[HTML][HTML] Methodological and quality flaws in the use of artificial intelligence in mental health research: systematic review

R Tornero-Costa, A Martinez-Millana… - JMIR Mental …, 2023 - mental.jmir.org
Background: Artificial intelligence (AI) is giving rise to a revolution in medicine and health
care. Mental health conditions are highly prevalent in many countries, and the COVID-19 …

Systematic review of current natural language processing methods and applications in cardiology

MR Turchioe, A Volodarskiy, J Pathak, DN Wright… - Heart, 2022 - heart.bmj.com
Natural language processing (NLP) is a set of automated methods to organise and evaluate
the information contained in unstructured clinical notes, which are a rich source of real-world …

[HTML][HTML] Artificial intelligence and its impact on the domains of universal health coverage, health emergencies and health promotion: An overview of systematic reviews

A Martinez-Millana, A Saez-Saez… - International Journal of …, 2022 - Elsevier
Background Artificial intelligence is fueling a new revolution in medicine and in the
healthcare sector. Despite the growing evidence on the benefits of artificial intelligence there …

[HTML][HTML] Understanding basic principles of artificial intelligence: a practical guide for intensivists

V Bellini, M Cascella, F Cutugno, M Russo… - Acta Bio Medica …, 2022 - ncbi.nlm.nih.gov
Conclusions: High-performance characteristics and strict quality controls are needed during
its progress. During this process, different measures can be identified (pre-processing …

Current status and challenges in establishing reference intervals based on real-world data

S Ma, J Yu, X Qin, J Liu - Critical Reviews in Clinical Laboratory …, 2023 - Taylor & Francis
Reference intervals (RIs) are the cornerstone for evaluation of test results in clinical practice
and are invaluable in judging patient health and making clinical decisions. Establishing RIs …

[HTML][HTML] Digital transformation in healthcare 4.0: critical factors for business intelligence systems

F Kitsios, N Kapetaneas - Information, 2022 - mdpi.com
The health sector is one of the most knowledge-intensive and complicated globally. It has
been proven repeatedly that Business Intelligence (BI) systems in the healthcare industry …

[HTML][HTML] Towards a New Paradigm for Digital Health Training and Education in Australia: Exploring the Implication of the Fifth Industrial Revolution

TY Pang, TK Lee, M Murshed - Applied Sciences, 2023 - mdpi.com
Featured Application This paper presents a new, fifth industrial revolution (Industry 5.0)-
inspired paradigm for educating and training Australian healthcare professionals and …

[HTML][HTML] Real world—big data analytics in healthcare

D Piovani, S Bonovas - … journal of environmental research and public …, 2022 - mdpi.com
The term Big Data is used to describe extremely large datasets that are complex,
multidimensional, unstructured, and heterogeneous and that are accumulating rapidly and …

[HTML][HTML] A Review of Big Data Trends and Challenges in Healthcare

L Baloch, SU Bazai, S Marjan, F Aftab… - International Journal …, 2023 - ijtech.eng.ui.ac.id
The healthcare sector produces an enormous amount of complicated data from several
sources, such as health monitoring systems, medical devices, and electronic health records …

Data Analytics and Techniques

SS Abdul-Jabbar - ARO-The Scientific Journal of Koya …, 2022 - aro.koyauniversity.org
Big data of different types, such as texts and images, are rapidly generated from the internet
and other applications. Dealing with this data using traditional methods is not practical since …