Computational methods and artificial intelligence-based modeling of magnesium alloys: a systematic review of machine learning, deep learning, and data-driven design and optimizatio... by Hanxuan Wang, Raman Kumar, Raman Kumar, Ashutosh Pattanaik, Rajender Kumar, Rajender Kumar, Ali Saeed Owayez Khawaf Aljaberi, Mayada Ahmed Abass

“…The review highlights the extensive application of models, including Artificial Neural Networks, Convolutional Neural Networks, and hybrid frameworks that combine ML with optimization algorithms or physical simulations. These approaches enhance predictions on mechanical properties, microstructural changes, corrosion behavior, and processing results of Mg alloys. …”
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Teens and opioids postsurgery (TOPS): protocol for a prospective observational study describing associations between sleep deficiency and opioid use following outpatient surgery in... by Tonya Palermo, Jennifer A Rabbitts, Cornelius B Groenewald, Rebecca L Flack, Sophia L Kreider

“…We will apply modern machine learning algorithms to develop and validate models predicting adolescent prescription opioid misuse at 24 months from surgery.Ethics and dissemination This study was approved by Advarra’s Center for Institutional Review Board Intelligence (CIRBI) (Protocol 00072049), which serves as the single IRB of record for this multisite study.…”
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C2 pars interarticularis length on the side of high-riding vertebral artery with implications for pars screw insertion by Tomasz Klepinowski, Miszela Kałachurska, Michał Chylewski, Natalia Żyłka, Dominik Taterra, Kajetan Łątka, Bartłomiej Pala, Wojciech Poncyljusz, Leszek Sagan

“…We aimed to measure C2PIL specifically on the sides with HRVA, define short pars, optimal pars screw length, and incorporate C2PIL into HRVA clusters using machine learning algorithms. A clinical anatomical study based on cervical CT was conducted with STROBE-compliant case–control design. …”
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Propagating observation errors to enable scalable and rigorous enumeration of plant population abundance with aerial imagery by Andrii Zaiats, T. Trevor Caughlin, Jennyffer Cruz, David S. Pilliod, Megan E. Cattau, Rongsong Liu, Richard Rachman, Maisha Maliha, Donna Delparte, John D. J. Clare

“…Integrating >16 ha of UAS imagery with >700 georeferenced field plots, we fit our model to generate insights into the prevalence and drivers of observation errors associated with classification algorithms used to distinguish individual plants, relationships between abundance and landscape context, and to generate spatially explicit maps of shrub abundance. …”
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Feasibility of Implementing Motion-Compensated Magnetic Resonance Imaging Reconstruction on Graphics Processing Units Using Compute Unified Device Architecture by Mohamed Aziz Zeroual, Natalia Dudysheva, Vincent Gras, Franck Mauconduit, Karyna Isaieva, Pierre-André Vuissoz, Freddy Odille

“…Motion correction in magnetic resonance imaging (MRI) has become increasingly complex due to the high computational demands of iterative reconstruction algorithms and the heterogeneity of emerging computing platforms. …”
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School-Based Online Surveillance of Youth: Systematic Search and Content Analysis of Surveillance Company Websites by Alison O'Daffer, Wendy Liu, Cinnamon S Bloss

“…Findings suggest that students who only have school-provided devices are more heavily surveilled and that historically marginalized students may be at a higher risk of being flagged due to algorithmic bias. The dearth of research on efficacy and the notable lack of transparency about how surveillance services work indicate that increased oversight by policy makers of this industry may be warranted. …”
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Prediction of lymph node metastasis in papillary thyroid carcinoma using non-contrast CT-based radiomics and deep learning with thyroid lobe segmentation: A dual-center study by Hao Wang, Xuan Wang, Yusheng Du, You Wang, Zhuojie Bai, Di Wu, Wuliang Tang, Hanling Zeng, Jing Tao, Jian He

