Artificial Intelligence in Clinical Health Care Applications: Viewpoint

TL;DR

This paper discusses the potential and challenges of applying AI in clinical healthcare, emphasizing recent technological advances and proposing recommendations to enhance AI projects in biomedical applications.

Contribution

It provides a comprehensive viewpoint on AI's role in healthcare and offers specific recommendations to address challenges in biomedical AI projects.

Findings

AI is increasingly promising for healthcare applications

Challenges in biomedical AI include data quality and integration

Recommendations aim to improve AI project success in clinical settings

Abstract

The idea of Artificial Intelligence (AI) has a long history. It turned out, however, that reaching intelligence at human levels is more complicated than originally anticipated. Currently we are experiencing a renewed interest in AI, fueled by an enormous increase in computing power and an even larger increase in data, in combination with improved AI technologies like deep learning. Healthcare is considered the next domain to be revolutionized by Artificial Intelligence. While AI approaches are excellently suited to develop certain algorithms, for biomedical applications there are specific challenges. We propose recommendations to improve AI projects in the biomedical space and especially clinical healthcare.