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The Intersection between Medicine and Artificial Intelligence (AI)

By Sowmiya T on June 21, 2024

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As I had written in a previous blog article, Artificial Intelligence (AI) is a tool being used in medicine to deliver more precise healthcare outcomes by observing one’s genes and physical traits. It is an interesting development that goes beyond the current capabilities of medicine. Let us look into it in greater depth by focusing on two applications: clinical decision support and imaging analysis.

In clinical decision support, AI is used to analyze large amounts of data and predict possible treatments and their complications, as well as provide efficient ways for healthcare workers to solve problems. This is done with the help of health data available from patient records as well as population data.

Here are some examples of its applications:

* The use of several ML models to predict the long-term survival of patients after cardiac surgery
* The experimentation and comparison of AI algorithms to predict the survival of ICU patients due to heart rate variability (HRV)

In imaging analysis, AI is being used to automate routine processes such as image processing, quality control, and data management. This improves the precision of the analysis and can lead to better patient outcomes.

Listed below are a few ways that AI simplifies imaging:

  • Segments and labels organs
  • Checks photos for quality
  • Organize large volumes of relevant data

By easing the burden of healthcare workers, AI seeks to improve patient care as well as allow healthcare professionals to advance in their careers. In the future, we can hope for AI to complement medical workers by preparing data for quick consultation and approval so that time can be saved in treatments of patients. It could even assist physicians in finding new treatments by analyzing data and patterns using its algorithms, especially with the growth of neural networks.

Thank you Sharon V for editing this article! peer tutoring, for free.


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