6 Incredible Use Cases Where AI Is Impacting Healthcare

Written by Guest author on 18 Mar 2021

Artificial intelligence has been disrupting different industries for a couple of years now. Healthcare is one of the fields that greatly benefit from this advanced technology.

From hospital care, drug development, clinical research, and diagnostics, every segment of the healthcare sector has been impacted by the life-changing power of AI and its branches.

The latest research has shown that the global AI in the healthcare market is expected to grow from $4.9 billion in 2020 to $45.2 by 2026. There are numerous reasons for this meteoric rise, but some of the most prominent include an attempt to slash the growing healthcare costs and a huge increase in healthcare data.

Also, as we’ve recently witnessed, the need to speed up COVID-19 vaccine development has been a critical factor that spurred the adoption of this technology by pharmaceutical and biotech companies.

Here’s a list of some really incredible use cases of AI in healthcare.

1. The Digitization of Pathology

Digital pathology is a medical field dealing with capturing, management, sharing, and interpretation of digitized specimen slides. These microscopic tissue samples are digitized when high-resolution images of glass slides are taken using a whole slide imaging scanner.

Deep learning, a subset of AI, is used for analyzing digital images and automated tumor detection.

This AI-powered approach helps pathologists:

  • Reduce the risk of glass slides breakage in transit
  • Eliminate the risk of misidentification
  • Zoom in and get multiple angle views
  • Access previous cases quickly and easily
  • Share and access data remotely
  • Improve long-term predictive analytics.

In a nutshell, the digitalization of specimen slides allows pathologists to see minuscule details that they wouldn’t be able to notice with the naked eye, thus improving and accelerating the triage process, and providing more accurate diagnostics.

2. Robotic Surgery

Precision plays a critical role in surgical procedures, and given that sometimes they can last for hours, surgeons have to struggle with exhaustion that can affect their performance.

The synergy of AI and computer vision software is a game-changer in this field, as intelligent robot surgeons can work for hours without a pause and still keep the same level of precision. Moreover, the AI element is what allows these mechanical surgeons to conduct procedures independently.

Abdominal surgeons use eye-tracking camera control with pan and zoom features to move the robotic arm during delicate surgical procedures that require steady hands. Similarly, robotic surgeons can perform complex movements on a small scale with the help of micro-instrumentation, meaning that they can perform delicate procedures.

3. Healthcare Bots

AI-powered conversational chatbots can facilitate the triage process and allow patients to access reliable and accurate healthcare information.

For example, many people tend to search the internet in an attempt to identify the cause of their symptoms. With the help of conversational chatbots, healthcare providers can help their users understand whether their condition requires urgent medical attention or they can resolve the issues they have via teleconsultations.

In addition to that, healthcare chatbots can streamline the process of appointment scheduling, handle paying medical bills, and collecting patient information while ensuring HIPAA and GDPR compliance.

By implementing the right chatbot strategy, healthcare providers will be able to provide care to more patients and:

  • Reduce waiting times
  • Scale customer support
  • Offer timely medical advice
  • Obtain feedback from patients
  • Automate payments
  • Minimize expenses.

4. Improving Health Outcomes With EHR Data

Electronic Health Records (EHRs) are packed with valuable information about patients such as patient history, current status, or previous medical treatments and procedures.

65% of physicians say that using EHRs allows them to deliver better patient care.

However, all that data isn’t readily available, meaning that medical professionals have to sift through mountains of clutter in order to find the most important insights.

AI together with big data analytics, can be employed to analyze EHRs and unearth relevant pieces of information about patients, that are easily overlooked so that doctors and nurses can make informed decisions. This way, preventable errors such as adverse drug reactions can be avoided, while the most effective medication can be prescribed.

As a result, health outcomes can be significantly improved.

Organizations like KenSci help healthcare providers manage and use their EMR data, transforming them into AI ready models and use cases.

5. Drug Research and Development

The process of drug discovery and development is long, challenging, and expensive.

Sometimes researchers spend years working on a new drug, only to find that it isn’t successful after it’s tested on live human subjects.

Artificial intelligence and machine learning can process and interpret vast datasets, and help scientists identify targets, isolate molecule candidates that deserve their attention, and simulate billions of interactions between drugs and their biological targets, and all that within minutes.

In other words, researchers feed AI tools sample problems, that is a molecule, and solutions, that is how that particular molecule should behave as a drug, without providing expert-developed analytical techniques. Instead, AI tools develop their own computational approach in order to generate the same solutions.

By adding patient data into this equation, researchers can prevent serious side effects and create safer drugs.

6. Virtual Nursing Assistants

In situations where medical facilities deal with high volumes of patients and nurses have to take care of many patients simultaneously, advanced technology can come in handy to pick up some slack and reduce the workload.

Virtual nursing assistants are capable of performing different healthcare tasks such as monitoring patients’ vitals remotely 24/7, notifying and alerting healthcare providers when something isn’t right, checking whether patients stick to their care plans, and allowing for care outside the clinical setting.

These intelligent robotic nurses are built using different technologies, including ML, computer vision, natural language processing, advanced robotics, and big data.

Some of them, like Pepper, the humanoid robot, can even recognize faces, detect patients’ gender, or communicate with them in more than 20 languages. RIBA, or Robot for Interactive Body Assistance, can turn patients in bed, lift them, and help them stand.

Artificial intelligence has brought numerous innovations to the healthcare landscape and helped it evolve tremendously. Both healthcare providers and their patients see the benefits of implementing this technology, and these six use cases illustrate how powerful the impact of this technology is.

 

About the author

Jennifer Wilson is a writer at Qeedle.com She knows business processes and operations management inside out. As she understands all the challenges of running a small business firsthand, it’s her mission to tackle the topics that are most relevant to entrepreneurs and offer viable solutions.

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