Journal Article10.1016/j.smhl.2022.100279
Emerging point of care devices and artificial intelligence: Prospects and challenges for public health
Andrew Stranieri,Sitalakshmi Venkatraman,John Minicz,A. Zarnegar,Sally Firmin,V. Balasubramanian,Herbert F. Jelinek +6 more
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TL;DR: In this paper , a case study of a diabetes screening clinic in a rural area of Australia is presented to illustrate its benefits, showing that universal, poly-aetiological screening is shown to meet the ten World Health Organisation criteria for screening programmes.
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About: This article is published in Smart Health. The article was published on 01 Mar 2022. The article focuses on the topics: Public health.
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Citations
Integrating artificial intelligence and big data in mobile health: a systematic review of innovations and challenges in healthcare systems
04 Jan 2024
TL;DR: Integration of AI and Big Data in mHealth significantly enhances diagnostic precision, personalizes treatment strategies, and streamlines healthcare operations. However, challenges such as ethical dilemmas, data privacy and security issues, and the need for human oversight must be carefully addressed to harness the full potential of this transformative technology.
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AI-Assisted Detection of Biomarkers by Sensors and Biosensors for Early Diagnosis and Monitoring
Tomasz Wasilewski,Wojciech Kamysz,Jacek Gębicki +2 more
TL;DR: This article focuses on a comparison of traditional clinical practices with modern diagnostic techniques based on AI and machine learning (ML), which will bypass laboratories and start being commercialized, which should lead to improvement or substitution of current diagnostic tools.
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Contemporary Role and Applications of Artificial Intelligence in Dentistry
T. Bonny,Wafaa Al Nassan,Khaled Obaideen,Maryam Nooman Al Mallahi,Yara Mohammad,Hatem M. El-damanhoury +5 more
TL;DR: The purpose of this paper is to identify the advancement of artificial intelligence algorithms that have been frequently used in dentistry and assess how well they perform in terms of diagnosis, clinical decision-making, treatment, and prognosis prediction in ten dental specialties.
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Modeling Conceptual Framework for Implementing Barriers of AI in Public Healthcare for Improving Operational Excellence: Experiences from Developing Countries
Sudhanshu Joshi,Manu Sharma,Rashmi Das,Joanna Rosak-Szyrocka,Justyna Zywiolek,Kamalakanta Muduli,Mukesh Prasad +6 more
TL;DR: This study aims to determine the crucial AI implementation barriers in public healthcare from the viewpoint of the society, the economy, and the infrastructure and used MCDM techniques to structure the multiple-level analysis of the AI implementation.
Label-Free DNA Biosensor Based on Reduced Graphene Oxide and Gold Nanoparticles
TL;DR: A label-free DNA biosensor is developed using reduced graphene oxide and gold nanoparticles at screen-printed carbon electrodes, enhancing surface conductivity and sensitivity for DNA detection through electrochemical signal changes.
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References
Developments, application, and performance of artificial intelligence in dentistry - A systematic review.
Sanjeev Khanagar,Sanjeev Khanagar,Ali Al-Ehaideb,Ali Al-Ehaideb,Ali Al-Ehaideb,Prabhadevi C Maganur,Satish Vishwanathaiah,Shankargouda Patil,Hosam Ali Baeshen,Sachin C Sarode,Shilpa Bhandi +10 more
TL;DR: These studies indicate that the performance of an AI based automated system is excellent and mimic the precision and accuracy of trained specialists, in some studies it was found that these systems were even able to outmatch dental specialists in terms of performance and accuracy.
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AUSDRISK: an Australian Type 2 Diabetes Risk Assessment Tool based on demographic, lifestyle and simple anthropometric measures.
Lei Chen,Dianna J. Magliano,Beverley Balkau,Beverley Balkau,Stephen Colagiuri,Paul Zimmet,Andrew Tonkin,Paul Mitchell,Patrick P. J. Phillips,Jonathan E. Shaw +9 more
TL;DR: The objective is to develop and validate a diabetes risk assessment tool for Australia based on demographic, lifestyle and simple anthropometric measures.
Value Co-Creation through Patient Engagement in Health Care: A micro-level approach and research agenda
TL;DR: Drawing on emerging ideas in the services marketing and public management literatures, this article offers the first elucidation of the importance of studying ‘value co-creation’ as a basis for further empirical analysis of patient engagement in micro-level encounters.
Early detection of type 2 diabetes mellitus using machine learning-based prediction models.
TL;DR: This study compares machine learning-based prediction models to commonly used regression models for prediction of undiagnosed T2DM and shows no clinically relevant improvement when more sophisticated prediction models were used.
IoMT amid COVID-19 pandemic: Application, architecture, technology, and security
Azana Hafizah Mohd Aman,Wan Haslina Hassan,Shilan Sameen,Shilan Sameen,Zainab Senan Attarbashi,Mojtaba Alizadeh,Liza Abdul Latiff +6 more
TL;DR: In many countries, the Internet of Medical Things has been deployed in tandem with other strategies to curb the spread of COVID-19, improve the safety of front-line personnel, increase efficacy by lessening the severity of the disease on human lives, and decrease mortality rates.
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