As a transformational force in the healthcare sector, artificial intelligence (AI) has become an attention point among health professionals and researchers. AI has started assisting healthcare professionals in providing more efficient patient care, treatment variability, and diagnostics.

 

This article explains the use of AI in healthcare, its growth in the medical field, and its limitations in healthcare.

 

What Is Artificial Intelligence In Healthcare?

Artificial intelligence in healthcare is a computer-assisted technology that uses complex algorithms specially designed to accelerate diagnostic processes, patient outcomes, and treatment techniques.

 

Arterial spin labeling (ASL) imaging, Natural language processing (NLP), ASSL-MRI, and Brain-computer interfaces (BSIs) are some automated algorithms and tools that aim to prevent disease progression, minimize errors, and help medical professionals to handle diverse medical data [1].

 

Artificial intelligence helps researchers inject data into computers. The algorithm then evaluates and interprets the data. AI algorithms also deploy solutions to complex medical problems [2]. 

 

Applications Of AI In Healthcare:

Here are some currently implied applications of AI in healthcare:

 

1. Drug Discovery: 

The lengthy and expensive process of drug discovery has found its place in Artificial Intelligence. The identification and testing of new drugs is a lengthy and tedious process. Still, Artificial Intelligence has helped many pharmaceutical companies to adopt different algorithms that save time and identify patterns that are far more complex for humans to identify [3].

 

2. Improved Patient Outcomes: 

Artificial Intelligence has revolutionized the healthcare sector by improving patient outcomes in different ways, among which reduced span of hospital stays, patient satisfaction, and cost savings are most common. There has been a 3x more reduction in the costs of both patient and provider [4].

 

3. Pain Management: 

This emergent healthcare area is currently leveraging Artificial Intelligence combined with Virtual Reality (VR) to help patients with the opioid crisis. Both these technologies design "simulated realities" that divert patients' attention from the source of their pain.

 

Benefits Of AI In Healthcare:

We have counted some benefits of AI that has revolutionized the science of healthcare:

 

1. Health Monitoring Through Personal Devices And Wearables: 

AI plays a significant role in patient care by generating health-related data derived from devices. Now, people can track their health by wearing devices with sensors. For example, you can now track your heartbeat through your smartphone.

 

2. Revolutionized Clinical Decision Making:

AI is continuously transforming the healthcare sector by helping the providers get ahead through different healthcare challenges by powering clinical decision-making support tools. For example, doctors can take help from AI to make decisions about whether or not a patient with cardiac arrest needs continuous care.

 

3. Bringing Intelligence To Smart Devices: 

The use of AI in smart devices has made it easier for both physicians and patients. Now, a physician can monitor the patient in the ICU through smart devices to ensure that the patient is receiving continuous care.

 

4. Developing Radiology Tools: 

There are many diagnostic processes that carry the risk of infection with the need for physical tissue samples. AI has authorized the development of the next generation of radiology tools to replace the need for physical tissue samples [5]. 

 

 

References: 

 

[1] Secinaro S, Calandra D, Secinaro A, Muthurangu V, Biancone P. The role of artificial intelligence in healthcare: a structured literature review. BMC Med Inform Decis Mak 2021;21:125. https://doi.org/10.1186/s12911-021-01488-9.

[2] Yu K-H, Beam AL, Kohane IS. Artificial intelligence in healthcare. Nat Biomed Eng 2018;2:719–31. https://doi.org/10.1038/s41551-018-0305-z.

[3] Datta S. Application of Artificial Intelligence in Modern Healthcare System. In: Barua R, editor., Rijeka: IntechOpen; 2020, p. Ch. 8. https://doi.org/10.5772/intechopen.90454

[4] Bobak CA, Svoboda M, Giffin KA, Wall DP, Moore J. Raising the stakeholders: Improving patient outcomes through interprofessional collaborations in AI for healthcare. Biocomput. 2021, WORLD SCIENTIFIC; 2020, p. 351–5. https://doi.org/doi:10.1142/9789811232701_0035.

[5] Vallabhaneni A, Wang T, He B. Brain—Computer Interface BT - Neural Engineering. In: He B, editor., Boston, MA: Springer US; 2005, p. 85–121. https://doi.org/10.1007/0-306-48610-5_3.

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