AI in Healthcare: How it’s revolutionizing patient care

The rise of AI

The buzz around AI has been there for years, and if you still think its capabilities are limited to such virtual assistants as Siri and Alexa, you’re so mistaken. Well, we believe it’s impossible not to notice how AI has been transforming industries worldwide with a myriad of groundbreaking advancements. 

We bet there’s hardly anyone who hasn’t heard about AI so far. Even those who are not into technology so much have at least some basic understanding of that concept. There are numerous complex explanations guiding you through the amazing world of artificial intelligence, but we rather put it in layman’s words and make it short. 

So what’s AI about? AI technology allows computers to learn and make decisions for themselves so little to no human intervention is required.

Do we dare to say that AI will shape the future of most industries? Yes, we do! Though we don’t know for sure what the future holds for us, we’re sure it will be exciting! And while we’re waiting for the next revolutionizing breakthrough, let’s talk about those changing our life right here and now. 

Healthcare is among the industries affected by AI most of all. Keep on reading to find out how emerging technology creates new possibilities and pushes boundaries in the realm of medicine. 

How AI impacts healthcare

Healthcare has been upgraded a lot in recent years, particularly due to the incorporation of top-notch technology. It’s worth mentioning that such rapid innovations have led to longer life expectancies worldwide. However, the population ages so the patient’s needs and demands are growing as well. This is driven by various factors, including the implication of an aging population, increased chronic diseases, greater awareness of health and wellness, etc. This creates quite a number of challenges that healthcare providers must accept in order to deal with more complex needs effectively.

AI is the next game-changer that enhances healthcare with new and unique possibilities for predictive analytics, personalized medicine, and early disease detection or prevention. Additionally, AI has made drug development faster and more cost-effective. 

The future of healthcare is being shaped by technology. AI-powered technologies use ML algorithms in order to enable the processing of large chunks of data in real-time faster than ever before; it has the great potential to change patients’ lives by improving treatment considerably. 

Talking about the impact of AI in the healthcare sector in detail, we should highlight that the massive integration of AI into medicine started during the Covid-19 pandemic. The technology was leveraged by scientists for vaccine development acceleration, tracking the virus, and understanding individual and population risks. 

Artificial intelligence is constantly proving its usefulness in terms of improving the productivity and efficiency of care delivery, efficient resource management, operations streamlining, lowering the error rate, and reducing costs. 

We invite you to explore the ways of AI redefining healthcare delivery models fundamentally and figure out what it means for patients, doctors, nurses, and everyone involved in providing medical care. 

10 Ways AI Is Transforming Healthcare

The ultimate goal of AI in healthcare lies in improving patient outcomes through advanced treatment techniques. Such subtypes of AI as NLP and ML algorithms are widely applied to reach this goal. AI applications have already turned the healthcare sector upside down and the transformation is just gaining pace so the prospects of the technology seem promising enough.

The ways AI is applied in medicine are diverse and widespread, covering almost every aspect of care delivery. We’ve gathered 10 key AI applications you should know. Check them out right here!

Medical imaging

This process is focused on visualizing the body’s parts and organs in order to diagnose, monitor, or treat medical conditions. AI solutions make medical imaging as accurate as ever before. ML algorithms allow for accelerated analysis and therefore quicker diagnoses and treatment. At the same time, radiation exposure for patients is reduced. AI-driven advancements are being utilized in MRI, CT scans, X-rays, and so on.

The two basic examples of AI integration into medical imaging are radiology and diagnosis & treatment. AI algorithms are helpful for early and accurate disease detection as well as for better treatment, namely for assisting in planning surgical procedures. 

Despite all the benefits, it’s important to note that AI systems should always be used in conjunction with human expertise and should undergo rigorous validation and regulatory approval before clinical deployment.

Early diagnostics

AI-powered technology helps to identify diseases before they become severe. Machine learning algorithms process vast volumes of medical data to spot patterns in electronic health records (EHRs) and medical images such as X-rays or MRIs that may indicate early signs of diseases like cancer or Alzheimer’s disease.

Emerging symptom checkers (e.g. smart health assistants) powered by ML algorithms ask patients a series of questions about their health conditions and, based on their answers, provide recommendations on further actions. 

Now clinicians are making use of various tools to boost the diagnostic process. In fact, numerous surveys have shown that relying on these imaging tools leads to more accurate and quicker conclusions.

