Multiple imputation integrated to machine learning: predicting post-stroke recovery of ambulation after intensive inpatient rehabilitation by Alice Finocchi, Silvia Campagnini, Andrea Mannini, Stefano Doronzio, Marco Baccini, Bahia Hakiki, Donata Bardi, Antonello Grippo, Claudio Macchi, Jorge Navarro Solano, Michela Baccini, Francesca Cecchi

“…The random forest (the validation best-performing algorithm) obtained 75.5% aggregated balanced accuracy on the test set. …”
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Aided Greenway Design Approach Based on Internet Big Data and AIGC Fine-Tuning Model by Yifan WU, Lu MENG, Liang LI

“…SnowNLP is employed to analyze the sentiment of texts associated with images, obtain the sentiment score of images, and correct image score in combination with the microblog interaction data, with the corrected sentiment score being taken as the basis for image quality judgment. The image data collected is gradually cleaned and filtered into a training set for LoRA fine-tuning model training.ResultsThe LoRA model for the greenway scenario is successfully obtained by applying the approach. …”
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The diagnostic efficacy of seven autoantibodies in early detection of ground-glass nodular lung adenocarcinoma by Hua Guo, Wei Zhao, Chunsun Li, Zhen Wu, Ling Yu, Miaoyu Wang, Yuanhui Wei, Zirui Wang, Shangshu Liu, Yue Yin, Zhen Yang, Liangan Chen

“…Our study set cut-off values for seven autoantibodies in identifying GGNs no more than 3cm and constructed a machine learning model for effective diagnosis. …”
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A neural network design for black-box identification of converter impedance models in arbitrary operating conditions by CHEN Bing, ZHAO Chongbin, JIANG Qirong, WANG Xu, WANG Fangming

“…In the model verification phase, the network is fed with set operating conditions, achieving highly accurate identification of stable operating conditions and offline prediction.…”
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Chess Position Evaluation Using Radial Basis Function Neural Networks by Dimitrios Kagkas, Despina Karamichailidou, Alex Alexandridis

“…The proposed approach introduces models based on the radial basis function (RBF) neural network architecture trained with the fuzzy means algorithm, in conjunction with a novel set of input features; different methods of network training are also examined and compared, involving the multilayer perceptron (MLP) and convolutional neural network (CNN) architectures and a different set of input features. …”
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A Pilot Study: Sleep and Activity Monitoring of Newborn Infants by GRU-Stack-Based Model Using Video Actigraphy and Pulse Rate Variability Features by Ádám Nagy, Zita Lilla Róka, Imre Jánoki, Máté Siket, Péter Földesy, Judit Varga, Miklós Szabó, Ákos Zarándy

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Importance Analysis of Causative Nodes for Accident Chains of Railway Locomotive Operation Based on STPA-PageRank Method by Ping WAN, Wei-Lun YANG, Jie-Wen LUO, Xiao-Feng MA

“…Firstly, 68 sets of data of railway locomotive operation accidents happened in recent two years were collected and compiled. …”
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Endocranial Morphology in Metopism by Silviya Nikolova, Diana Toneva, Gennady Agre

“…This study aimed to compare the endocranial space in metopic and control crania using morphometric analysis and machine learning algorithms. …”
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Observer of changes in the forest of the shortest paths on dynamic graphs of transport networks by N. V. Khajynova, M. P. Revotjuk, L. Y. Shilin

“…The purpose of the work is the development of basic data structures, speed-efficient and memoryefficient algorithms for tracking changes in predefined decisions about sets of shortest paths on transport networks, notifications about which are received by autonomous coordinated transport agents with centralized or collective control. …”
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U-Sodar: Noncontact Vital Sign Detection Technology Based on Ultrasonic Radar by Shuaiming HUANG, Xiaohua ZHU, Wubin WANG, Heng ZHAO, Hong HONG

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Exploring stroke risk factors in different genders using Bayesian networks: a cross-sectional study involving a population of 134,382 by Liqin Linghu, Yaxin Huang, Lixia Qiu, Xuchun Wang, Jia Zhang, Lin Ma, chenglian Li, Lijie Wang