“…Deep learning and radiomics features were selected using LASSO algorithms to compute DLRad scores. Logistic regression identified independent predictors, forming DLRad, clinical, and combined models. …”
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Socioeconomic status and lifestyle as factors of multimorbidity among older adults in China: results from the China Health and Retirement Longitudinal Survey by Wei Gong, Wei Gong, Wei Gong, Xiaoxiao Hu, Huimin Cui, Huimin Cui, Yuxin Zhao, Yuxin Zhao, Hong Lin, Hong Lin, Hong Lin, Peng Sun, Peng Sun, Jianjun Yang, Jianjun Yang

“…Eight machine learning algorithms including logistic regression, decision tree, naive Bayes, neural network, support vector machine, random forest, XGBoost and Bayesian Ridge Regression were applied to build predictive models. …”
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Fuzzy logic-controlled three-phase dynamic voltage restorer for enhancing voltage stabilization and power quality by Abu Shufian, Sowrov Komar Shib, Durjoy Roy Dipto, Md Tanvir Rahman, Nasif Hannan, Shaikh Anowarul Fattah

“…Unlike conventional algorithms, which struggle under fluctuating grid conditions and complex disturbances, FLC dynamically adjusts the output of DVR based on real-time reference and load voltage measurements. …”
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A review of altimetry waveform retracking for inland water levels by Xinyuan Deng, Linghong Ke, Liguang Jiang, Karina Nielsen, Xiaomei Fan, Jida Wang, Chunqiao Song

“…By synthesizing pioneering studies on “retracking algorithms”, this review demonstrates, from a user perspective, why optimizing conventional retracking is still important and how it can extend reliable historical water level retrieval over more ungauged sites. …”
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In-depth insight into structure-reactivity/regioselectivity relationship of Lewis acid catalyzed cascade 4πe-cyclization/dicycloexpansion reaction by Ka Lu, Pan-Pan Zhou, Yong-Qiang Tu, Fu-Min Zhang, Xiao-Ming Zhang, Kai Li, Kun Fang, Yun-Peng Wang, Zi-Hao Li, Jia-Qi Li

“…Then, DFT calculations combined with machine learning algorithms establish a prediction model for first cycloexpansion (i e. regioselectivity). …”
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Pubertal hypothalamic dysfunction: epidemiology, risk factors, features of the clinical course and consequences of pathology in adults by I.S. Lembryk, I.O. Kostitska, O.V. Zhyliak, E.A. Saretsian, D.O. Kulynych, S.A. Shelever, Yu.T. Khruniak

“…A personalized approach to the early diagnosis and management of patients with hypothalamic dysfunction allows to improve therapeutic algorithms and increase the effectiveness of treatment of comorbid pathology in young patients.…”
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A machine learning model for predicting anatomical response to Anti-VEGF therapy in diabetic macular edema by Wenrui Lu, Kunhong Xiao, Xuemei Zhang, Yuqing Wang, Wenbin Chen, Xierong Wang, Yunxi Ye, Yan Lou, Li Li

“…Five machine learning algorithms—logistic regression, decision tree, multilayer perceptron, random forest, and support vector machine—were trained and validated. …”
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The prognostic and therapeutic significance of polyunsaturated fatty acid‐derived oxylipins in ST‐segment elevation myocardial infarction by Zhiyong Du, Yingyuan Lu, Ying Ma, Yunxiao Yang, Wei Luo, Sheng Liu, Ming Zhang, Yong Wang, Lei Li, Chun Li, Wei Wang, Hai Gao

“…Herein, we used targeted metabolomics and machine learning algorithms to develop an oxylipin‐based risk model to accurately predict recurrent major adverse cardiovascular events (MACE) after STEMI in two independent prospective cohorts with 2 years of follow‐up. …”
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Fc-Binding Cyclopeptide Induces Allostery from Fc to Fab: Revealed Through in Silico Structural Analysis to Anti-Phenobarbital Antibody by Tao Zhou, Huiling Zhang, Xiaoting Yu, Kangliang Pan, Xiaojun Yao, Xing Shen, Hongtao Lei

