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Why We Need Synthetic Data in Clinical Trials

Nuvanitic

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Dashboard showing Clinical Trials
Data illustrations by Story set

The benefits of artificial intelligence (AI) and machine learning (ML) in clinical trials are immense. We’re living in a global society where information can travel the globe quickly, and diseases are more common as we live longer; we need to roll out advances in medicine faster than ever.

AI and ML are two areas that can provide the speed and accuracy to get through many stages of clinical trials. They can do it safely and assess potential issues before any living thing ever gets involved in a clinical trial.

Follow along as we review what AI and ML can do for clinical trials and why the benefits are worth investing more resources into advancing the technologies and incorporating them into all clinical trials.

What’s the Difference Between Artificial Intelligence and Machine Learning?

Artificial Intelligence

Artificial Intelligence is the concept of machines performing intelligent tasks that a human would otherwise do. For example, sorting a collection of pills based on just weight isn’t intelligent; you’re just using an automated scale. However, sorting pills based on weight, what they look like, what they say on them, and numerous other factors would be considered Artificial Intelligence.

A pill dispenser, while seemingly simple, can remove human error from dispensing pills, either the wrong pill or even a pill that will interact poorly with other prescribed medications to the patient.

Machine Learning

Machine learning is a subset of artificial intelligence, but instead of manually programming a commuter with the intelligence you require, you create a program that can learn and build on experience and patterns to make decisions and connections that it wasn’t given initially.

Clinicians can use machine learning to provide data and then have potential diagnoses provided back based on the symptoms and vital statistics of a patient.

Benefits of…

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