Neuromorphic, physics-informed spiking neural network for molecular dynamics by Vuong Van Pham, Temoor Muther, Amirmasoud Kalantari Dahaghi

“…It also leverages the enhanced representation of real biological neural systems through spiking neural network integration with molecular dynamic physical principles, offering greater efficiency compared to conventional AI algorithms. NP-SNN integrates three core components: (1) embedding MD principles directly into the training, (2) employing best practices for training physics-informed ML systems, and (3) utilizing a highly advanced and efficient SNN architecture. …”
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Detecting Post-Midnight Plasma Depletions Through Plasma Density and Electric Field Measurements in the Low-Latitude Ionosphere by Giulia D’Angelo, Emanuele Papini, Alessio Pignalberi, Dario Recchiuti, Piero Diego

“…Plasma depletions in the low-latitude ionosphere are irregularities of special interest in space weather research, as they are highly detrimental to the operation of satellite-based communication and navigation systems. …”
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Co-Occurring Diseases and Mortality in Patients With Chronic Heart Disease, Modeling Their Dynamically Expanding Disease Portfolios: Nationwide Register Study by Nikolaj Normann Holm, Anne Frølich, Helena Dominguez, Kim Peder Dalhoff, Helle Gybel Juul-Larsen, Ove Andersen, Anders Stockmarr

“…MethodsThis study used data from the national Danish registries and algorithmic diagnoses of 15 chronic diseases to obtain a study population of all 766,596 adult patients with HD in Denmark from January 1, 1995, to December 31, 2015. …”
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Impacts of air fraction increase on Arctic sea ice density, freeboard, and thickness estimation during the melt season by E. Salganik, O. Crabeck, O. Crabeck, N. Fuchs, N. Hutter, N. Hutter, P. Anhaus, P. Anhaus, J. C. Landy

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Transformer Models improve the acoustic recognition of buzz-pollinating bee species by Alef Iury Siqueira Ferreira, Nádia Felix Felipe da Silva, Fernanda Neiva Mesquita, Thierson Couto Rosa, Stephen L. Buchmann, José Neiva Mesquita-Neto

“…We document the potential of transformer architectures to improve the performance of audible bee species identification, offering promising new avenues for bioacoustic research and pollination ecology.…”
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Energy-Efficient Recessed-Source/Drain SOI Feedback FET-Based Oscillators and Coupled Networks for Neuromorphic Computing by Sasi Kiran Suddarsi, Dhanaraj Kakkanattu Jagalchandran, Gopi Krishna Saramekala

“…This research introduces the first-ever implementation of non-linear relaxation oscillators and coupled networks utilising energy-efficient Recessed-Source/Drain (Re-S/D) Silicon-On-Insulator (SOI) Feedback Field Effect Transistors (FBFETs). …”
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A Clinically Interpretable Approach for Early Detection of Autism Using Machine Learning With Explainable AI by Oishi Jyoti, Hafsa Binte Kibria, Zareen Tasnim Pear, Md Nahiduzzaman, Md. Faysal Ahamed, Khandaker Reajul Islam, Jaya Kumar, Muhammad E. H. Chowdhury

“…After handling missing values, balancing the dataset, and analyzing the classifier’s performance, it is found that tree-based algorithms, particularly RF, perform better for all the datasets. …”
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Comparison of different downscaling schemes for obtaining regional high-resolution soil moisture data by Yulin Shangguan, Cheng Tong, Zhou Shi, Hongquan Wang, Xiaodong Deng

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Deep reinforcement learning agents for dynamic spectrum access in television whitespace cognitive radio networks by Udeme C. Ukpong, Olabode Idowu-Bismark, Emmanuel Adetiba, Jules R. Kala, Emmanuel Owolabi, Oluwadamilola Oshin, Abdultaofeek Abayomi, Oluwatobi E. Dare

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Comparison of Raman spectroscopy with mass spectrometry for sequence typing of Acinetobacter baumannii strains: a single-center study by Suling Liu, Ni Zhang, Jiawei Tang, Chong Chen, Weisha Wang, Jingfang Zhou, Long Ye, Xiaoli Chen, ZhengKang Li, Liang Wang