“…The combination of molecular docking and multiple allosteric site prediction algorithms in these methods identified that the cyclopeptide binds to the interface of heavy chain region-1 (CH₁) in antibody Fab and heavy chain region-2 (CH₂) in antibody Fc. …”
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Nursing Educators’ Perspectives on the Integration of Artificial Intelligence Into Academic Settings by Moustaq Karim Khan Rony MSS, MPH, RN, Sumon Ahmad MPH, RN, Sabren Mukta Tanha MPH, RN, Dipak Chandra Das MSS, Mosammat Ruma Akter MSN, RN, Mst. Amena Khatun MPH, RN, Most. Hasina Begum MSN, RN, Md Ibrahim Khalil MSS, RN, Umme Rabeya Peu MSS, RN, Mst. Rina Parvin BSN, RN, Daifallah M Alrazeeni PhD, Fazila Akter MSc, RN

“…However, barriers such as insufficient training, infrastructural challenges, and ethical concerns related to data privacy, algorithmic bias, and AI-driven decision making were highlighted. …”
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Disease progression & treatment need in sub-genotype C4 hepatitis B infection: a retrospective cohort study in the Northern Territory, Australia by Genevieve E. Martin, Kelly Hosking, Kelly Banz, Catherine Gargan, Geoff Stewart, Belinda Greenwood-Smith, Penelope Ramsay, Jaclyn Tate-Baker, Christine Connors, Paula Binks, Melita McKinnon, Prashanti Manchikanti, George Garambaka Gurruwiwi, Nicole Allard, Ashleigh Qama, Jessica Michaels, Emily Vintour-Cesar, Robert Batey, Catherine Marshall, Peter Nihill, Tammy-Allyn Fernandes, Karen Fuller, Steven Y. C. Tong, David Boettiger, Benjamin Cowie, Joshua S. Davis, Sarah Mariyalawuy Bukulatjpi, Jane Davies, on behalf of the Hep B PAST Partnership

“…Disease phase and cirrhotic status were determined algorithmically using clinical and laboratory data at two time points. …”
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A Nomogram for Predicting Recurrence in Stage I Non‐Small Cell Lung Cancer by Rongrong Bian, Feng Zhao, Bo Peng, Jin Zhang, Qixing Mao, Lin Wang, Qiang Chen

“…In the discovery phase, two algorithms, least absolute shrinkage and selector operation and support vector machine‐recursive feature elimination, were used to identify candidate genes. …”
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Parsimonious and explainable machine learning for predicting mortality in patients post hip fracture surgery by Fouad Trad, Bassel Isber, Ryan Yammine, Khaled Hatoum, Dana Obeid, Mohammad Chahine, Rachid Haidar, Ghada El-Hajj Fuleihan, Ali Chehab

“…In this study, we developed machine learning (ML) algorithms to estimate 30-day mortality risk post-hip fracture surgery in the elderly using data from the National Surgical Quality Improvement Program (NSQIP 2012–2017, n = 62,492 patients). …”
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Machine-Learning Parsimonious Prediction Model for Diagnostic Screening of Severe Hematological Adverse Events in Cancer Patients Treated with PD-1/PD-L1 Inhibitors: Retrospective... by Seok Jun Park, Seungwon Yang, Suhyun Lee, Sung Hwan Joo, Taemin Park, Dong Hyun Kim, Hyeonji Kim, Soyun Park, Jung-Tae Kim, Won Gun Kwack, Sung Wook Kang, Yun-Kyoung Song, Jae Myung Cha, Sang Youl Rhee, Eun Kyoung Chung

“…Among the tested ML algorithms, random forest achieved the highest accuracy (area under the receiver operating characteristic curve [AUROC] 0.88 for both cohorts). …”
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