Enhanced MRI brain tumor detection using deep learning in conjunction with explainable AI SHAP based diverse and multi feature analysis by Asif Rahman, Maqsood Hayat, Nadeem Iqbal, Fawaz Khaled Alarfaj, Salem Alkhalaf, Fahad Alturise

“…In a small dataset, CNN obtained 97.8% accuracy while SVC yielded 98.06% accuracy. In subsequent analysis, a large benchmark dataset is also utilized to evaluate the performance of learning algorithms in order to investigate the generalization power of the proposed model. …”
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The Significance of Cellular Senescence Hub Genes in the Diagnosis and Subtype Classification of a Comprehensive Database of Gene Expression in Intervertebral Disc Degeneration by Fei Liu, Silong Gao, Ji Yin, Chao Song, Yongliang Mei, Zhaoqiang Wang, Zongchao Liu

“…Results We ultimately identified four hub cellular CSRGs DUSP3, MAPKAPK5, SP1, and VEGFA, and further validated their expression using various algorithms and clinical samples. Our results revealed that DUSP3 and SP1 were upregulated in IVDD, while MAPKAPK5 and VEGFA were downregulated. …”
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Quantum secured blockchain framework for enhancing post quantum data security by Nalavala Ramanjaneya Reddy, Supriya Suryadevara, K. Guru Raghavendra Reddy, Ramisetty Umamaheswari, Ramakrishna Guttula, Rajitha Kotoju

“…Experimental evaluation demonstrates that QuantumShield-BC achieves low consensus latency and high throughput, while providing perfect security against simulated attacks from Shor’s and Grover’s algorithms. …”
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Control of three-level quadratic DC-DC boost converters for energy systems using various technique-based MPPT methods by Souheyb Mohammed Belhadj, Bouziane Meliani, Habib Benbouhenni, Ilhami Colak, Z. M. S. Elbarbary, Saad F. Al-Gahtani

“…Therefore, this paper proposes a three-level quadratic DC-DC boost converter as a suitable solution to replace conventional inverters in photovoltaic systems, while combined with an advanced MPPT method. The new approach is MPPT based on NARX neural network (NARAX-NN) algorithms. …”
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Elogio de la lentitud. Modulaciones temporoespaciales de decolonización del dispositivo digital en la sociedad algorítmica by Verónica Paula Gómez

“…This leads to the strengthening of an algorithmic society in which the opacity of information means the loss of futurity in the hands of a closed circuit of knowledge-power and truth. …”
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Identification and analysis of the endoplasmic reticulum stress hub genes in sepsis-associated ARDS by Ling Gao, Tingting Liu, Xiaoyan Li

“…The aim of this study was to identify and analyze hub genes related to ERS in sepsis-associated ARDS using bioinformatics and machine learning algorithms, which may serve as diagnostic markers and therapeutic targets. …”
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Advancing Agile Software Cost Estimation Through Data Synthesis: A Comparative Analysis of Five Generation Techniques by Xiaoyan Zhao, Zulkefli Mansor, Rozilawati Razali, Mohd Zakree Ahmad Nazri, Xin Xiong

“…This is reflected in the fact that the accuracy of estimation still needs improvement, and most cost estimation techniques still rely on the team’s experience and knowledge. While machine learning algorithms have performed better in this area, the lack of sufficient agile cost data hinders large-scale training and in-depth research. …”
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Leveraging machine learning to proactively identify phishing campaigns before they strike by Kun Zhang, Haifeng Wang, Meiyi Chen, Xianglin Chen, Long Liu, Qiang Geng, Yu Zhou

“…These algorithms were chosen for their strong global search capabilities and adaptability to complex datasets, ensuring optimal parameter selection for improved model performance. …”
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Diagnostic Models for Differentiating COVID-19-Related Acute Ischemic Stroke Using Machine Learning Methods by Eylem Gul Ates, Gokcen Coban, Jale Karakaya

“…Various feature selection algorithms were applied to identify the most relevant features, which were then used to train and evaluate machine learning classification models. …”
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Development and Validation of a Questionnaire for the Assessment of Diabetic Peripheral Neuropathy: Implications for Clinical Practice in Physical Therapy and Patient Management by Constantin CIUCUREL, Mariana TUDOR, Elena Ioana ICONARU

“…Introduction: The aim of this study is to develop and validate a questionnaire that evaluates the impact of diabetic peripheral neuropathy (DPN) on quality of life and functional capacity in older adults, while also exploring correlations between clinical factors and DPN severity to guide personalized treatment strategies. …”
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Enhancing Regional Topsoil Total Nitrogen Mapping Through Differentiated Fusion of Ground Hyperspectral Data and Satellite Images Under Low Vegetation Cover by Rongpeng He, Jihua Meng, Yanfei Du, Zhenxin Lin, Xinyan You, Xinyu Gao

