Challenges issues and future recommendations of deep learning techniques for SARS-CoV-2 detection utilising X-ray and CT images: a comprehensive review by Md Shofiqul Islam, Fahmid Al Farid, F. M. Javed Mehedi Shamrat, Md Nahidul Islam, Mamunur Rashid, Bifta Sama Bari, Junaidi Abdullah, Muhammad Nazrul Islam, Md Akhtaruzzaman, Muhammad Nomani Kabir, Sarina Mansor, Hezerul Abdul Karim

“…This article provides a meticulous and comprehensive review of imaging-based SARS-CoV-2 diagnosis using deep learning techniques up to May 2024. This article starts with an overview of imaging-based SARS-CoV-2 diagnosis, covering the basic steps of deep learning-based SARS-CoV-2 diagnosis, SARS-CoV-2 data sources, data pre-processing methods, the taxonomy of deep learning techniques, findings, research gaps and performance evaluation. …”
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The role of artificial intelligence in promoting health and developing preventive strategies for diabetes by Ameneh Marzban

“…For example, AI-driven analyses may reveal that regions with higher diabetes prevalence particularly benefit from targeted nutritional education programs, resulting in a 10% decrease in new diabetes cases.6Despite the promising advancements in AI applications within healthcare, it is essential to address ethical considerations and ensure data privacy during implementation. Establishing transparent policies, robust security protocols, and ethical guidelines is vital for safeguarding patient information and fostering trust in AI-driven solutions. …”
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Artificial intelligence and machine learning in acute respiratory distress syndrome management: recent advances by Songbei Li, Songbei Li, Ruiming Yue, Sen Lu, Jingchao Luo, Xiaoxiao Wu, Zhao Zhang, Mingzong Liu, Yuxin Fan, Yuxin Fan, Yuxuan Zhang, Yuxuan Zhang, Chun Pan, Xiaobo Huang, Hongli He

“…We explore diverse AI/ML applications, including early prediction and diagnosis using multi-modal data (electronic health records [EHR], imaging, ventilator waveforms), advanced prognostic assessment and risk stratification that outperform traditional scoring systems, and precise identification of ARDS subtypes to guide personalized treatment. …”
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Standardised and Objective Dietary Intake Assessment Tool (SODIAT): Protocol of a dual-site dietary intervention study to integrate dietary assessment methods [version 2; peer revi... by Katerina Petropoulou, Julie A Lovegrove, John Draper, Manfred Beckmann, Albert Koulman, Amanda J Lloyd, Benny Lo, George Mylonas, Stamatia Giannarou, Juliet Vickar, Adrian R Solis, Frank P.-W. Lo, Rosalind Fallaize, Jennifer Pugh, Isabel Garcia-Perez, Thomas Wilson, Michelle Weech, Eka Bobokhidze, Gary Frost

“…Urine and capillary blood samples were collected for biomarker analysis. Data analysis will assess dietary reporting accuracy across these methods using Lin’s concordance correlation coefficient. …”
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The Ethical Significance of Brain-Computer Interfaces as Enablers of Communication by Toma Gruica

“…For BCIs, this focus materializes in debates over whether to honor euthanasia requests (where legal) communicated through neural implants or concerns about data privacy and cognitive liberty. While these concerns are valid and urgent, they fail to capture the more “fundamental dimension,” which is how BCIs alter the conditions of moral personhood by restoring the capacity to communicate. …”
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A multicenter study of neurofibromatosis type 1 utilizing deep learning for whole body tumor identification by Cheng-Jiang Wei, Yan Tang, Yang-Bai Sun, Tie-Long Yang, Cheng Yan, Hui Liu, Jun Liu, Jing-Ning Huang, Ming-Han Wang, Zhen-Wei Yao, Ji-Long Yang, Zhi-Chao Wang, Qing-Feng Li

“…Previous studies have primarily focused on specific anatomical regions, overlooking tumors occurring throughout the body with highly heterogeneous whole-body backgrounds. Using neurofibromatosis type 1 (NF1) as an example, this study developed highly accurate MRI-based deep-learning models for the early automated screening of malignant peripheral nerve sheath tumors (MPNSTs) against complex whole-body background. …”
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Life-time experience of violence among women and girls living with disability in Nepal. by Padam Simkhada, Sapana Basnet, Shaurabh Sharma, Edwin van Teijlingen, Sharada Prasad Wasti, Tikadevi Dahal, Joshua Okyere, Ram Chandra Silwal, Manita Pyakurel

