Customize Consent Preferences

We use cookies to help you navigate efficiently and perform certain functions. You will find detailed information about all cookies under each consent category below.

The cookies that are categorized as "Necessary" are stored on your browser as they are essential for enabling the basic functionalities of the site. ... 

Always Active

Necessary cookies are required to enable the basic features of this site, such as providing secure log-in or adjusting your consent preferences. These cookies do not store any personally identifiable data.

No cookies to display.

Functional cookies help perform certain functionalities like sharing the content of the website on social media platforms, collecting feedback, and other third-party features.

No cookies to display.

Analytical cookies are used to understand how visitors interact with the website. These cookies help provide information on metrics such as the number of visitors, bounce rate, traffic source, etc.

No cookies to display.

Performance cookies are used to understand and analyze the key performance indexes of the website which helps in delivering a better user experience for the visitors.

No cookies to display.

Advertisement cookies are used to provide visitors with customized advertisements based on the pages you visited previously and to analyze the effectiveness of the ad campaigns.

No cookies to display.

Is healthcare ready for artificial intelligence to take over?

Reading Time: < 1 minute

Artificial intelligence (AI) is revolutionizing the field of medicine, with algorithms already matching or surpassing human performance in various diagnostic procedures. However, a recent study published in The Lancet Digital Health highlights the need for more rigorous testing and research before widespread implementation.

One example cited in the study is the Epic Sepsis Model, used in hundreds of U.S. hospitals to predict sepsis. Despite its widespread use, the model has not been adequately tested and has shown poor performance in identifying septic patients.

The review also found that AI systems have the potential to improve disease management in various areas, such as optimizing insulin dosage, reducing tumor volume in radiation therapy, and predicting diabetic retinopathy risk. These findings suggest that AI can enhance patient care and clinical decision-making efficiency.

However, the study also revealed a lack of randomized controlled trials in primary care, which is essential for all medical specialties. The majority of studies were conducted in individual countries, primarily the United States and China, highlighting the need for more international collaboration and multicenter trials to ensure the generalizability of AI systems across different populations and healthcare systems.

Overall, while AI shows promise in improving healthcare outcomes, there is still a long way to go in terms of rigorous testing and research to fully realize its potential in clinical practice. The findings underscore the importance of continued research and collaboration to harness the full benefits of AI in medicine.

Taylor Swifts New Album Release Health issues from using ACs Boston Marathon 2024 15 Practical Ways To Save Money