Should Artificial Intelligence Play a Durable Role in Biomedical Research and Practice?

Area of Science:

• Biomedical Research
• Artificial Intelligence
• Machine Learning

Background:

• Biomedical research faces increasing complexity in elucidating intricate systems.
• Traditional methods like theoretical modeling and computer simulation are insufficient for current challenges.
• The growing need for advanced analytical tools in life sciences is evident.

Purpose of the Study:

• To evaluate the barriers in current biomedical research.
• To assess the potential of artificial intelligence (AI) in overcoming these barriers.
• To determine the future role of AI in biomedical practice.

Main Methods:

• Analysis of major barriers in biomedical research over the last two decades.
• Examination of AI's capabilities in classification, prediction, and data interpretation for multivariate systems.
• Review of recent machine learning results comparing AI efficiency with human operators.

Main Results:

• Biomedical research increasingly requires methods to elucidate complex systems.
• AI, especially machine learning, is well-suited for classification and prediction in multivariate systems.
• AI demonstrates efficiency comparable to human operators in specific tasks.

Conclusions:

• Artificial intelligence should play a significant and durable role in biomedical research.
• Combining AI with conventional methods can drive further progress and novel applications.
• AI enhances data interpretation and heuristic approaches in biomedical science.