Artificial Intelligence in Epidemiology and Medical Sciences

A special issue of Epidemiologia (ISSN 2673-3986).

Deadline for manuscript submissions: 31 December 2024 | Viewed by 1136

Special Issue Editors


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Guest Editor
Italian Society of Environmental Medicine, Viale di Porta Vercellina 23, 20124 Milan, Italy
Interests: epidemiology; environmental health; preventive medicine

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Guest Editor Assistant
Law Faculty, University of Salerno, Fisciano, Italy
Interests: data protection law

Special Issue Information

Dear Colleagues, 

The new frontiers of artificial intelligence (AI) have generated interesting perspectives on observational and experimental epidemiology, as AI can be widely used, along with machine learning techniques, for a wide range of applications in both the diagnosis and treatment of several diseases. For this Special Issue, we request papers discussing AI use in all fields of medicine and surgery, such as AI applications in radiology for the diagnosis of any pathological condition, as well as AI use to support surgery and endoscopy and in the study of retina, brain, liver, heart, kidney and other organs’ function. Studies analyzing big data or exploring AI applications in any field of epidemiology, including population studies, models of the spread of infectious diseases, and medical science are welcome. We also encourage the submission of articles on the analysis of hospital or insurance administrative databases and those addressing the issue of personal data protection within the framework of AI’s application to medical records. 

Prof. Dr. Prisco Piscitelli
Prof. Dr. Alessandro Miani
Guest Editors

Prof. Dr. Pasquale Stanzione
Guest Editor Assistant

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Epidemiologia is an international peer-reviewed open access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • artificial intelligence
  • epidemiology
  • diagnosis
  • treatment
  • population
  • surveillance
  • infectious disease spread

Published Papers (1 paper)

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Research

8 pages, 212 KiB  
Communication
AI-Enhanced Tools and Strategies for Airborne Disease Prevention in Cultural Heritage Sites
by Enrico Greco, Anastasia Serena Gaetano, Alessia De Spirt, Sabrina Semeraro, Prisco Piscitelli, Alessandro Miani, Saverio Mecca, Stela Karaj, Rita Trombin, Rachel Hodgton and Pierluigi Barbieri
Epidemiologia 2024, 5(2), 267-274; https://doi.org/10.3390/epidemiologia5020018 - 6 Jun 2024
Viewed by 952
Abstract
In the wake of the COVID-19 pandemic, the surveillance and safety measures of indoor Cultural Heritage sites have become a paramount concern due to the unique challenges posed by their enclosed environments and high visitor volumes. This communication explores the integration of Artificial [...] Read more.
In the wake of the COVID-19 pandemic, the surveillance and safety measures of indoor Cultural Heritage sites have become a paramount concern due to the unique challenges posed by their enclosed environments and high visitor volumes. This communication explores the integration of Artificial Intelligence (AI) in enhancing epidemiological surveillance and health safety protocols in these culturally significant spaces. AI technologies, including machine learning algorithms and Internet of Things (IoT) sensors, have shown promising potential in monitoring air quality, detecting pathogens, and managing crowd dynamics to mitigate the spread of infectious diseases. We review various applications of AI that have been employed to address both direct health risks and indirect impacts such as visitor experience and preservation practices. Additionally, this paper discusses the challenges and limitations of AI deployment, such as ethical considerations, privacy issues, and financial constraints. By harnessing AI, Cultural Heritage sites can not only improve their resilience against future pandemics but also ensure the safety and well-being of visitors and staff, thus preserving these treasured sites for future generations. This exploration into AI’s role in post-COVID surveillance at Cultural Heritage sites opens new frontiers in combining technology with traditional conservation and public health efforts, providing a blueprint for enhanced safety and operational efficiency in response to global health challenges. Full article
(This article belongs to the Special Issue Artificial Intelligence in Epidemiology and Medical Sciences)
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