Enhancing Breast Cancer Diagnosis With Multi-Resolution Vision Transformers and Robust Decision-Making by Margo Sabry, Hossam Magdy Balaha, Khadiga M. Ali, Tayseer Hassan A. Soliman, Dibson Gondim, Mohammed Ghazal, Norah Saleh Alghamdi, Ayman El-Baz

“…The proposed framework uses multiscale feature extraction at three magnification levels (L0, L1, L2 or 16x, 4x, 2x) to capture both fine-grained and high-level tumor features. …”
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Optimization of heat and mass transfer in chemically radiative nanofluids using Cattaneo-Christov fluxes and advanced machine learning techniques by Shazia Habib, Saleem Nasir, Zeeshan Khan, Abdallah S. Berrouk, Waseem Khan, Saeed Islam

“…In contrast, a temperature profile decreases when both the Prandtl number and ratio parameter are increased. …”
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A Complementary Dataset of Scalp EEG Recordings Featuring Participants with Alzheimer’s Disease, Frontotemporal Dementia, and Healthy Controls, Obtained from Photostimulation EEG by Aimilia Ntetska, Andreas Miltiadous, Markos G. Tsipouras, Katerina D. Tzimourta, Theodora Afrantou, Panagiotis Ioannidis, Dimitrios G. Tsalikakis, Konstantinos Sakkas, Emmanouil D. Oikonomou, Nikolaos Grigoriadis, Pantelis Angelidis, Nikolaos Giannakeas, Alexandros T. Tzallas

“…This new dataset enables the study of brain responses to visual stimulation across different cognitive states and supports the development and validation of automated classification algorithms for dementia detection. It offers a valuable benchmark for both methodological comparisons and biological investigations, and it is expected to significantly contribute to the fields of neurodegenerative disease research, biomarker discovery, and EEG-based diagnostics.…”
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Reconsidering CPR protocols: Exploring hypernatremia's role in ventricular tachycardia from a case report by Arthur Gavotto, Jean-Yves Le Guennec, Cyril Amouroux, Pascal Champeroux, Angelo Polito, Jérôme Thireau, Alain Lacampagne, Gilles Cambonie

“…We hypothesized that hypernatremia could increase late sodium current in a context of adrenergic stimulation, both being already known to favour early-after-depolarizations. …”
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Harmonizing Landsat-8 OLI and Sentinel-2 MSI: an assessment of surface reflectance and vegetation index consistency by Jiaqi Zhang, Xiaocheng Zhou, Xueping Liu, Xiaoqin Wang, Guojin He, Youshui Zhang

“…The derived conversion equations were highly accurate for harmonizing data from both sensor systems.…”
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Enhancing energy efficiency of industrial boiler application by the integration of ground-source heat pumps and photovoltaic-thermal solar water collectors by Praveen Barmavatu, Baburao Gaddala, Sharun Mendonca, Sonali Anant Deshmukh, Marco Rosales-Vera, Hussein Togun, Ramalinga Viswanathan Mangalaraja, Vineet Singh Sikarwar

“…The system's performance was evaluated in both heating and cooling modes, with results indicating a GSHP Coefficient of Performance (COP) of 4.2 during winter heating and a PVT collector efficiency of 18 %. …”
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Development of Adaptive Testing Method Based on Neurotechnologies by E. V. Chumakova, D. G. Korneev, M. S. Gasparian

“…However, it remains to answer the question of the need to improve the efficiency of an already implemented network, and, therefore, to conduct research on methods to improve the efficiency of networks, including finer tuning of parameters and learning algorithms, as well as architecture.A well-known and obvious drawback of using LSTMs is their exactingness in terms of equipment and resources, both during training (the training process takes a significant amount of time) and during startup, in our case, it is supplemented by increased requirements for the training sample and casts doubt on the advisability of further study of LSTM networks when solving this task.Conclusion. …”
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Interpretable Multi-Sensor Fusion of Optical and SAR Data for GEDI-Based Canopy Height Mapping in Southeastern North Carolina by Chao Wang, Conghe Song, Todd A. Schroeder, Curtis E. Woodcock, Tamlin M. Pavelsky, Qianqian Han, Fangfang Yao

“…This study presents an explainable machine learning framework that integrates sparse GEDI LiDAR samples with multi-sensor remote sensing data to improve both the accuracy and interpretability of forest canopy height estimation. …”
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Mapping expanded prostate cancer index composite to EQ5D utilities to inform economic evaluations in prostate cancer: Secondary analysis of NRG/RTOG 0415. by Rahul Khairnar, Stephanie L Pugh, Howard M Sandler, W Robert Lee, Ester Villalonga Olives, C Daniel Mullins, Francis B Palumbo, Deborah W Bruner, Fadia T Shaya, Soren M Bentzen, Amit B Shah, Shawn C Malone, Jeff M Michalski, Ian S Dayes, Samantha A Seaward, Michele Albert, Adam D Currey, Thomas M Pisansky, Yuhchyau Chen, Eric M Horwitz, Albert S DeNittis, Felix Y Feng, Mark V Mishra

