The role of artificial neural network and machine learning in utilizing spatial information

A Goel, AK Goel, A Kumar - Spatial Information Research, 2023 - Springer
In this age of the fourth industrial revolution 4.0, the digital world has a plethora of data,
including the internet of things, mobile, cybersecurity, social media, forecasts, health data …

Artificial intelligence in medicine: A comprehensive survey of medical doctor's perspectives in Portugal

AR Pedro, MB Dias, L Laranjo, AS Cunha, JV Cordeiro - Plos one, 2023 - journals.plos.org
Artificial Intelligence (AI) is increasingly influential across various sectors, including
healthcare, with the potential to revolutionize clinical practice. However, risks associated …

[HTML][HTML] Machine learning in orthopaedic surgery

SP Lalehzarian, AK Gowd, JN Liu - World journal of orthopedics, 2021 - ncbi.nlm.nih.gov
Artificial intelligence and machine learning in orthopaedic surgery has gained mass interest
over the last decade or so. In prior studies, researchers have demonstrated that machine …

[HTML][HTML] Managing disruptive technologies for innovative healthcare solutions: the role of high-involvement work systems and technologically-mediated relational …

A Malik, S Kumar, S Basu, R Bebenroth - Journal of Business Research, 2023 - Elsevier
In this research, we present a model of innovative healthcare solutions as an interactive
outcome of high-involvement work systems and technologically-mediated relational …

[HTML][HTML] Teaching AI ethics in medical education: a sco** review of current literature and practices

L Weidener, M Fischer - Perspectives on medical education, 2023 - ncbi.nlm.nih.gov
Methods: The PRISMA-SCR guidelines and JBI methodology guided a literature search in
four databases (PubMed, Embase, Scopus, and Web of Science) for the past 22 years (2000 …

The enlightening role of explainable artificial intelligence in chronic wound classification

S Sarp, M Kuzlu, E Wilson, U Cali, O Guler - Electronics, 2021 - mdpi.com
Artificial Intelligence (AI) has been among the most emerging research and industrial
application fields, especially in the healthcare domain, but operated as a black-box model …

[HTML][HTML] Explainable discovery of disease biomarkers: The case of ovarian cancer to illustrate the best practice in machine learning and Shapley analysis

W Huang, H Suominen, T Liu, G Rice… - Journal of Biomedical …, 2023 - Elsevier
Objective: Ovarian cancer is a significant health issue with lasting impacts on the community.
Despite recent advances in surgical, chemotherapeutic and radiotherapeutic interventions …

Effects of artificial intelligence implementation on efficiency in medical imaging—a systematic literature review and meta-analysis

K Wenderott, J Krups, F Zaruchas, M Weigl - NPJ Digital Medicine, 2024 - nature.com
In healthcare, integration of artificial intelligence (AI) holds strong promise for facilitating
clinicians' work, especially in clinical imaging. We aimed to assess the impact of AI …

Dynamic coati optimization algorithm for biomedical classification tasks

EH Houssein, NA Samee, NF Mahmoud… - Computers in Biology …, 2023 - Elsevier
Medical datasets are primarily made up of numerous pointless and redundant elements in a
collection of patient records. None of these characteristics are necessary for a medical …

A justifiable investment in AI for healthcare: aligning ambition with reality

K Karpathakis, J Morley, L Floridi - Minds and Machines, 2024 - Springer
Healthcare systems are grappling with critical challenges, including chronic diseases in
aging populations, unprecedented health care staffing shortages and turnover, scarce …