Artificial intelligence (AI) is already changing much of the world as we know it, from automating systems to improving the way we make and execute decisions. But perhaps the most impactful and personal way in which AI is changing our world is in the medical field. Here’s what you need to know at a glance:
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The adoption of AI in the medical field is progressing rapidly. Menlo Ventures reports that 22% of healthcare organizations will have “domain-specific AI tools” in place in 2025, a 10x increase from 2023. [1].
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Common uses of AI in the healthcare industry include diagnosing patients, creating personalized treatment plans, recording medical visits, and for medical coding and billing purposes.
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Common AI technologies used in the medical field include machine learning, deep learning, natural language processing, and generative AI.
Below, we discuss the types of AI used in healthcare, its applications, the benefits of AI in this field, and future prospects. Then, if you want to continue learning, consider enrolling in Stanford University’s AI in Healthcare Specialization.
How is AI used in the medical field?
Artificial intelligence uses computers and machine processes to simulate human intelligence and perform complex automated tasks in healthcare. While AI-enabled machines seek to mirror the capabilities of the human mind, they can also exceed it in many ways, especially by efficiently sifting through large amounts of big data to identify patterns, anomalies, and trends.
Unsurprisingly, AI presents a wealth of opportunities in healthcare, and healthcare providers can use it to enhance a variety of common healthcare processes, from diagnosing diseases to identifying optimal treatment plans for patients facing serious illnesses such as cancer. Robotic surgical devices powered by AI can help surgeons perform surgeries better by reducing their physical fluctuations and providing up-to-date information during surgery.
What are some use cases for AI in healthcare?
AI is an umbrella term that covers a variety of different but interconnected processes. Some of the most common forms of AI used in the medical field include:
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Machine learning (ML): Datasets such as health records are used to train algorithms to create models that can perform tasks such as classifying information and predicting outcomes.
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deep learning: A subset of machine learning that involves larger amounts of data, training time, and layers of ML algorithms to produce neural networks that can perform more complex tasks.
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Natural language processing (NLP): The use of ML to understand human language, whether oral or written. In the medical field, NLP helps interpret documents, notes, reports, and published research.
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Robotic Process Automation (RPA): The use of AI in computer programs to automate administrative and clinical workflows. Some healthcare organizations are using RPA to improve the patient experience and day-to-day functionality of their facilities.
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Generative AI: This widespread form of AI uses large-scale language models (LLMs) to create original output in response to unique user input, allowing the model to generate text, create documents, analyze data, and more. In healthcare, generative AI is used for everything from creating patient notes and documents, to reviewing medical literature, to helping find new treatments.
Artificial intelligence tools are on the rise in healthcare. Below are some of the ones you may come across as they become increasingly common.
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Merativ (Formerly IBM Watson Health): This platform provides a suite of data and AI-powered solutions to those working in industries such as clinical trials, imaging, and clinical decision support.
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Chat GPT: This popular generative AI tool from OpenAI can be implemented across your organization to reduce documentation time, securely streamline care workflows, and assist with administrative tasks.
How has AI impacted the healthcare industry?
As artificial intelligence becomes more widely adopted, so too are the ways in which professionals are using the technology across industries. Researchers still don’t expect AI to replace medical professionals. Rather, they believe it will support and improve the work of health care providers and professionals in the near future. The most common applications of AI in the field today are:
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precision medicine: AI can help create personalized treatment plans for patients, taking into account factors such as medical history, environmental factors, lifestyle, and genetic makeup.
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Interpret tests and diagnose diseases. ML models can be trained using common medical scans, such as MRIs and X-rays, to interpret and diagnose conditions such as cancerous lesions.
The future of AI in mental health care
As with healthcare as a whole, artificial intelligence offers benefits that healthcare providers can leverage in mental healthcare. Mental health care often involves understanding complex emotions and their motivations, but it’s even harder to imagine machines being better at it. However, the growing need for mental health care around the world is creating an opportunity for AI to help doctors meet the needs of their patients.
In the future, AI in mental health care could look like things like natural language processing algorithms that diagnose illnesses by identifying patterns in the many data sources that patients interact with on a daily basis, such as medical records, search history, and social media posts and usage, or that track the sentiment of the words patients use online or in email to mediate in a crisis.
Benefits of AI in Healthcare
AI offers many benefits to the medical field, the professionals who work in it, and the patients who interact with it every day. Healthcare professionals can expect to reduce operational costs through improved decision-making and more efficient automated services, while healthcare professionals can leverage this technology to design tailored treatment plans and diagnose conditions faster and more accurately than they could on their own. Patients could see improved health outcomes and lower costs through more efficient healthcare services.
AI market in healthcare
Like many other industries, AI is already changing the healthcare landscape. AI is expected to help run medical facilities, diagnose patients, develop treatment plans, improve overall health, as well as develop and discover new treatments.
The use of artificial intelligence in healthcare is expected to increase significantly over the next decade. According to Grand View Research, the market size for AI in healthcare is expected to reach $36.67 billion in 2025, with a compound annual growth rate of 38.90 percent annually from 2026 to 2033. [2].
Explore AI in Healthcare on Coursera
AI is a growing, complex field with a wealth of potential. Use the following resources from Coursera to build the skills you need to master this increasingly impactful technology and apply it to your healthcare outcomes.
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