Personalized treatment

Highly personalized medicine is no longer a fantasy but a reality. This is achieved through the use of AI and ML. Data-driven models enable tailoring approaches as per each patient’s conditions and individual characteristics such as genetics, lifestyle, and medical history. Emerging technology integration results in disease risk prediction, suggesting personalized treatment options, better outcomes, and reduced costs.

Drug development & discovery

In 2023, healthcare services are expected to be high-quality, fast, and widely accessible. It is vital because it deals with a human’s well-being and life. 

Fortunately, the list of incurable diseases is gradually decreasing. Conditions that were critical a few years ago are now treatable. This is because of rapid progress in the medical field. 

The process of drug development has accelerated significantly in recent years, but the faster it is, the better. 

AI has the power to speed up drug development by reducing the time and cost needed for discovery. Researchers make use of AI-enabled tools for data-driven decision-making in order to figure out what compounds they should further explore. 

The discovery of new drug targets is now enhanced by AI as well. You may wonder how and here’s a simple explanation: via large datasets analyses. Moreover, the technology predicts drug efficacy as well as potential side effects, too. 

Predictive analytics

AI-powered predictive analytics is actively applied to identify upcoming patterns and trends that may be predictive of future events. Proactive planning and resource allocation are possible as well with AI. A combination of AI and predictive analytics provides data scientists with deeper insights into diverse factors affecting human health. 

Talking about each patient’s personal treatment, AI algorithms are involved to assess the risk of certain medical conditions based on individual health history, lifestyle habits, and genetic makeup.

Remote patient monitoring

Remote monitoring is a great advancement that has made medicine accessible to anyone regardless of location, age, or health condition. Keeping track of patients’ health state distantly is possible today. This means long travels are eliminated in most cases so patients get the required help immediately while saving time and expenses related to transportation. 

Telemedicine along with virtual care (assistants, chatbots, and more) is experiencing significant growth right now with a multitude of smart wearables, apps, etc. collecting and analyzing real-time health data. With this, clinicians can easier and quicker offer personalized feedback and recommendations, manage chronic conditions, and improve patient compliance from literally any location. By the way, this brings such a pleasant bonus as lower healthcare costs. 

Electronic Health Records (EHRs)

EHRs are essential for advanced healthcare services providing. It takes clinicians to deal with large volumes of medical data. Manual entry is quite time-consuming, isn’t it? Luckily, there’s AI that completely changes the situation. Record-keeping tasks are automated through ML algorithms thus letting doctors or other caregivers focus on direct care activities. 

Genome analysis

Medical services as well as medical research are increasingly powered by AI. Technology drives progress and provides us with a much deeper understanding of the human body and internal processes. 

Advancements in whole genome sequencing could not have happened if it wasn’t for AI and ML algorithms that can analyze lots of genomic data, identify patterns, and help us figure out the role of genetics in diseases. Genome sequencing data analysis is done with accelerated computing, data science, and AI that enable reading and understanding the genome. 

Patient engagement and adherence

AI has the potential to significantly improve patient engagement and adherence. 

A big percentage of patients find it difficult to adhere to treatment recommendations for a long time yet it’s crucial for positive outcomes. 

AI-powered tools such as wearables and personalized medical devices turned out to be helpful in keeping patients compliant so treatment plans do not fail. 

AI brings personalization that boosts patient engagement. In other words, patients receive timely notifications or alerts reminding them about taking medications, measuring vital signals, doing activities, or whatever. 

Administrative tasks optimization 

Automation is everything! As mentioned above, healthcare services are supposed to be delivered as quickly as possible. How can this goal be achieved? Automating tedious and routine tasks makes sense, therefore, upgrading administrative and operational workflow. Completing simple repetitive tasks manually takes a lot of time and leads to productivity losses. 

For example, clinical documentation tools powered by NLP help reduce the time spent on documentation and allow clinicians to pay more attention to delivering first-rate care. Scheduling appointments, managing patient records, processing insurance claims, and other administrative tasks are also easily automated these days. This way, better efficiency is reached.  

Groundbreaking benefits

If integrated appropriately, AI can significantly benefit the healthcare sector. While some skeptics worry about machines replacing human workers, we can say for sure that this is far from the truth. At least for now. 

When it comes to medicine, technology drives optimization, enhances numerous processes, and serves as a helpful assisting tool for clinicians. The probability that technology will replace doctors is presently very low. 

Explore the key advantages that AI brings to healthcare:

• More accurate diagnosis and higher treatment quality through data processing. Furthermore, machines can spot patterns in patient data that humans might miss. This eliminates errors and leads to better outcomes.
• Workflow optimization is achieved via administrative task automation. This gives healthcare specialists more time for direct patient care. 
• Clinical trials are taken to the next level. That means developing way more targeted therapies that are more likely to bring positive results in clinical trials.
• Better patient safety is a must-have. When it comes to healthcare, measures must be taken to reduce the risk of medical errors and critical and harmful events. 

