Peri- and postoperative complications of laparoscopic tubal ligation versus salpingectomy for permanent contraception: An ACS-NSQIP analysis by Vaishnavi J. Patel, Devki Patel, Kimberly Toumazos, Young Son, Komal Sharma, Virgil Kevin DeMario, Shelby Boock, Grace Lara, Alexandra McQuillen, Brianna Clark

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Modeling the determinants of attrition in a two-stage epilepsy prevalence survey in Nairobi using machine learning by Daniel M. Mwanga, Isaac C. Kipchirchir, George O. Muhua, Charles R. Newton, Damazo T. Kadengye, Abankwah Junior, Albert Akpalu, Arjune Sen, Bruno Mmbando, Charles R. Newton, Cynthia Sottie, Dan Bhwana, Daniel Mtai Mwanga, Damazo T. Kadengye, Daniel Nana Yaw, David McDaid, Dorcas Muli, Emmanuel Darkwa, Frederick Murunga Wekesah, Gershim Asiki, Gergana Manolova, Guillaume Pages, Helen Cross, Henrika Kimambo, Isolide S. Massawe, Josemir W. Sander, Mary Bitta, Mercy Atieno, Neerja Chowdhary, Patrick Adjei, Peter O. Otieno, Ryan Wagner, Richard Walker, Sabina Asiamah, Samuel Iddi, Simone Grassi, Sloan Mahone, Sonia Vallentin, Stella Waruingi, Symon Kariuki, Tarun Dua, Thomas Kwasa, Timothy Denison, Tony Godi, Vivian Mushi, William Matuja

“…These findings will inform development of a web-based algorithm to predict attrition risk and aid in targeted follow-up efforts in similar studies.…”
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An introduction to causal discovery by Martin Huber

“…Abstract In social sciences and economics, causal inference traditionally focuses on assessing the impact of predefined treatments (or interventions) on predefined outcomes, such as the effect of education programs on earnings. Causal discovery, in contrast, aims to uncover causal relationships among multiple variables in a data-driven manner, by investigating statistical associations rather than relying on predefined causal structures. …”
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Deep learning for COVID-19 by X-ray images Analysis and Designing Diagnostic Application by Thamer Khaleel, Ali Kalakech

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Perceived worries in the adoption of artificial intelligence among nurses in neonatal intensive care units by Ahmad Ayed, Ahmad Batran, Ibrahim Aqtam, Malakeh Z. Malak, Moath Abu Ejheisheh, Mosaab Farajallah, Lamees Farraj, Sanaa Alkhatib

“…Abstract Introduction Artificial Intelligence (AI) comprises computational algorithms designed to analyze data, learn patterns, and execute tasks traditionally requiring human cognition. …”
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Adaptive FPGA-Based Accelerators for Human–Robot Interaction in Indoor Environments by Mangali Sravanthi, Sravan Kumar Gunturi, Mangali Chinna Chinnaiah, Siew-Kei Lam, G. Divya Vani, Mudasar Basha, Narambhatla Janardhan, Dodde Hari Krishna, Sanjay Dubey

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Trained neural networking framework based skin cancer diagnosis and categorization using grey wolf optimization by Amit Kumar K., Satheesha T.Y., Syed Thouheed Ahmed, Sandeep Kumar Mathivanan, Sangeetha Varadhan, Mohd Asif Shah

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Processing and analysis of images of microstructure metals for determining the grain point by R. P. Bohush, Y. R. Adamousky, S. F. Denisenak

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Quality Assessment of MRI-Radiomics-Based Machine Learning Methods in Classification of Brain Tumors: Systematic Review by Shailesh S. Nayak, Saikiran Pendem, Girish R. Menon, Niranjana Sampathila, Prakashini Koteshwar

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A STUDY OF PEOPLE’S PERCEPTION OF ARTIFICIAL INTELLIGENCE IN FINANCE AND SOCIETY by Dan MITRA, Ioana-Florina COITA