“…Therefore, a differentiated fusion of enhanced multispectral image bands (DFE_MSIBs) method combined with Random Forest (RF) algorithms was developed for spectral inversion of STN content. …”
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Development and validation of a machine learning model for online predicting the risk of in heart failure: based on the routine blood test and their derived parameters by Jianchen Pu, Yimin Yao, Xiaochun Wang

“…In addition, eight different machine learning algorithms were applied for prediction, and the prediction performances of these algorithms were comprehensively evaluated using the receiver operating characteristic curve, area under the curve (AUC), calibration curve analysis, and decision curve analysis and confusion matrix.ConclusionsUsing LASSO regression analysis, leukocyte, neutrophil, red blood cell, hemoglobin, platelet, and monocyte-to-lymphocyte ratios were identified as risk factors for HF. …”
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Exploring timely and safe discharge from ICU: a comparative study of machine learning predictions and clinical practices by Chao Ping Wu, Rachel Benish Shirley, Alex Milinovich, Kaiyin Liu, Eduardo Mireles-Cabodevila, Hassan Khouli, Abhijit Duggal, Anirban Bhattacharyya

“…The LightGBM model outperformed other algorithms, achieving a AUROC of 0.91 (95%CI 0.9–0.91) and performance was held in the 2020 validation cohort (n = 509) with an AUROC of 0.85 (95%CI 0.84–0.85). …”
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Optimizing image capture for low-light widefield quantitative fluorescence microscopy by Zane Peterkovic, Avinash Upadhya, Christopher Perrella, Admir Bajraktarevic, Ramses E. Bautista Gonzalez, Megan Lim, Kylie R. Dunning, Kishan Dholakia

“…The tutorial covers a detailed discussion of user-controllable parameters, as well as the application of post-processing algorithms for denoising. We illustrate these concepts using autofluorescence images of live mammalian embryos captured with a two-photon light sheet fluorescence microscope.…”
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An FPGA-accelerated multi-level AI-integrated simulation framework for multi-time domain power systems with high penetration of power converters by Chen Liu, Peng Su, Hao Bai, Xizheng Guo, Alber Filbà Martínez, Jose Luis Dominguez Garcia

“…The framework structures systems hierarchically using energy transmission functions and unified energy information flow-based surrogate models with defined ports, ensuring compatibility with artificial intelligence algorithms. By integrating AI techniques, such as back propagation neural networks, the framework predicts variables with high computational complexity, improving accuracy and simulation efficiency. …”
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A Study on Non-Contact Multi-Sensor Fusion Online Monitoring of Circuit Breaker Contact Resistance for Operational State Awareness by Zheng Wang, Hua Zhang, Yiyang Zhang, Haoyong Zhang, Jing Chen, Shuting Feng, Jie Guo, Yanpeng Lv

“…The contact condition of circuit breaker contacts directly affects their operational reliability, while circuit resistance, as a key performance indicator, reflects physical changes such as wear, oxidation, and ablation. …”
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Machine learning-driven nanoparticle toxicity by Zied Hosni, Sofiene Achour, Fatma Saadi, Yangfan Chen, Mohammed Al Qaraghuli

“…By using a robust dataset, we deployed Random Forest (RF) and Light Gradient Boosting Machine (LightGBM) algorithms to identify key NP features that significantly influence cellular toxicity. …”
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Symmetric Grayscale Image Encryption Based on Quantum Operators with Dynamic Matrices by Luis Olvera-Martinez, Manuel Cedillo-Hernandez, Carlos Adolfo Diaz-Rodriguez, Leonardo Faustinos-Morales, Antonio Cedillo-Hernandez, Francisco Javier Garcia-Ugalde

“…However, existing encryption algorithms often involve complex mathematical operations or require specialized hardware, which limits their efficiency and practicality. …”
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Electrical discharge machining: Recent advances and future trends in modeling, optimization, and sustainability by Muhamad Taufik Ulhakim, Sukarman, Khoirudin, Dodi Mulyadi, Hendri Susilo, Rohman, Muji Setiyo

“…Optimization approaches, including machine learning-based algorithms, multi-objective optimization, and hybrid methods, have enhanced key performance indicators, such as material removal rate (MRR), surface quality, and tool wear, thereby increasing process efficiency and reducing machining time. …”
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Revolutionizing Water Quality Monitoring with Artificial Intelligence: A Systematic Review by Mahmoud Saleh Al-Khafaji, Layth Abdulameer, Muthanna M. A. AL-Shammari, Najah M. L. Al Maimuri, Anmar Dulaimi, Dhiya Al‑Jumeily

“…The novelty of this review lies in its dual focus—quantifying AI's scalability for global water security while critically addressing unresolved challenges in data standardization, model interpretability, and ethical governance. …”
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