Ensemble learning guided survival prediction and chemotherapy benefit analysis in high-grade chondrosarcoma: A study based on the surveillance, epidemiology, and end results (SEER)... by Xu Zheng, Longqiang Shu, Shanyi Lin, Hanqiang Jin, Xiaoyu Wang, Ting Yuan

“…According to the ensemble model, overall survival generally improved in younger patients after chemotherapy. …”
Get full text

An adaptive defense mechanism to prevent advanced persistent threats by Yi-xi Xie, Li-xin Ji, Ling-shu Li, Zehua Guo, Thar Baker

“…The evaluation shows that the proposed algorithm has about 10% security utility improvement compared to the state-of-the-art.…”
Get full text

Saliva-derived transcriptomic signature for gastric cancer detection using machine learning and leveraging publicly available datasets by Catarina Lopes, Andreia Brandão, Manuel R. Teixeira, Mário Dinis-Ribeiro, Carina Pereira

“…Leveraging transcriptomic data from the Gene Expression Omnibus (GEO), we constructed and validated predictive models through machine learning algorithms within the tidymodels framework. …”
Get full text

Identifying the best reference gene for RT-qPCR analyses of the three-dimensional osteogenic differentiation of human induced pluripotent stem cells by Masakazu Okamoto, Yusuke Inagaki, Kensuke Okamura, Yoshinobu Uchihara, Kenichiro Saito, Akihito Kawai, Munehiro Ogawa, Akira Kido, Eiichiro Mori, Yasuhito Tanaka

“…Reverse transcription quantitative real-time polymerase chain reaction (RT-qPCR) is an essential tool for gene expression analysis; choosing appropriate reference genes for normalization is crucial to ensure data reliability. However, most studies on osteogenic differentiation have had limited success in identifying optimal reference genes. …”
Get full text

Experimental and numerical investigations on the bidirectional thermal contact performance by Chen Wang, Mingjun Qiu, Huijing Liu, Jun Hong, Feiyu Gu, Lifei Chen, Tao Wang, Hao Guan, Qiyin Lin

“…Additionally, a prediction model for TCR was developed using the Levenberg-Marquardt (L-M) algorithm. …”
Get full text

Current status and outlook of UWB radar personnel localization for mine rescue by ZHENG Xuezhao, MA Jiawen, HUANG Yuan, LI Qiang, REN Jing, LIU Yu

“…Future research directions of UWB radar personnel localization technology for mine rescue operations are proposed: ① optimizing the UWB radar localization system by constructing cross-modal information fusion models and developing highly adaptive signal processing methods to enhance the system's adaptability to post-mining disaster environments; ② improving the applicability of combined static and dynamic target localization by developing hybrid localization algorithms that integrate Bayesian networks or deep belief networks to fuse static and dynamic target features and establishing state-switching-based comprehensive models; ③ improving UWB radar echo processing algorithms, combining adaptive beamforming technology, Multiple Input Multiple Output (MIMO) technology, and optimized K-means++ or entropy-based hierarchical analysis algorithms, effectively distinguishing multi-target position information, and validating their adaptability and reliability in complex environments through extensive simulation experiments.…”
Get full text

Reliable Autism Spectrum Disorder Diagnosis for Pediatrics Using Machine Learning and Explainable AI by Insu Jeon, Minjoong Kim, Dayeong So, Eun Young Kim, Yunyoung Nam, Seungsoo Kim, Sehoon Shim, Joungmin Kim, Jihoon Moon

“…XAI techniques were employed to improve model transparency, offering insights into how features contribute to predictions, thereby enhancing clinician trust. …”
Get full text

Low-light image enhancement method based on retinex theory and dual-tree complex wavelet transform by Yuqian Zhang, Jie Jiang, Zhan Wang, Qi Zhang, Yudi Jiang, Jun Liu, Zeyao Hou

“…To address these problems, various Low-light Image Enhancement (LIE) algorithms have been developed in recent years, including histogram-based methods, gamma correction, and approaches based on Retinex theory. …”
Get full text

Analisis Kinerja Intrusion Detection System Berbasis Algoritma Random Forest Menggunakan Dataset Unbalanced Honeynet BSSN by Kuni Inayah, Kalamullah Ramli

“…One way to improve IDS performance is by using machine learning. …”
Get full text

Innovative Lightweight Detection for Airborne Remote Sensing: Integrating G-Shuffle and Dynamic Multiscale Pyramid Networks by Ruofei Liang, Yigang Cen, Linna Zhang, Fugui Zhang, Yansen Huang, Fei Gan

“…To address the challenges of significant scale variations and difficulty in extracting discriminative features for small targets in airborne remote sensing object detection, while considering the constraints and efficiency requirements of onboard systems, this article proposes a lightweight detection algorithm. First, a structural reparameterization strategy is applied to optimize depthwise separable convolutions, simplifying complex structures during the inference stage, which improves inference speed and memory utilization. …”
Get full text

