Machine learning-based detection of medical service anomalies: Kazakhstan’s health insurance data by Maksut Kulzhanov, Alexander Wagner, Abylkair Skakov, Iliyas Mukhamejan, Saya Zhorabek, Ainur B. Qumar

“…With the exponential growth of medical data and limited analytical resources, healthcare systems are increasingly adopting Artificial Intelligence (AI) and Machine Learning (ML) technologies to enhance their decision-making processes. This research aims to apply advanced ML algorithms to analyze data from the Republic of Kazakhstan’s Obligatory Health Insurance Fund (OHIF) and automatically detect anomalies in the structure of delivered medical services. …”
Get full text

HARDWARE AND SOFTWARE COMPLEX FOR FUNCTIONAL STATE MONITORING OF MOTHER AND FETUS by I. V. Tolmachyov, K. S. Brazovsky, A. S. Tsverova, V. S. Ripenko

“…This technique is passive for a body so there is no research time limit. Device for simultaneous registration of fetal and maternal electrocardiogram is high sensitive bioamplifier with low level of intrinsic noises, high input resistance and suppression of inphase noises more than 80 DB. …”
Get full text

Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…Specifically, our precision reached 96.10%, sensitivity was 95.35%, specificity achieved 97.06%, and accuracy was 96.10%. This research enhances the precision of DR diagnosis by applying it to different publicly accessible datasets. …”
Get full text

Local Outlier Detection Method Based on Improved K-means by Yu ZHOU, Hao XIA, Xuezhen YUE, Peichong WANG

“…They are often regarded as noise points due to their deviation from normal data points and are considered points of research value, occupying a small proportion of the dataset. …”
Get full text

Advanced Machine Learning and Deep Learning Approaches for Estimating the Remaining Life of EV Batteries—A Review by Daniel H. de la Iglesia, Carlos Chinchilla Corbacho, Jorge Zakour Dib, Vidal Alonso-Secades, Alfonso J. López Rivero

“…The review introduces an innovative clustering approach that provides a nuanced understanding of research trends and methodological gaps. In addition, we discuss the ethical implications of DL in RUL estimation, addressing concerns about privacy and algorithmic bias. …”
Get full text

DEICTIC MITIGATION VS COMMISSIVE ACTS IN POLITICAL INTERVIEW (BASED ON THE MODERN EUROPEAN DISCOURSE OF AID TO UKRAINE) by Nataliia K. Kravchenko, Sviatoslav I. Vylinskyi, Oleksandr I. Yudenko

“…The purpose is achieved by solving the following objectives that determine the research algorithm, including (a) felicity conditions revealing for commissives, weakened by shields that affect the illocutionary force of acts; (b) identifying those deictic coordinates of statements, the reference to which weakens the illocutionary force of commissives; (c) lexical-semantic and syntactic deictic mitigators complex determination. …”
Get full text

Permanent Laser Scanning and 3D Time Series Analysis for Geomorphic Monitoring using Low-Cost Sensors and Open-Source Software by L. de Vugt, E. Carraro, A. Fatihi, E. Mattea, E. Myall, D. Czerwonka-Schröder, K. Anders

“…By comparing the results obtained from both systems, this research highlights the potential of low-cost alternatives for continuous geomorphic monitoring, offering valuable insights for cost-effective environmental management and research.…”
Get full text

Immune-related adverse events of neoadjuvant immunotherapy in patients with perioperative cancer: a machine-learning-driven, decade-long informatics investigation by Yuan Meng, Rong Hu, Song-Bin Guo, Deng-Yao Liu, Zhen-Zhong Zhou, Hai-Long Li, Wei-Juan Huang, Xiao-Peng Tian

“…Using an unsupervised clustering algorithm, we identified six dominant research clusters, among which Cluster 1 (standardizing response assessment criteria for NAI to minimize its adverse reactions; average citation=34.86±95.48) had the highest impact and Cluster 6 (efficacy and safety of multiple therapy patterns combination) was an emerging research cluster (temporal central tendency=2022.43, research effort dispersion=0.52), with “irAEs” (s=0.4242 (95% CI: 0.01142 to 0.8371), R2=0.4125, p=0.0453), “ICIs” (immune checkpoint inhibitors) (s=1.127 (95% CI: 0.5403 to 1.714), R2=0.7103, p=0.0022), and “efficacy and safety” (s=0.5455 (95% CI: 0.1145 to 0.9764), R2=0.5157, p=0.0193) showing significant overall growth. …”
Get full text