“…<h4>Conclusions</h4>This is the first study to identify a comprehensive set of mapping algorithms to generate EQ5D utilities from EPIC domain/ sub-domain scores. …”
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Machine learning models for the prediction of preclinical coal workers’ pneumoconiosis: integrating CT radiomics and occupational health surveillance records by Yankun Ma, Fengtao Cui, Yulong Yao, Fuhai Shen, Hongyi Qin, Bing Li, Yan Wang

“…Second, two feature selection algorithms were applied to select critical features from both CT radiomics and occupational health data. …”
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Comparing machine learning models for predicting preoperative DVT incidence in elderly hypertensive patients with hip fractures: a retrospective analysis by Xue Ge, Lan Yao, Yan Liu, Yi Wang, Fang Zhang

“…Various machine learning algorithms were also employed to build predictive models. …”
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Machine learning with the body roundness index and associated indicators: a new approach to predicting metabolic syndrome by Yaxuan He, Zekai Chen, Zhaohui Tang, Yuexiang Qin, Fang Wang

“…Ten machine learning algorithms were evaluated using 10-fold cross-validation. …”
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Individualized post‐operative prediction of cochlear implantation outcomes in children with prelingual deafness using functional near‐infrared spectroscopy by Zhe Chen, Xue Zhao, Haotian Liu, Yuyang Wang, Zhikai Zhang, Yuxuan Zhang, Yuhe Liu

“…Post‐CI auditory and verbal communication performance was evaluated using clinical questionnaires with caretakers. Both classification and individualized regression models were constructed to predict post‐CI behavioral improvement from fNIRS data using support vector machine (SVM) learning algorithms. …”
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Interventions to improve referrals from primary care to outpatient specialist services for chronic conditions: a systematic review and framework synthesis update by Layla Bolton Saghdaoui, Smaragda Lampridou, Sara Tavares, Rachael Lear, Alun Huw Davies, Mary Wells, Sarah Onida

“…When used alone, referral algorithms and staff education were less effective at improving referral rates or appropriateness. …”
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Identification and validation of pyroptosis-related genes in Alzheimer’s disease based on multi-transcriptome and machine learning by Yuntai Wang, Yuntai Wang, Yilin Li, Lu Zhou, Yihuan Yuan, Chuanfei Liu, Zimeng Zeng, Yuanqi Chen, Qi He, Zhuoze Wu

“…Their superior performances were validated through comprehensive bioinformatic analysis in both patient and mouse transcriptomes, as well as the experimental data. …”
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Comparison of safety of lecanemab and aducanumab: a real-world disproportionality analysis using the FDA adverse event reporting system by Lingti Kong, Lingti Kong, Lingti Kong, Xiaohu Yang, Xiaohu Yang, Jian Xu, Jian Xu

“…Additionally, the time-to-onset of ADEs was also compared between the two drugs and between male and female patients.ResultsA total of 1,409 ADE reports in which an anti-Aβ antibody drug was primarily suspected were included in the study, comprising 892 cases (63.31%) of lecanemab and 517 cases (36.69%) of aducanumab. For both lecanemab and aducanumab, only the SOC ‘nervous system disorders’ met the criteria for positive signal for all four algorithms. …”
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Global soil moisture mapping at 5 km by combining GNSS reflectometry and machine learning in view of HydroGNSS by Emanuele Santi, Davide Comite, Laura Dente, Leila Guerriero, Nazzareno Pierdicca, Maria Paola Clarizia, Nicolas Floury

“…Taking advantage of the versatility of both machine learning techniques, several combinations of input data, including CyGNSS observables and auxiliary information, have been exploited and the role of GNSS-R and auxiliary data has been assessed. …”
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Closing the multichannel gap through computational reconstruction of interaction in super-resolution microscopy by Ben Cardoen, Hanene Ben Yedder, Ivan Robert Nabi, Ghassan Hamarneh

“…We review novel interaction-analysis algorithms, and we identify specific SRM factors that can compromise the accuracy of interaction analysis. …”
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The key genes ME1 and ALDH3A1 involved in glycolysis regulate the lactate pathway and mediate COPD related immune dysregulation by Wenli XIE, Guang ZHOU, Zhitao JING, Shilin QIU

“…Subsequently, key genes involved in glycolysis were identified using the LASSO and SVM-RFE algorithms. After subtyping, GSEA analysis was conducted. …”
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Machine Learning in Cyber-Physical Systems and Manufacturing Singularity – it Does Not Mean Total Automation, Human Is Still in the Centre: Part I – Manufacturing Singularity and a... by Goran D. PUTNIK, Vaibhav SHAH, Zlata PUTNIK, Luis FERREIRA

“…In the first part a review of argumentation from literature, both in favor of and against the thesis on the human role in future, is presented. …”
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