Current application, possibilities, and challenges of artificial intelligence in the management of rheumatoid arthritis, axial spondyloarthritis, and psoriatic arthritis by Emre Bilgin

“…Predictive algorithms help stratify and predict disease outcomes, while clinical decision support systems integrate clinical and imaging data for optimized management. …”
Get full text

Machine Learning Unveils the Impacts of Key Elements and Their Interaction on the Ambient-Temperature Tensile Properties of Cast Titanium Aluminides Employing SHAP Analysis by Shiqiu Liu, Li Liang

“…Comparative analysis of three algorithms within the training dataset proved the random forest regression (RFR) as the optimal modeling approach. …”
Get full text

Myoelectric Control in Rehabilitative and Assistive Soft Exoskeletons: A Comprehensive Review of Trends, Challenges, and Integration with Soft Robotic Devices by Alejandro Toro-Ossaba, Juan C. Tejada, Daniel Sanin-Villa

“…Additionally, we identify persistent challenges such as EMG signal variability, computational complexity, and the real-time adaptability of control algorithms, which limit clinical implementation. By interpreting recent trends, this review highlights the need for improved EMG acquisition techniques, robust adaptive control frameworks, and enhanced real-time learning to optimize human-exoskeleton interaction. …”
Get full text

Application of precision agriculture technologies for crop protection and soil health by Emogine Mamabolo, Makgabo Johanna Mashala, Ephias Mugari, Tlou Elizabeth Mogale, Norman Mathebula, Kabisheng Mabitsela, Kwabena Kingsley Ayisi

“…Among the technologies, spectral imaging emerged as the most widely used for early detection of plant stress, diseases, and pests, followed by machine learning algorithms, UAVs (Unmanned Aerial Vehicles), and IoT (Internet of Things) devices, all of which enable real-time monitoring and targeted interventions. …”
Get full text

Predicting biomarkers of progressive pulmonary fibrosis: morphological, cytokine profile, and clinical portrait by Nicol Bernardinello, Federica Pezzuto, Lauren D’Sa, Luca Vedovelli, Chiara Giraudo, Anamaria Chelu, Anamaria Chelu, Cecilia de Chellis, Francesca Lunardi, Francesco Fortarezza, Francesca Boscaro, Elisabetta Cocconcelli, Paolo Spagnolo, Elisabetta Balestro, Fiorella Calabrese

“…Lung specimens revealed a significant overexpression of IL9 in the PPF compared to the nPPF group (p=0.049). Boruta algorithm analysis showed that lymphoid aggregates and traction bronchiectasis at diagnosis are the most important variables in determining the PPF status.ConclusionsThe present results increase the understanding of the pathological mechanisms of PPF, offering potential avenues for improved prognostication and therapeutic intervention.…”
Get full text

Possibilities of magnet-resonance tomography usage while examining patients with reccurent genital prolapse by Banakhevych R.M.

“…Complex problem of establishing a diagnosis and choosing optimal treatment for patients with recurrent genital prolapse calls for improving preoperative clinical examination of these patients. …”
Get full text

Machine Learning Based Flexible Transmission Time Interval Scheduling for eMBB and uRLLC Coexistence Scenario by Jingxuan Zhang, Xiaodong Xu, Kangjie Zhang, Bufang Zhang, Xiaofeng Tao, Ping Zhang

Get full text

SiCRNN: A Siamese Approach for Sleep Apnea Identification via Tracheal Microphone Signals by Davide Lillini, Carlo Aironi, Lucia Migliorelli, Leonardo Gabrielli, Stefano Squartini

“…The final detection of <i>apnea</i> events is performed using an unsupervised clustering algorithm, specifically <i>k-means</i>. Multiple experimental runs were carried out to determine the optimal network configuration and the most suitable type and frequency range for the input data. …”
Get full text

High-voltage defibrillator unit with increased energy output from a controlled capacitor storage by E. E. Gorokhov-Miroshnikov, G. V. Slyusarev

“…It has been established that it is possible to form a pulse with a virtually constant output energy in a wide range of patient resistances. The model of the proposed high-voltage unit shows the possibility of increasing the energy output from the capacitor bank when forming a pulse of optimal duration with a flat front. …”
Get full text

Adversarial Sample Generation Method Based on Frequency Domain Transformation and Channel Awareness by Yalin Gao, Dongwei Xu, Huiyan Zhu, Qi Xuan

“…To solve these problems, we propose a super-resolution denoising residual network (SDRNet), which combines the advantages of the super-resolution convolutional neural network (SRCNN) and the denoising convolutional neural network (DnCNN) to construct a pilot-based OFDM signal model, train SDRNet using OFDM pilot data containing Gaussian noise, and optimize its feature enhancement ability in frequency-selective fading channels. …”
Get full text