“…This was done by trained enumerators using the KoBo application on smartphones or tablets. …”
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GPU Acceleration for FHEW/TFHE Bootstrapping by Yu Xiao, Feng-Hao Liu, Yu-Te Ku, Ming-Chien Ho, Chih-Fan Hsu, Ming-Ching Chang, Shih-Hao Hung, Wei-Chao Chen

“… Fully Homomorphic Encryption (FHE) allows computations to be performed directly on encrypted data without decryption. Despite its great theoretical potential, the computational overhead remains a major obstacle for practical applications. …”
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Role of AI in empowering and redefining the oncology care landscape: perspective from a developing nation by Isha Goel, Isha Goel, Yogendra Bhaskar, Nand Kumar, Sunil Singh, Mohammed Amanullah, Ruby Dhar, Subhradip Karmakar

“…However, it is essential to ensure responsible implementation and address potential ethical and privacy concerns associated with using AI in healthcare.…”
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Patients’ Perspectives on Social Barriers to Care and the Acceptability and Impact of a Community Health Worker Program in Outpatient Ophthalmology by Rustam Z, Amezcua Moreno J, Tran D, Ferguson K, Woods R, Cai CX

“…The transcripts were analyzed using traditional text analysis based on classic grounded theory to identify themes.Results: Patients reported transportation (66%), scheduling conflicts (50%), forgetting appointments (50%) and other illnesses (40%) as barriers to attending eye appointments. …”
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Acceptability, feasibility and appropriateness of integrating HPV self-sampling for cervical cancer screening into voluntary family planning services in Malawi by Patani Mhango, Andrew Kumitawa, Monica Patricia Malata, Jennifer H. Tang, Effie Chipeta, Bianca Kandeya, Medrina Mtende, Princess Kaira, Razak Mussa, Wanangwa Chimwaza, Lameck Chinula, Ireen Magongwa, Jacqueline Mbendera, Eneli Mhango, Eunice Mwandira, Lizzie Msowoya, Jennifer S. Smith, Mitch Matoga, Agatha Bula, Luis Gadama, Victor Mwapasa

“…The quantitative survey data were analyzed using the Fisher exact test to test for association in Stata Version 16. …”
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Artificial intelligence conversational agents in mental health: Patients see potential, but prefer humans in the loop by Hyein S. Lee, Hyein S. Lee, Colton Wright, Julia Ferranto, Jessica Buttimer, Clare E. Palmer, Andrew Welchman, Kathleen M. Mazor, Kimberly A. Fisher, David Smelson, Laurel O’Connor, Laurel O’Connor, Nisha Fahey, Nisha Fahey, Apurv Soni, Apurv Soni, Apurv Soni

“…Anxiety levels were assessed using the Generalized Anxiety Disorder scale. Data were collected from December 2022 to February 2023, and three researchers conducted rapid qualitative analysis to identify and synthesize themes.ResultsThe sample included 29 adults (ages 19-66), predominantly under age 35, non-Hispanic, White, and female. …”
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Enhancing Access to Mental Health Services for Antepartum and Postpartum Women Through Telemental Health Services at Wellbeing Centers in Selected Health Facilities in Bangladesh:... by Aniqa Tasnim Hossain, Md Hafizur Rahman, Ridwana Maher Manna, Ema Akter, SM Hasibul Islam, Md Alamgir Hossain, Tasnu Ara, Nasimul Ghani Usmani, Pradip Chandra, Maruf Ahmed Khan, SM Mustafizur Rahman, Helal Uddin Ahmed, Muhammad Kamruzzaman Mozumder, Jesmin Mahmuda Juthi, Fatema Shahrin, Sadia Afrose Shams, Fahmida Afroze, Mukta Jahan Banu, Shafiqul Ameen, Sabrina Jabeen, Anisuddin Ahmed, Mohammad Robed Amin, Shams El Arifeen, Mohammad Sohel Shomik, Ahmed Ehsanur Rahman

