Top ten artificial intelligence application scenarios in the medical field

What is medical artificial intelligence?

Medical artificial intelligence refers to the application of artificial intelligence in medical services and medical service management or delivery. Machine learning, large unstructured data sets, advanced sensors, natural language processing and robotics are all being used in an increasing number of healthcare sectors.

In addition to its broad application prospects, artificial intelligence technology also brings significant potential problems-such as possible misuse from the centralization and digitization of patient data, and possible links to nanomedicine or universal biometric IDs . Fairness and bias have also been concerns in some early AI applications, but the technology may also be able to improve medical equity.

Although the deployment of artificial intelligence in healthcare is just beginning, it is becoming increasingly common. Research firm Gartner predicts that global healthcare IT spending will reach US$140 billion in 2021, and companies will list artificial intelligence and robotic process automation (RPA) as major expenditures.

In 2020, medical costs were close to 20) (19.7%) of the total U.S. economy (approximately $4.1 trillion). And fraud against governments is particularly serious.

Therefore, from administrative management to medical artificial intelligence, the potential value of medical artificial intelligence is huge.

Top 10 Application Scenarios of Artificial Intelligence in Healthcare in 2022

The following are 10 major areas where healthcare AI use cases are currently being developed and deployed.

(1) Medical management

Administrative expenses are estimated to account for 15% to 25% of the total medical expenses. Tools that improve and simplify administration are valuable to insurers, payers, and providers.

However, identifying and reducing fraud may provide the most immediate return because healthcare fraud can occur at many levels and be committed by various parties. In some of the worst cases, fraud can lead to insurance companies charging for services that were not performed, or to surgeons performing unnecessary surgeries in exchange for higher insurance benefits. Insurers may also pay more for defective equipment or testing kits.

Artificial Intelligence can be a useful tool in preventing fraud from occurring. Just as banks often use algorithms to detect unusual transactions, health insurance companies can do the same.

• McKinsey & Company research finds savings could be achieved through algorithm-driven “intelligent audits” of insurance claims.
• The U.S. government’s Centers for Medicare and Medicaid Services formed the Healthcare Fraud and Prevention Partnership to identify patterns in aggregate databases.

(2) Public health

Artificial intelligence has been applied to the entire public health sector. These include:

• Machine learning algorithms are being applied to large public health data sets, and the U.S. Centers for Disease Control and Prevention (CDC) has compiled many examples of artificial intelligence in analyzing the COVID-19 epidemic and its public health. Application method.
• Natural language processing is being applied in public health.
• More and more diagnostic imaging data are used for population analysis and prediction.
• Apply consumer data science and behavioral “push” technology to create “precision” or personalized pushes to promote medical visits, medical compliance, and more.

(3) Medical Research

• Finding new drugs to treat disease can be complex. Computer-aided drug design is a very complex field.
• In some cases, the goal is to repurpose existing drugs. In one recent example, artificial intelligence is analyzing images of cells to see which drugs are most effective in patients with neurodegenerative diseases. When responding positively to these treatments, neurons will change shape. However, conventional computers are too slow to detect these differences.
• Pharmaceutical supplier Bayer believes artificial intelligence can enhance clinical trials by using medical database information to create virtual control groups. They are also exploring other AI clinical trial applications to make these studies safer and more effective.

(4) Medical training

Artificial intelligence may also change the way medical students receive parts of their education. These include the following:

• In one example, an AI tutor provided assistance to medical students as they learned to remove brain tumors. The system uses machine learning algorithms to teach students safe and effective techniques and then evaluates their performance. People who use AI systems learn skills 2.6 times faster and perform 36% better than those who don’t.
• Healthcare organizations in the US and UK have also deployed AI-based patient services to facilitate virtual and remote training. This approach is particularly useful when the COVID-19 pandemic inhibits group gatherings. Artificial intelligence supports the practice of a variety of skills, such as comforting a distressed patient or delivering a message.

(5) Medical Professional Support

Artificial intelligence is also used to support medical professionals in clinical settings, including:

• Artificial intelligence should be used to support medical facilities in recruiting professionals. A pilot project at Stanford University uses algorithms to determine whether a patient is at high enough risk to require ICU care, or experiences a code-related event, or needs a rapid response team. They assess the likelihood of these events within six to 18 hours, helping doctors make more confident decisions.
• AI-based applications are being developed to support nurses, providing decision support, sensors to inform them of patient needs, and robotic assistance in challenging or dangerous situations in the field.

(6) Provide direct support to patients

Artificial intelligence is also used to provide direct support to patients:

• Hospitals use artificial intelligence chatbots Check in with patients to help them get necessary information faster. When the Northwell Health artificial intelligence system chatted with patients, the engagement rate among patients using oncology services was 94%. Clinicians who have tried the tool agree that it extends the care they provide. Chatbots can check in on patients’ symptoms, recovery, and more. Many people are accustomed to text messaging, which improves patient acceptance. Chatbots also reduce the challenges patients may face when seeking care. People can use them to find a hospital or clinic, make an appointment and describe their needs.
• It is estimated that as many as half of patients do not take their medications as prescribed. However, artificial intelligence can increase the chances of patients taking their medications on time. Some platforms use smart algorithms to recommend when medical professionals should communicate with patients about compliance issues, and through what channels. There are even medication reminder chatbots. In one recent example, researchers collaborated and used artificial intelligence to help find the best drugs for people with type 2 diabetes. These algorithms helped more than 83% of patients choose the right treatment, even when patients were taking multiple medications at the same time.

(7) Telemedicine

Telemedicine in the form of virtual doctor visits has become increasingly common since the COVID-19 pandemic resulted in travel restrictions. Beyond this, AI supports other forms of telemedicine, including:

• VirtuSense app predicts AI-powered remote monitoring and alerts providers of high-risk changes that could lead to patient falls.
• Some facilities currently using artificial intelligence for monitoring rely on it to detect everything from heart disease to diabetes. Hospitals are also using the technology to monitor COVID-19 patients, making it easier to decide which patients can receive home care and which need hospitalization.

(8) Diagnosis

Artificial intelligence is also used for diagnosis in health care centers, including:

• An artificial intelligence system for detecting breast cancer Smart systems can detect current problems and the likelihood that a patient will develop the disease in the next few years.
• Some applications of artificial intelligence in healthcare can also detect mental illness. Researchers used algorithms trained to identify people with depression by listening to their voices or scanning their social media messages.

(9) Surgery

Artificial intelligence will not eliminate surgical problems, but it has the potential to reduce them while improving outcomes for patients and surgeons. The following example illustrates this:

• A startup called theater recently raised $39.5 million in Series A funding. The company has an AI video solution designed to help surgeons understand what is going wrong and what is going right during surgery. They can then study these videos and make improvements in the future.
• Applications of artificial intelligence in healthcare include surgical robots, which are increasingly common in operating rooms. Many are minimally invasive and often achieve better results than non-robotic interventions. These applications of artificial intelligence will not replace human surgical expertise. However, they can serve as a companion to the surgeon, increasing the likelihood of successful surgery.

(10) Hospital Care

In addition to the diagnostic use cases described above, clinicians must also meet patient care needs and stock medical supplies and deliver goods. Artificial intelligence-powered collaborative robots are starting to ease this burden. According to Gartner, 50% of U.S. suppliers will invest in robotic process automation by 2023. Some examples of robotic process automation in hospitals include:

• One hospital recently deployed five robots called Moxie. The machines will proactively determine when nurses need supplies or assist with lab testing logistics. They then respond before the provider's workload becomes too intensive.

The robots provided by Atheon not only support medical functions, but can also complete tasks such as weeding and garbage removal.

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