Multiobjective Approach to the Transit Network Design Problem with Variable Demand considering Transit Equity by Su Jin Park, Seungmo Kang, Young-Ji Byon, Seung-Young Kho

“…Existing research on the transit network design problem has tended to focus on minimizing the various costs for both transit operators and users. …”
Get full text

Autonomous air combat decision making via graph neural networks and reinforcement learning by Lin Huo, Chudi Wang, Yue Han

“…Abstract With the rapid advancement of technology, aerial interaction patterns have become increasingly complex, making intelligent air combat a prominent and cutting-edge research area in multi-agent systems. …”
Get full text

IoT-enabled real-time health monitoring system for adolescent physical rehabilitation by Jie Yang, Juanjuan Hu, Wenrui Chen

“…A particle swarm optimization support vector machine (PSO-SVM) algorithm is utilized to classify motion patterns. …”
Get full text

AI-driven biomarker discovery: enhancing precision in cancer diagnosis and prognosis by Esther Ugo Alum

Get full text

Intelligent Classification Method for Rail Defects in Magnetic Flux Leakage Testing Based on Feature Selection and Parameter Optimization by Kailun Ji, Ping Wang, Yinliang Jia

“…Three key innovations drive this research: (1) A dynamic PSO algorithm incorporating adaptive learning factors and nonlinear inertia weight for precise RBF parameter optimization; (2) A hierarchical feature processing strategy combining mutual information selection with correlation-based dimensionality reduction; (3) Adaptive model architecture adjustment for small-sample scenarios. …”
Get full text

Migrative armadillo optimization enabled a one-dimensional quantum convolutional neural network for supply chain demand forecasting. by Mohamed Irhuma, Ahmad Alzubi, Tolga Öz, Kolawole Iyiola

“…In recent years, numerous methods were developed for Supply Chain (SC) demand forecasting, which posed several limitations related to inadequate handling of dynamic time series patterns and data requirement problems. Thus, this research proposes a Migrative Armadillo Optimization-enabled one-dimensional Quantum convolutional neural network (MiA + 1D-QNN) for effective demand forecasting. …”
Get full text

Faster? Softer? Or More Formal? A Study on the Methods of Enterprises’ Crisis Response on Social Media by Yongtian Yu, Weiming Ye, Kaihang Zhang

“…Algorithmic recommendation mechanisms of social media platforms, viral diffusion of user-generated content (UGC), and real-time public opinion pressures are fundamentally deconstructing the traditional corporate crisis response paradigm that used to rely on one-way statements and delayed reactions. …”
Get full text

Artificial Intelligence in Chest Radiography—A Comparative Review of Human and Veterinary Medicine by Andrea Rubini, Roberto Di Via, Vito Paolo Pastore, Francesca Del Signore, Martina Rosto, Andrea De Bonis, Francesca Odone, Massimo Vignoli

“…However, challenges include smaller datasets, breed variability, and limited research. Addressing these through focused research on species with less phenotypic variability (like cats) and cross-sector collaborations could advance AI in veterinary medicine. …”
Get full text

Adaptive Robust Method for Dynamic Economic Emission Dispatch Incorporating Renewable Energy and Energy Storage by Tingli Cheng, Minyou Chen, Yingxiang Wang, Bo Li, Muhammad Arshad Shehzad Hassan, Tao Chen, Ruilin Xu

Get full text

Secure healthcare data sharing and attack detection framework using radial basis neural network by Abhishek Kumar, Priya Batta, Pramod Singh Rathore, Sachin Ahuja

“…Specifically, the Intelligent Voyage Optimization algorithm effectively tunes the model hyperparameters and the deployment of hybrid features contributes to the proposed model to detect attack patterns effectively. …”
Get full text

Human-Annotated Label Noise and Their Impact on ConvNets for Remote Sensing Image Scene Classification by Longkang Peng, Tao Wei, Xuehong Chen, Xiaobei Chen, Rui Sun, Luoma Wan, Jin Chen, Xiaolin Zhu

“…Additionally, the label noise estimation algorithm (confident learning) cannot fully identify label noise. …”
Get full text

A Spatiotemporal Dataset of Soil Properties in Northeast China Based on Soil Sampling and Interpolation From 2009 to 2020 by Shuzhen Li, Jieyong Wang, Xu Lin, Yaqun Liu

Get full text