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Utilising artificial intelligence in prehospital emergency care systems in low- and middle-income countries: a scoping review by Odhran Mallon, Odhran Mallon, Odhran Mallon, Freddy Lippert, Freddy Lippert, Willem Stassen, Marcus Eng Hock Ong, Caitlin Dolkart, Caitlin Dolkart, Thomas Krafft, Eva Pilot

“…Overall, machine learning algorithms outperformed other comparator methods when they were used in all but two studies.DiscussionLimitations included only analysing articles published in English. …”
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Development of a warning model for drug-induced liver injury in the older patients by Qiaozhi Hu, Qiaozhi Hu, Xiaoqi Li, Xiaoqi Li, Dan Zou, Zhiyao He, Zhiyao He, Ting Xu

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A machine learning model revealed that exosome small RNAs may participate in the development of breast cancer through the chemokine signaling pathway by Jun-luan Mo, Xi Li, Lin Lei, Ji Peng, Xiong-shun Liang, Hong-hao Zhou, Zhao-qian Liu, Wen-xu Hong, Ji-ye Yin

“…The differences in the expression of small RNAs between the two groups were compared. We used machine learning algorithms to analyze small RNAs with significant differences between the two groups, fit the model through training sets, and optimize the model through testing sets. …”
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Deployment of real-time particle detection monitoring system in operating theatres for airborne contamination assessments: a methodological evaluation by Frans Stålfelt, Johan Tenghamn, Henrik Malchau, Karin Svensson Malchau

“…Although the system shows promise for infection prevention and workflow optimization, its direct impact on SSI rates requires validation in larger cohorts. Future research should focus on integrating predictive algorithms and machine-learning to enhance clinical utility and drive improvements in surgical safety. …”
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Machine learning prediction of permeability distribution in the X field Malay Basin using elastic properties by Zaky Ahmad Riyadi, John Oluwadamilola Olutoki, Maman Hermana, Abdul Halim Abdul Latif, Ida Bagus Suananda Yogi, Said Jadid A. Kadir

“…In contrast, XGBoost model performed better (R2 = 0.87, RMSLE = 0.195) using only elastic properties as features. This research highlights a robust method for predicting permeability distribution using elastic properties, which can significantly enhance the efficiency of reservoir assessment. …”
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Construction and performance of a clinical prediction rule for ureteral stone without the use of race or ethnicity: A new STONE score by Christopher L. Moore, Cary P. Gross, Louis Hart, Annette M. Molinaro, Deborah Rhodes, Dinesh Singh, Cristiana Baloescu

“…Future research could investigate the potential contributions of social drivers of health (SDOH) to the diagnosis of kidney stone.…”
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Predictors of pathological complete response after total neoadjuvant treatment using short course radiotherapy for locally advanced rectal cancer by Haythem Yacoub, Yosr Zenzri, Dhouha Cherif, Hajer Ben Mansour, Najla Attia, Cyrine Mokrani, Khadija Ben Zid, Feryel Letaief, Nadia Maamouri, Amel Mezlini

“…Integrating these factors into personalized treatment algorithms may help optimize therapeutic strategies and improve outcomes for patients with LARC.…”
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A Review on Stable Precipitation Type Forecast in Winter by Zhao Linna, Mu Xiuxiang, Ma Cuiping, Wang Xiujuan, Li Dihua

“…The probabilistic prediction has further improved the prediction skills compared with the deterministic model. However, even with such complex algorithms of NWP, correctly predicting what phase of precipitation ends up at the ground remains a challenging task. …”
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Predictive performance of risk prediction models for lung cancer incidence in Western and Asian countries: a systematic review and meta-analysis by Yah Ru Juang, Lina Ang, Wei Jie Seow

“…Machine-learning algorithms were applied in eight Western models and two Asian models. …”
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Prediction of Flexural Ultimate Capacity for Reinforced UHPC Beams Using Ensemble Learning and SHAP Method by Zhe Zhang, Xuemei Zhou, Ping Zhu, Zhaochao Li, Yichuan Wang

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