jia-Wei He

“…Additionally, the PICRUSt2 algorithm was used to predict the microbial functions. Results The salivary microbial composition in pPNs group showed significantly lower α- and β-diversity compared to healthy controls. …”
Get full text

A machine learning model for predicting worsening renal function using one‐year time series data in patients with type 2 diabetes by Mari Watanabe, Shu Meguro, Kaiken Kimura, Michiaki Furukoshi, Tsuyoshi Masuda, Makoto Enomoto, Hiroshi Itoh

“…This model will allow us to identify patients whose renal functions are relatively preserved with eGFR of more than 60 mL/min/1.73 m2 and are likely to benefit clinically from immediate treatment intensification.…”
Get full text

Scaling Up and Enhancing the Functionality of the Electronic Integrated Diseases Surveillance and Response System in Uganda, 2020-2022: Description of the Journey, Challenges, and Lessons Learned by Rodney Mugasha, Andrew Kwiringira, Vivian Ntono, Lydia Nakiire, Immaculate Ayebazibwe, Caroline Kyozira, Allan Niyonzima Muruta, Juliet Namugga Kasule, Dathan M Byonanebye, Judith Nanyondo, Richard Walwema, Francis Kakooza, Mohammed Lamorde

Get full text

LLM-Guided Ensemble Learning for Contextual Bandits with Copula and Gaussian Process Models by Jong-Min Kim

Get full text

Outage Performance and Novel Loss Function for an ML-Assisted Resource Allocation: An Exact Analytical Framework by Nidhi Simmons, David E. Simmons, Michel Daoud Yacoub

Subjects: Get full text

Fortified-Edge 2.0: Advanced Machine-Learning-Driven Framework for Secure PUF-Based Authentication in Collaborative Edge Computing by Seema G. Aarella, Venkata P. Yanambaka, Saraju P. Mohanty, Elias Kougianos

“…This research introduces Fortified-Edge 2.0, a novel authentication framework that addresses critical security and privacy challenges in Physically Unclonable Function (PUF)-based systems for collaborative edge computing (CEC). …”
Get full text