AI in Healthcare: It’s Growth, Benefits and Use Cases
Artificial intelligence (AI) is becoming increasingly mainstream and proving to be more efficient and sophisticated in various fields, including healthcare. AI’s potential is huge. This is thanks to its rapid amalgamation into the healthcare ecosystem facilitated by the fast-paced advancement of tools and technology. The healthcare industry globally stands to reap immense benefits, including cost savings. In the US, for example, AI-powered applications are estimated to cut annual healthcare costs by $150 billion in 2026. The cost reductions come as a result of a health management model that lowers hospitalization rates, doctor appointments, and treatments.
The AI-driven healthcare market is also expanding, fueling the growth of AI-powered tools in this sector. A recent market report from Allied Market Research shows the AI healthcare market was worth $8.23 billion in 2020 and is estimated to reach $194.4 billion by 2030, a compound annual growth rate (CAGR) of 38.1% during the forecasted period. Therefore, let’s explore the benefits and use cases of AI. In the end, you’ll have a first grasp of the following:
- The role of AI in healthcare
- Different applications of AI in healthcare and use cases, such as:
- Early disease detection
- Accurate disease diagnosis
- Robotic disease management
- Drug research and development
- Precision medicine
- Concluding thoughts and how the future looks like for AI in healthcare
Role of AI in Healthcare
Artificial intelligence is gaining traction globally, and its application is becoming routine in organizations. In healthcare, it has a bigger success rate in disease diagnosis, treatment, research and development, among other key areas. Analyzing complex medical data is the heart of AI in healthcare, a process that typically begins with data labeling. Did you know that the healthcare industry generates about 30% of global data? As a result, healthcare data will experience a CAGR of 36% through 2025. Processing such an enormous amount of data and making sense of it requires the use of AI algorithms. AI algorithms are capable of sifting through data, discerning patterns and drawing conclusions. All which help scientists understand, diagnose and treat diseases.
To reiterate, AI trains computer systems to mimic human cognitive skills, combine data analytics, computer science, and math. AI in healthcare is doing exactly that in disease diagnosis, prediction, and research. So why do healthcare professionals need AI more than ever before? They need artificial intelligence to best understand new disease patterns, get accurate predictions, offer feedback, guidance, and support to patients and the industry.
Early Disease Detection
AI is transforming healthcare in a way that can save many lives. Healthcare professionals are using artificial intelligence tools to detect diseases, such as cancer in their early stages. Houston Methodist, for example, utilizes AI software to interpret patients’ mammograms. This helps doctors come up with an accurate and fast prediction of breast cancer risk. The software also translates patient charts into useful diagnostic information at 30x the speed of humans with 99% accuracy. In conclusion, these solutions help detect problems quickly, resulting in faster treatment decisions which saves lives.
Accurate Disease Diagnosis
Another way machine learning is revolutionizing healthcare is by improving and accurately diagnosing diseases. One example is IBM Watson Health. This digital tool reviews vast amounts of medical data from medical journals, disease symptoms, and treatment case studies. Another example is Google’s DeepMind Health. This team has partnered with healthcare professionals to solve complex healthcare problems through powerful AI research and mobile tools. More specifically, they build machine learning algorithms in the form of neural networks, mimicking the human brain.
Robotic Disease Management
Advances in technology and AI have introduced robots to the operating room to assist during surgeries. Robotic intelligence is proving to be more reliable with its speed and depth in making fine incisions during novel and complex surgeries. Today, surgeons can use surgical robots to position and manipulate surgical instruments as they focus on the complex aspects of the surgery. Surgical robots can identify key insights and cutting-edge practices by sifting through massive amounts of medical data. Asensus Surgical’s laparoscopic AI robot, for example, is giving surgeons helpful information like the size of the tissue, etc.
Drug Research and Development
Developing a drug begins with research, which is a long and costly process. According to the US Food and Drug Administration (FDA), drug approvals can take up to 12 years and the chance of a new drug making it to market is 1 in 5,000. As if that’s not enough, it costs an average of $359 million to develop and approve a single drug for human use. With such low odds in drug discovery, AI in healthcare is the ultimate antidote to this status quo. AI is streamlining drug discovery and repurposing the process, resulting in low drug discovery costs and a reasonable timespan.
AI in healthcare is synonymous with precision medicine, thanks to its disruptive technological innovation of advanced biotechnology, health sensors, and genome sequencing. AI’s advanced algorithms through deep learning is what makes precision medicine possible. In the US, for example, Scripps Research Institute developed a deep learning algorithm that successfully identifies 23 patients with a high risk of cardiovascular disease with 85 percent accuracy. In the end, physicians are seeking AI-powered solutions in precision medicine that have vast clinical knowledge on top of reasoning and analytical powers.
To sum up, there is a notable growth of the AI healthcare market, projected to reach $194.4 billion by 2030, at a CAGR of 38.1% between 2021 and 2030. These numbers point at the demand for AI-enabled advancements in medical technology. These powered solutions are revolutionizing the healthcare industry as well from disease diagnosis, treatment, to drug research and discovery. Having that in mind, humans continuously find creative solutions to everyday problems, also addressing healthcare challenges. The breakthroughs in the healthcare ecosystem through AI will continue to bring more intelligent solutions to the industry, resulting in fewer hospital visits, better patient care, and a healthy lifestyle, in general. Additionally, AI is also helping the healthcare recruiting industry by identifying and sourcing candidates, credentialing, eliminating bias, identifying patterns that help improve recruiting and more.
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