AI in Health Care: Applications, Benefits, and Examples

Artificial intelligence (AI) has already changed much of the world as we know it—from automating systems to improving the decisions we make and the ways we go about making them. Yet AI in health care is perhaps the most impactful and personal way AI is changing our world, as it’s helping to diagnose, create personalized treatment plans, and even predict patient survival rates. 

Explore the types of AI used in health care, some of their applications, the benefits of AI within the field, and what the future might hold. You’ll also discover relevant jobs and online courses that can help you start learning to use AI for health care purposes today.

How is AI used in health care?

Artificial intelligence (AI) uses computers and machine processes to simulate human intelligence and perform complex automated tasks in health care. While they seek to reflect the abilities of the human mind, AI-enabled machines are also capable of exceeding it in a number of ways, particularly by sifting through large volumes of big data efficiently in order to identify patterns, anomalies, and trends. 

Unsurprisingly, AI presents a wealth of opportunities to health care, where providers can use it to enhance a variety of common medical processes—from diagnosing diseases to identifying the best treatment plans for patients facing critical illnesses like cancer. Robotic surgical equipment outfitted with AI can help surgeons better perform surgeries by decreasing their physical fluctuations and providing updated information during the operation.

Types of AI in health care

AI is an umbrella term covering a variety of distinct but interrelated processes. Some of the most common forms of AI used within health care include: 

• Machine learning (ML): Training algorithms using data sets, such as health records, to create models capable of performing such tasks as categorizing information or predicting outcomes. 

• Deep learning: A subset of machine learning that involves greater volumes of data, training times, and layers of ML algorithms to produce neural networks capable of more complex tasks. 

• Natural language processing (NLP): The use of ML to understand human language, whether it be verbal or written. In health care, NLP can help interpret documentation, notes, reports, and published research. 

• Robotic process automation (RPA): The use of AI in computer programs to automate administrative and clinical workflows. Some health care organizations use RPA to improve the patient experience and the daily function of their facilities. 

How AI is helping in the health care industry

As artificial intelligence becomes more widely adopted, so too does the number of ways professionals are using the technology across industries. Researchers don’t expect AI to replace health care professionals just yet. Instead, they see it as supporting and improving the work of health providers and professionals in the near future. Some of the most common applications of AI in the field today are:

• Health care analytics: ML algorithms train on historical data to produce insights, improve decision-making, and optimize health outcomes.

• Precision medicine: AI helps produce personalized treatment plans for patients that take into account such factors as their medical history, environmental factors, lifestyles, and genetic makeup. 

• Predicting diseases and illness: Using predictive models, health care professionals can determine the likelihood that someone might develop a particular condition or contract a disease. 

• Interpret tests and diagnose diseases: ML models can be trained using common medical scans, like MRIs or X-rays, to interpret and diagnose such conditions as cancerous lesions.

The future of AI in mental health care

Like health care as a whole, artificial intelligence offers benefits that providers can use for mental health care. Mental health care often involves working to understand complex emotions and what motivates them, which is more difficult to imagine a machine excelling at. But the increasing need for mental health care worldwide offers an opportunity for AI to help doctors meet patient needs. In the future, AI in mental health care could look like identifying patterns from the many sources of data patients interact with daily (medical records, search history, or social media posts and usage, for example) to diagnosis illness, or it could look like natural language processing algorithms tracking the sentiment of the words they use online or in emails to intercede when a patient might be in crisis.

Benefits of AI in health care

AI provides a number of benefits to the field of health care, the professionals working within it, and the patients who interact with it every day. While health care professionals can expect lower operational costs due to improved decision-making and more efficient automated services, providers can leverage the technology to design bespoke treatment plans and diagnose conditions more quickly and accurately than they could alone. Patients may experience improved health outcomes and lower costs resulting from more efficient health services. 

AI jobs in health care 

Both AI and health care are growing fields that are likely to have a big impact in the coming decade. It’s little surprise, then, that AI-oriented positions are becoming increasingly common within the field of health care. 

If you’d like to pursue one of these careers, consider exploring some of the following positions: 

1. Health informatics specialist 

2. Machine learning engineer 

3. Data scientist 

4. AI engineer

The AI market in health care 

As with many other industries, AI is likely to change the health care landscape over the coming years. In addition to improving health facility operations, patient diagnoses, treatment plan development, and overall health outcomes, AI is also expected to help with the development and discovery of new medical cures. 

The use of artificial intelligence in health care is likely to grow significantly over the next decade. According to Grand View Research, AI in health care represented a market worth $19.27 billion in 2023, with a projected compounded annual growth rate of 38.5 percent every year through 2030 [1]. 

Explore AI in health care on Coursera 

AI is a growing and complicated field with a wealth of potential. If you’re considering a career using AI to help improve health care and maybe even solve some of the most elusive medical mysteries, then you might consider taking a relevant course through Coursera. 

Deeplearning.ai’s AI for Medicine Specialization, for example, provides practical experience applying machine learning to concrete problems in medicine like predicting patient survival rates, estimating treatment plan efficacy, and diagnosing diseases from 3D MRI brain scans.