“…This paper investigates how people perceive artificial intelligence (AI), using both original survey data and insights from recent academic and policy literature. …”
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Transforming Chiller Plant Efficiency with SC+BAS: Case Study in a Hong Kong Shopping Mall by Fong Ming-Lun Alan, Li Baonan Nelson

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Recent Advances in Flexible and Wearable Gas Sensors Harnessing the Potential of 2D Materials by Azmira Jannat, Md Mehdi Masud Talukder, Zhong Li, Jian Zhen Ou

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Artificial Intelligence in PR: Transformations of Communication Strategies and Campaigns by Maria Nikolova

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Adherence to Clinical Quidelines on Preoperative Assessment and Correction of Cardiovascular Risk in Non-cardiac Surgery by M. D. Nigmatkulova, E. B. Kleymenova, L. P. Yashina, V. A. Otdelenov, S. A. Payushchik, O. D. Konova, D. A. Sychev

“…The number of inappropriate ECGs and echocardiographies, as well as incorrect treatment with beta-blockers, HMG CoA reductase inhibitors and ACE inhibitors (ARBs) in perioperative period evidence that the adherence of physicians to the clinical guidelines on preoperative assessment and perioperative management of patients remains low.It is reasonably to develop risk-based interdisciplinary protocols for preoperative examination, algorithms for interdisciplinary communication and interaction between specialists and the healthcare levels, as well as physicians' education for better adherence to clinical guidelines.…”
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Urban–rural disparities in fall risk among older Chinese adults: insights from machine learning-based predictive models by LiHan Lin, LiHan Lin, XiaoYang Liu, CaiHua Cai, YiKun Zheng, Delong Li, GuoPeng Hu

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Multilevel determinants of racial/ethnic disparities in severe maternal morbidity and mortality in the context of the COVID-19 pandemic in the USA: protocol for a concurrent triang... by Bankole Olatosi, Jiajia Zhang, Xiaoming Li, Chen Liang, Jihong Liu, Peiyin Hung, Shan Qiao, Berry A Campbell, Myriam E Torres, Neset Hikmet

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Sepsis-Associated Acute Kidney Disease Incidence, Trajectory, and Outcomes by Hsiu-Yin Chiang, Chih-Chia Liang, Ya-Luan Hsiao, Uyen-Minh Le, Yi-Ching Chang, Pei-Shan Chen, David Ray Chang, I-Wen Ting, Hung-Chieh Yeh, Chin-Chi Kuo

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Influence of Aerobic Exercise Load Intensity on Children’s Mental Health by Sihong Zhao

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Coronary Heart Disease Risk Prediction Model Based on Machine Learning by YUE Haitao, HE Chanchan, CHENG Yuyou, ZHANG Sencheng, WU You, MA Jing

“…Conclusion This study not only confirmed known factors affecting CHD but also identified potential impacts of self-assessed health level, income level, and education level on CHD. The performance of the five algorithms was significantly enhanced after employing two data balancing methods. …”
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Cinematic Rendered Computed Tomography Imaging Enhances 3D Visualization of Upper Extremity Arteriovenous Malformation by Balazs C. Lengyel, Alan B. Lumsden, Ponraj Chinnadurai

“…Inspired by the quality of computer-rendered images in the animated movie industry, cinematic rendering (CR) is a novel image visualization technique using proprietary rendering algorithms that simulate the propagation and interaction of light rays passing through 3-dimensional (3D) volumetric data, resulting in a photorealistic representation of bodily organs and vasculature.1,2 Due to its more realistic representative and intuitive format, it has become part of medical education, especially 3D anatomy teaching, patient education, and communication.3,4 It also plays an important role in the diagnostics and treatment planning for complex vascular pathologies, especially malformations.5 This short report highlights the additional diagnostic and clinical value of this image visualization technique by showing its value in treatment planning in a case of arteriovenous malformation (Figure 1).…”
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