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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

“…In particular, precisely generating motion trajectories is a prerequisite to controlling exoskeleton assistive devices, and deep learning-based prediction algorithms, such as Long–Short-Term Memory (LSTM) networks, have proven effective in forecasting joint trajectories of gait. …”
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Upper limb human-exoskeleton system motion state classification based on semg: application of CNN-BiLSTM-attention model by Dongwei Zhao, Xiangming Ye, Song Wang, Chenfeng Zhang, Shouqian Sun, Xuequn Zhang, Ruidong Cheng

“…The proposed model achieved a classification accuracy of 97.29% on the test set, with an average accuracy of 88.17 ± 5.39% under leave-one-subject-out cross-validation, outperforming baseline algorithms. …”
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A Longitudinal Multimodal Dataset of Type 1 Diabetes by Ashwaq Alsuhaymi, Ahmad Bilal, Daniel Gasca García, Rujiravee Kongdee, Nicole Lubasinski, Hood Thabit, Paul W. Nutter, Simon Harper

“…The dataset includes longitudinal (3-month) real-world data collected from 17 PwT1D participants. By making this resource available, the study aims to advance algorithm development and improve diabetes management, particularly in settings where AID technology is less accessible.…”
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Real-time temperature prediction of large-scale lithium battery module driven by data based on few measurement points by Jiajie HAN, Qingyang YUAN, Yu LI, Bo ZHANG, Ke XUE, Tian LAN

“…This database captures essential thermal characteristics of the battery module, allowing for accurate temperature predictions without exhaustive simulations. The Gappy POD algorithm is further enhanced by incorporating a correlation coefficient filtering technique, which identifies a minimal set of optimal measurement points to ensure high accuracy in the reconstructed temperature field while reducing sensor requirements. …”
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RETRACTED ARTICLE: Screening and identification of susceptibility genes for cervical cancer via bioinformatics analysis and the construction of an mitophagy-related genes diagnosti... by Zhang Zhang, Fangfang Chen, Xiaoxiao Deng

“…Method We initially collected a large amount of genomic data, including gene expression profile and single nucleotide polymorphism (SNP) data, from the control group and Cervical cancer (CC) patients. …”
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Development experience of information system for ranking of academic and pedagogical staff by A. A. Chernousov, E. V. Vavilova

“…As a result, the concept of an automated rating system of Plekhanov Russian University of Economics was based on the following design decisions: dynamic setting of indicators and algorithms of ranking, the dynamic configuration of the personal account of the rated academic and pedagogical staff, external configuring of control parameters, the possibility of creating extensible libraries of output forms, the use of Internet technologies.Results. …”
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Verifying the Effects of the Grey Level Co-Occurrence Matrix and Topographic–Hydrologic Features on Automatic Gully Extraction in Dexiang Town, Bayan County, China by Zhuo Chen, Tao Liu

“…Erosion gullies can reduce arable land area and decrease agricultural machinery efficiency; therefore, automatic gully extraction on a regional scale should be one of the preconditions of gully control and land management. The purpose of this study is to compare the effects of the grey level co-occurrence matrix (GLCM) and topographic–hydrologic features on automatic gully extraction and guide future practices in adjacent regions. …”
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Application of artificial neural networks in the drilling processes: Can equivalent circulation density be estimated prior to drilling? by Husam H. Alkinani, Abo Taleb T. Al-Hameedi, Shari Dunn-Norman, David Lian

“…Once ECD is recognized, the crucial drilling variables impact ECD can be modified to control ECD within the acceptable ranges. Data from over 2000 wells collected worldwide were used in this study to create an ANN to predict ECD prior to drilling. …”
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Machine learning to improve HIV screening using routine data in Kenya by Jonathan D. Friedman, Jonathan M. Mwangi, Kennedy J. Muthoka, Benedette A. Otieno, Jacob O. Odhiambo, Frederick O. Miruka, Lilly M. Nyagah, Pascal M. Mwele, Edmon O. Obat, Gonza O. Omoro, Margaret M. Ndisha, Davies O. Kimanga

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