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The Current State of AI in Healthcare and Where It’s Going in 2023

Introduction

The potential for using artificial intelligence to aid medical personnel in gaining crucial insights and enhancing patient outcomes is enormous. Although the adoption of AI in the healthcare industry has been slow, health insurers found that 87% of healthcare executives have an AI plan and that approximately 50% of those polled currently utilize the technology.

By detecting and analyzing both structured and unstructured data, AI in healthcare is helping to improve data flow. Now is the time to invest in artificial intelligence even if you’re still debating it.

Executive Summary

With the new performance improvements in data analysis, AI in healthcare recognizes patterns and is producing insights that could escape a doctor’s manual efforts.

Present And Beyond Of AI In Healthcare

The following trends for AI in healthcare of the current year, 2023, and over the following few years are:

1.    Retail Healthcare Will Be Doubled

In 2023, the volume of healthcare-related retail business will double, and it will even rise in the following few years. With businesses like Walmart, Amazon, and CVS now providing healthcare services like blood testing, immunizations, and physicals that were previously only available via hospitals, clinics, or doctor’s offices, this trend is becoming more and more obvious.

When budgets at established front-line primary care facilities are stretched as a result of the current global economic climate, this trend will be more pronounced. This is made worse by the fact that retail healthcare providers are utilizing customer expectations for a simplified customer experience and choice to develop services that consumers will find to be more practical and cost-effective than traditional primary healthcare provision.

2.    Automated Scheduling

In the upcoming year and beyond, expect automated scheduling to advance. You will see these businesses embracing automated scheduling the most as retail health now shifts to primary care. There aren’t many conventional healthcare providers who use it.

3.    Targeted Diagnosis and Tailored Treatment Will Be Made Possible by AI

Healthcare practitioners will be able to create targeted diagnostics and tailor care as they sound right from large datasets. Numerous customers of ours are attempting to index this data to arrange it. Unfortunately, the procedure is prone to mistakes. With these technologies, we are taking away all the hard lifting for a lot of these clients since it is highly expensive and operationally challenging, allowing them to concentrate on providing their patients with care and communities.

4.    Government AI Rules Will Be Stricter

Entrepreneurs and businesses in the field of medical AI will have to handle this element. That, in my opinion, will be a big transition from the field of medical decision support systems to that of medical devices. In the U.S. and Europe, AI regulation will tighten as the FDA chooses which medical equipment to acknowledge.

5.    Wearable Medical Devices

More people will be using wearable technology to check their fitness and health, as well as to monitor patients from a distance in the next few years.

The “Internet of Medical Things” has grown quickly in recent years from basic monitoring devices for vital signs like heart rate and oxygen levels of blood to smartwatches with ECG capabilities, smart fabrics that could detect blood pressure and foretell the likelihood of heart attacks, and smart gloves that can lessen Parkinson’s disease patient’s tremors.

In addition to physical sickness, there is an increasing focus on creating wearable technology that can track and identify symptoms of mental illnesses.

6.    Artificial Intelligence for Dialogue and NLP

Although NLP and conversational AI have improved the healthcare industry, experts predict that during the next one to three years, the use of virtual assistants will grow significantly. The practice of triage and symptom checking will become increasingly common and complex. AI will assist healthcare professionals in separating individuals with urgent needs from those who can be treated by a primary care physician.

Preparing for an appointment and offering directions to a hospital are two examples of conversational AI in healthcare use cases. Conversational AI will provide patients with recommendations on what to wear, how long to fast before an appointment, and how to prepare for an exam.

Conclusion

Healthcare providers should effectively integrate AI solutions into workflows when deploying AI in the industry. In this manner, issues like latency when examining radiological images in the ER can be prevented. Clinicians won’t adopt AI technology if it makes their workflow more difficult, takes longer for them to implement, or requires them to go to another screen and add processes.

When developing AI in healthcare, the providers should involve doctors in the process. The greatest person to come up with a solution might be a doctor. Your solution won’t be the best if you don’t take the suggestions and knowledge of the doctor outlining the workflow.

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