1. Promises, Pitfalls, and Clinical Applications of Artificial Intelligence in Pediatrics.
- Author
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Bhargava H, Salomon C, Suresh S, Chang A, Kilian R, Stijn DV, Oriol A, Low D, Knebel A, and Taraman S
- Subjects
- Humans, Child, Algorithms, Software, Intelligence, Artificial Intelligence, Medicine
- Abstract
Artificial intelligence (AI) broadly describes a branch of computer science focused on developing machines capable of performing tasks typically associated with human intelligence. Those who connect AI with the world of science fiction may meet its growing rise with hesitancy or outright skepticism. However, AI is becoming increasingly pervasive in our society, from algorithms helping to sift through airline fares to substituting words in emails and SMS text messages based on user choices. Data collection is ongoing and is being leveraged by software platforms to analyze patterns and make predictions across multiple industries. Health care is gradually becoming part of this technological transformation, as advancements in computational power and storage converge with the rapid expansion of digitized medical information. Given the growing and inevitable integration of AI into health care systems, it is our viewpoint that pediatricians urgently require training and orientation to the uses, promises, and pitfalls of AI in medicine. AI is unlikely to solve the full array of complex challenges confronting pediatricians today; however, if used responsibly, it holds great potential to improve many aspects of care for providers, children, and families. Our aim in this viewpoint is to provide clinicians with a targeted introduction to the field of AI in pediatrics, including key promises, pitfalls, and clinical applications, so they can play a more active role in shaping the future impact of AI in medicine., (©Hansa Bhargava, Carmela Salomon, Srinivasan Suresh, Anthony Chang, Rachel Kilian, Diana van Stijn, Albert Oriol, Daniel Low, Ashley Knebel, Sharief Taraman. Originally published in the Journal of Medical Internet Research (https://www.jmir.org), 29.02.2024.)
- Published
- 2024
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