Clinical Applications of Artificial Intelligence-An Updated Overview

Artificial intelligence has the potential to revolutionize modern society in all its aspects. Encouraged by the variety and vast amount of data that can be gathered from patients (e.g., medical images, text, and electronic health records), researchers have recently increased their interest in develo...

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Published inJournal of clinical medicine Vol. 11; no. 8; p. 2265
Main Authors Busnatu, Ștefan, Niculescu, Adelina-Gabriela, Bolocan, Alexandra, Petrescu, George E D, Păduraru, Dan Nicolae, Năstasă, Iulian, Lupușoru, Mircea, Geantă, Marius, Andronic, Octavian, Grumezescu, Alexandru Mihai, Martins, Henrique
Format Journal Article
LanguageEnglish
Published Switzerland MDPI AG 18.04.2022
MDPI
Subjects
Accuracy
Algorithms
Artificial intelligence
Automation
Business metrics
Cardiac arrhythmia
Cardiology
Classification
Clinical medicine
Electronic health records
Gastroenterology
Health care
Hematology
Hepatology
Hypertension
Mathematical functions
Medical prognosis
Nephrology
Neural networks
Orthopedics
Patients
Review
Rheumatology
Software
Tomography
Wavelet transforms
Wearable computers
deep learning
precision medicine
machine learning
clinical applications
artificial intelligence
personalized medicine
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Summary:Artificial intelligence has the potential to revolutionize modern society in all its aspects. Encouraged by the variety and vast amount of data that can be gathered from patients (e.g., medical images, text, and electronic health records), researchers have recently increased their interest in developing AI solutions for clinical care. Moreover, a diverse repertoire of methods can be chosen towards creating performant models for use in medical applications, ranging from disease prediction, diagnosis, and prognosis to opting for the most appropriate treatment for an individual patient. In this respect, the present paper aims to review the advancements reported at the convergence of AI and clinical care. Thus, this work presents AI clinical applications in a comprehensive manner, discussing the recent literature studies classified according to medical specialties. In addition, the challenges and limitations hindering AI integration in the clinical setting are further pointed out.
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ISSN:2077-0383
2077-0383
DOI:10.3390/jcm11082265