How AI is challenging healthcare

Rewards are always achieved through conquering challenges, and this area is no exception. Moreover, as AI in healthcare is a relatively new topic, there’s still an extensive scope for study and investigation. And there are still lots of challenges to face!

We want to make your digital transformation journey as smooth and simple as possible so we rounded up a few main challenges that healthcare professionals face when integrating AI:

• Ensuring technology safety and effectiveness. Once again – AI has been there for a relatively short period of time so there are concerns related to its security. However, proper testing helps to check systems’ reliability and accuracy.
• Patient data privacy. AI and ML algorithms deal with vast amounts of personal data that must be strictly protected to avoid breaches or unauthorized access.
• Gender and racial algorithmic bias in AI. This issue is due to the fact that AI models and algorithms can only identify and recognize things or persons that they have been trained to detect. Developers should continue working on AI tools’ improvement to make them unbiased. 
• Regulatory and legal considerations. The regulatory landscape for AI in healthcare is still evolving. Ensuring compliance with existing regulations, such as those related to medical devices and data privacy, can be challenging. Developing appropriate frameworks and guidelines to address the unique aspects of AI in healthcare is necessary.
• AI integration into existing systems. Interoperability issues are very likely to come up. The main barriers include limited skills and resources, different software with varying data standards, and outdated legacy systems. 

As the realm of AI keeps evolving, we are likely to meet more new challenges in the upcoming years along with active AI integration into healthcare. But they won’t turn into serious issues as long as you’re aware of them and ready to accept them.

Addressing these challenges requires collaboration among healthcare professionals, researchers, policymakers, and developers to create guidelines, standards, and best practices for the responsible and effective implementation of AI in healthcare. And despite all these challenges, AI will undoubtedly lead to great breakthroughs in medicine.

Social impacts of AI

It’s clear that AI will proceed to impact the healthcare industry by addressing numerous issues, and social issues in particular. We want to highlight that AI integration isn’t limited to bringing cutting-edge technologies to hospitals. There’s much more to it. In fact, digital transformation has the potential to solve some critical social problems such as accessibility of high-quality medical services to unprivileged communities and patient engagement and education. 

AI-driven tools, such as health apps, wearables, and virtual assistants provide ongoing support, and this way empower patients’ adherence to their treatment plans. These technologies provide access to health information, facilitate self-monitoring, and encourage healthier behaviors. However, ensuring that patients understand and can effectively use these tools is essential to prevent the exacerbation of health disparities.

Advanced technology is capable of solving a multitude of problems and making our life easier. On the other hand, it can forge new trouble as well. Concerns about job displacement resulting from automation are rising increasingly. The integration of AI in healthcare may alter the roles and responsibilities of healthcare professionals. This shift may require reskilling and training of the healthcare workforce to adapt to the changing landscape.

Both positive and negative social impacts related to the integration of AI in healthcare must be taken into account to mitigate risks and ensure the changes are for the better.

AI in healthcare in numbers

• The global artificial intelligence in healthcare market size is expected to grow at a CAGR of 37% during the forecast period 2022 to 2030.
• Addressing numerous experts, the global AI in healthcare market value is predicted to reach $272.91 billion by 2030. 
• According to Forbes, 86% of healthcare providers, life science companies, and technology vendors make use of AI technology.
• The AI healthcare industry leaders are such companies as Arterys, Butterfly Network, Caption Health, Cleerly, Corti, CloudMedX, Enlitic, DeepMind, Komodo, Owkin, Oncora Medical, AiCure, Apixio, Nanox, and others. 

AI in healthcare: future prospects

The future is unpredictable yet very exciting! We don’t know what it holds for us but we can see the enormous potential of AI in healthcare. With sufficient investments in research and development, the technology will surely proceed to reshape the industry in the coming years. Despite all the concerns and challenges, machines revolutionize medicine in countless ways and bring an ever-expanding list of benefits. 

As emerging technology becomes widespread and more accessible, experts all over the globe anticipate the use of AI in healthcare to keep growing in the near future.

If utilized properly and efficiently, artificial intelligence has the power to significantly upgrade healthcare systems and improve patient outcomes at lower expenses. 

Is AI shaping the future of new digital medicine? It definitely is! So fasten your seat belts and get ready for more to come!