Overview

What is artificial intelligence in medicine?

Artificial intelligence (AI) is technology patterned after the brain’s neural network sand uses multiple layers of information – including algorithms, pattern matching, rules, deep learning and cognitive computing – to learn how to understand data.

How do we use AI in medicine

AI-enabled tools can identify meaningful relationships in raw data and has the potential to be applied in almost every field of medicine, including drug development, treatment decisions, patient care, and financial and operational decisions.

With AI, healthcare professionals could can tackle complex problems that would be difficult, time-intensive, or inefficient to address alone.AI could be a valuable resource for medical professionals, allowing them to better use their expertise and provide value across the health ecosystem.

A physician reviews medical images on a monitor

Use cases

Benefits of artificial intelligence in medicine

AI-enabled tools can extract relevant information from large amounts of data and generate actionable insights that could be applied to many applications.

Surfacing treatment insights

With AI technologies, physicians could find information in unstructured medical literature to support care decisions.

Supporting user needs

AI can search and present data to help people find use full health information, which could lead to more informed users.

Identifying insights from patient data

AI tools could search structured and unstructured medical records to provide relevant patient histories.

Targeting similarities and patterns

AI could identify patterns and help researchers create dynamic patient cohorts for studies and clinical trials.

Evolution

About artificial intelligence in medicine

Before AI started being applied to medical information in the 2000s, predictive models in healthcare could only consider limited variables in clean and well-organized health data.Today, sophisticated machine-learning tools that use artificial neural networks to learn extremely complex relationships or deep learning technologies have been shown to support —and at times, exceed —human abilities in performing some medical-related tasks.AI systems are designed to tackle the complex data that has been generated from modern clinical care.

AI technologies, such as IBM Watson, are being used by healthcare providers, leaders and researchers to leverage millions of medical reports, patient records, clinical trials and medical journals to reveal data insights.

Role of AI

Why is artificial intelligence in medicine important?

Cutting through the noise

AI could help make sense of the overwhelming amount of clinical data, medical literature, and population and utilization data to inform decisions.

Providing contextual relevance

AI could empower healthcare providers to see expansively by quickly interpreting billions of data points–both text and image data –to identify contextually relevant information for individual patients.

Reducing errors related to human fatigue

Human error is costly and human fatigue can cause errors. AI algorithms don’t suffer from fatigue, distractions or moods. They could process vast amounts of data with incredible speed and accuracy.

Identifying diseases more readily

AI systems could be used to spot anomalies in medical images, such as MRIs or CT scans.

Increasing doctor-patient engagement

AI automation allows physicians to spend less time on data entry and desk work and more time engaging with patients.

Reducing cost of care

AI could help determine important utilization information, such as what citizens are eligible for assistance across health and human services programs.

Watson Health AI solutions

IBM has been a pioneer in developing AI software specifically for healthcare.