Events MOL2NET'23, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 9th ed.

Event submissions

Published

10.3390/mol2net-09-14286 (registering DOI)

This submission belongs to the session 05. USEDAT.NET: USA-Europe Data Analysis Trends & Complex Networks Mini Congress Series, Coruña, SP-Miami, USA, 2023 of the event MOL2NET'23, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 9th ed.

Published date

27 Mar, 2023

Academic Editor

Humbert G. Díaz

Citation

Andrea Ruiz Escudero, Artificial Intelligence in Medical Diagnosis, in Proceedings of MOL2NET'23, Conference on Molecular, Biomed., Comput. & Network Science and Engineering, 9th ed., 25 December–31 December 2023, MDPI: Basel, Switzerland, doi: 10.3390/mol2net-09-14286

Facebook

Twitter

Artificial Intelligence in Medical Diagnosis

Andrea Ruiz Escudero ^1,2

1. Department of Pharmacology, Faculty of Medicine and Nursing, University of the Basque Country (UPV/EHU), Leioa, Biscay, Spain.

2. Department of Information and Communication Technologies, Computer Science Faculty, University of A Coruña,Campus de Elviña, A Coruña, Spain.

Abstract

Artificial intelligence (AI) has the potential to revolutionize the domain of medicine, particularly in the realm of medical diagnosis. AI-based diagnostic tools have the ability to analyze large amounts of data and undercover complex patterns that may be hard for humans to detect. Also, it helps to assist healthcare providers to make more precise and prompt diagnoses. This review explores the role of AI in improving medical diagnoses, the limitations associated with this technology, and relevant examples.

Keywords

Artificial intelligence

deep learning

medicine

diagnostic

AI limitations

healthcare

Manuscript

Artificial Intelligence in Medical Diagnosis.pdf

Marijuana: an in-depth look at its use, cause, and effects in medical applications.

Variances in the Expression of mRNAs Related to the Histaminergic System in Endometrioid Endometrial Cancer