“…The Wellbeing Centers’ services were appreciated for their privacy and being free and accessible. However, stigma, postpartum illness, and long waiting times prevented some women from using these services. …”
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Cervical ripening at home or in hospital during induction of labour: the CHOICE prospective cohort study, process evaluation and economic analysis by Mairead Black, Cassandra Yuill, Mairi Harkness, Sayem Ahmed, Linda Williams, Kathleen A Boyd, Maggie Reid, Amar Bhide, Neelam Heera, Jane Huddleston, Neena Modi, John Norrie, Dharmintra Pasupathy, Julia Sanders, Gordon C S Smith, Rosemary Townsend, Helen Cheyne, Christine McCourt, Sarah Stock

“…Deidentified data on all eligible women having IOL was extracted from the BadgerNet system using existing data fields. …”
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Impact of the universal seasonal influenza vaccination policy on seasonal influenza vaccine uptake in Manitoba, Canada: a population-based interrupted time series analysis by Dr George Okoli, Dr Christiaan Righolt, Mr Geng Zhang, Dr Paul Van Caeseele, Dr I fan Kuo, Dr Silvia Alessi-Severini, Dr Salahhedin Mahmud

“…Methods: We conducted an ecological study utilizing anonymized population-wide electronic data from several centralized Manitoba Health (MH) administrative databases linked using a scrambled (encrypted) version of the unique personal health identification number (PHIN) in Manitoba as a key. …”
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Artificial Intelligence-Assisted Clinical Decision-Making: A Perspective on Advancing Personalized Precision Medicine for Elderly Diabetes Patients by Hu J, Ren L, Wang T, Yao P

“…Nonetheless, several challenges persist, including issues related to data standardization, algorithm transparency, and patient privacy protection. …”
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Awareness and Perception of Hepatitis C Self-Testing in Nigeria: A National Survey of Stakeholders and the Public by Victor Abiola Adepoju, Donald Chinazor Udah, Chinonye Alioha Ezenwa, Jamiu Ganiyu, Qorinah Estiningtyas Sakilah Adnani

“…<b>Methods:</b> A cross-sectional descriptive study was conducted using an online social media survey administered through SurveyMonkey. …”
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Integrative review of artificial intelligence applications in nursing: education, clinical practice, workload management, and professional perceptions by Rabie Adel El Arab, Omayma Abdulaziz Al Moosa, Mette Sagbakken, Ahmed Ghannam, Fuad H. Abuadas, Joel Somerville, Joel Somerville, Abbas Al Mutair, Abbas Al Mutair, Abbas Al Mutair, Abbas Al Mutair, Abbas Al Mutair

“…These efficiencies allowed nursing teams to devote more time to direct patient care and were associated with reductions in burnout and improved workplace morale.Nursing perceptionsAcross practice settings, nursing students and practicing nurses broadly welcomed AI’s ability to streamline workflows and support decision-making, recognizing its potential to elevate patient care and professional practice.Ethical implicationsSimultaneously, nurses voiced significant ethical concerns—chiefly around safeguarding patient data privacy, mitigating algorithmic bias, and preserving the compassionate, human-centered essence of nursing in an increasingly automated environment.Framework and recommendationsThe Nursing AI Integration Roadmap (NAIIR) was developed, emphasizing transformational education, advanced clinical integration, ethical governance, robust organizational infrastructure, participatory design, and rigorous economic evaluation. …”
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Artificial intelligence in nursing: an integrative review of clinical and operational impacts by Salwa Hassanein, Salwa Hassanein, Rabie Adel El Arab, Rabie Adel El Arab, Amany Abdrbo, Mohammad S. Abu-Mahfouz, Mastoura Khames Farag Gaballah, Mohamed Mahmoud Seweid, Mohamed Mahmoud Seweid, Mohammed Almari, Husam Alzghoul

“…However, despite these benefits, ethical challenges remain prominent. Key concerns include data privacy risks, algorithmic bias, and the potential erosion of clinical judgment due to overreliance on technology. …”
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Staff-reported barriers and facilitators to the implementation of healthcare interventions within regional and rural areas: a rapid review by Anna Chapman, Alison Buccheri, Devdini Mohotti, Anna Wong Shee, Catherine E. Huggins, Laura Alston, Alison M. Hutchinson, Sze Lin Yoong, Hannah Beks, Kevin Mc Namara, Anna Peeters, Anna Ugalde

“…Methods A systematic search for peer-reviewed publications was conducted using CINAHL, PsycINFO, Medline, and Embase databases (1/1/2000–29/08/2023). …”
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