AI in Healthcare: Applications, Benefits, and Examples

Written by Coursera Staff • Updated on

AI is changing how healthcare professionals provide care and how patients receive it. Learn more about what AI means for the field today—and in the coming years.

[Featured Image]:  Health informatics specialist analyzing patients' data.

Artificial intelligence (AI) has already changed much of the world as we know it—from automating systems to improving the decisions we make and how we make them. Yet, perhaps the most impactful and personal ways AI is changing our world are within healthcare, where it's being used to diagnose, create personalised treatment plans, and even predict patient survival rates. 

Read on to learn more about the types of AI used in healthcare, some of their applications, and their benefits. Also, explore relevant jobs and online courses that can help you get started with using AI for healthcare purposes today.  

How is AI used in healthcare?

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

Unsurprisingly, AI presents a wealth of opportunities in healthcare. It can be used 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 perform surgeries better by decreasing their physical fluctuations and providing updated information during the operation.  

Types of AI in healthcare

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

  • Machine learning (ML): Algorithms are trained using data sets, such as health records, to create models capable of performing tasks such as categorising information or predicting outcomes. 

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

  • Natural language processing (NLP): NLP involves the use of ML to understand human language, whether it be verbal or written. In healthcare, NLP is used to interpret documentation, notes, reports, and published research. 

  • Robotic process automation (RPA): This involves the use of AI in computer programs to automate administrative and clinical workflows. Some healthcare organisations use RPA to improve the patient experience and the daily function of their facilities. 

AI applications in healthcare

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

  • Healthcare analytics: ML algorithms are trained using historical data to produce insights, improve decision-making, and optimise health outcomes.

  • Precision medicine: AI is used to produce personalised treatment plans for patients and take into account factors such as their medical history, environmental factors, lifestyles, and genetic makeup.

 

  • Predict diseases and illness: Using predictive models, healthcare 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 conditions such as cancerous lesions.

Benefits of AI in healthcare

AI provides a number of benefits to the field of healthcare, the professionals working within it, and the patients who interact with it every day. Whilst healthcare 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 can expect potentially improved health outcomes and lower costs resulting from more efficient health services. 

AI jobs in healthcare 

Both AI and healthcare are growing fields that are projected 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 healthcare. 

If you’re interested in pursuing one of these careers, below are some of the positions you should consider exploring: 

*Health informatics specialist 

*Machine learning engineer 

*Data scientist 

*AI engineer

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The future of AI in healthcare 

As with many other industries, AI is poised to change the healthcare 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. For instance, NITI Aayog, the public policy think tank of the Indian government, has been exploring the use of AI to detect diabetes early and is now focusing on employing AI as a screening tool in eye care.

The use of AI in healthcare is expected to grow significantly over the next decade. According to Grand View Research, the global market for AI in healthcare is projected to expand at a CAGR of 38.5 per cent between 2024 and 2030 [1]. By 2025, India's investment in AI healthcare is forecasted to reach 11.78 billion USD, potentially resulting in a 1 trillion USD boost to the economy by 2035 [2].

Get started with Coursera 

AI is a growing and complicated field with a wealth of potential. If you’re considering a career using AI to help improve healthcare 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 Specialisation, for example, provides practical experience in applying machine learning to concrete problems in medicine, such as predicting patient survival rates, estimating treatment plan efficacy, and diagnosing diseases from 3D MRI brain scans. 

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Written by:
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