Artificial intelligence and machine learning are empowering healthcare systems, clinics, hospitals to fast track their research efforts. Besides, AI is also playing a significant role in clinical trial recruitment, vaccine development, detection of life-threatening drug events, and more. Although the concept of AI in the healthcare sector is in its infancy, it is making a great impact already.

In this article, we will shed light on the state of AI in healthcare today. We will take a look at which AI-powered technologies are coming to the forefront, who are the primary end-users of AI applications, and more.

1. The rise of business intelligence and foundational AI technologies

Medical professionals and industry leaders are of the opinion that by the end of 2021, data integration, business intelligence, and NLP are a few technologies that are likely to cement their place in the healthcare industry.

In addition, hospitals and healthcare organizations are increasingly showing interest in data science platforms and data annotation tools. It is a clear indication that healthcare companies and organizations are leaning toward utilizing their data to provide better service and medical care.

2. Clinicians and patients – primary users of AI applications

We are seeing a new trend emerging wherein AI is gradually being used by clinicians and patients apart from data scientists and other tech experts. A recent survey suggests that clinicians are among the key target users of new AI technologies and tools.

Besides clinicians, even patients are one of the key end-users of AI technologies. This trend highlights the democratization of AI tech in the healthcare sphere and provides a greater understanding of the widening applications of AI in a clinical environment.

We predict that chatbots and other interactive automation platforms will become an integral part of patient care as AI matures. In many ways, it will allow patients to schedule appointments and follow up with doctors in a remote setting without any difficulties.

3. The increasing popularity of open-source software

It is safe to say that open-source and public cloud providers are the two most popular types of software to develop AI solutions in the healthcare sector. In recent years, open-source software solutions have emerged as a feasible and more viable alternative to cloud-based solutions.

One of the factors that are driving this trend is the increasing challenges linked with cloud-service adoption such as data security and privacy. Besides, using cloud services in healthcare could be a tricky affair as laws and regulations prevent service providers from sharing third-party data.

4. Companies are creating instead of buying

Companies with experience deploying models to production make the right choice to rely on their own data and monitoring tools rather than being dependent on traditional review or software vendor representation. Companies that are already researching AI, on the other hand, are more open to evaluation metrics provided by services providers. This makes sense from a legislative standpoint as well as to meet the unique needs of the very dynamic healthcare industry.

Different hospitals or insurance companies, for example, may choose to use different billing codes, medical terminology, or protocols, making it impossible to use off-the-shelf solutions. For all of those with the tools to retain their AI efforts in-house, using models adapted to one’s individual needs while still keeping data within the organization is a wise choice.

5. Electronic health records

Although this trend may not be directly tied with AI, it is very important due to its impact on other developments. Electronic Health Records are the digital records of a patient’s medical diagnosis, health journey, history across multiple years. In short, it is a digital account of your clinician’s notes.

Electronic health records are collected during patient visits and then migrated into a database that streamlines data. These records include all the important patient-related data such as progress notes, medications, medical history, laboratory data, and more.

Currently, there are different standards for record-keeping. However, the Fast Healthcare Interoperability Resources (FHIR) is the most adopted protocol by companies such as Apple and Google.

6. Telemedicine

Machine learning models are allowing companies to build cutting-edge solutions that enable patients to receive the best level of treatment in the comfort of their homes.

A lot of medical companies such as Babylon Health have rolled out AI chatbots that offer medical guidance to patients in the absence of a medical expert. These chatbots gather information from patients such as their current health issues, symptoms they are experiencing, and find the most relevant disease.

Another area of telemedicine that is gaining popularity is remote diagnoses that are delivered by real doctors. It is similar to a regular visit to your doctor’s clinic, but the only twist here is that the nurse or the doctor is remote.

While this concept was hard to imagine a few years ago, today, the scenario has transformed. The COVID-19 pandemic has accelerated the development of remote-medical technologies as doctors and patients were not able to come under the same roof.

AI in healthcare – Current challenges
Although AI in the healthcare sector is making great strides, there are considerable challenges. Before AI can infuse into the healthcare industry completely, we need to address the looming challenges.

First things first, AI-based technologies need to gain complete acceptance by medical experts and even patients. Besides, healthcare professionals need to be comfortable with the existence of tech systems that are driven by data.

Secondly, companies and every relevant stakeholder should ensure that they adopt the best practices for data privacy. They should use patient data by adhering to the regulations and ensure there is no security breach.

Moving ahead, the industry will largely benefit from a standardized method to incorporate AI into the different areas of healthcare. There is no doubt that healthcare is slowly becoming one of the key industries that will deploy AI to overcome and streamline challenges in the traditional healthcare processes and treatments.