Top 10 AI application scenarios in the medical field

Top 10 AI application scenarios in the medical field. 해시게임

What is Medical AI?

Healthcare AI refers to the application of artificial intelligence in healthcare services and the management or delivery of healthcare services.

Machine learning, unstructured large datasets, advanced sensors, natural language processing, and robotics are all being used in an increasing number of healthcare sectors.

In addition to broad application prospects, artificial intelligence technology also brings significant potential problems.

such as may arise from the centralization and digital misuse of patient data,

And possibly a link to nanomedicine or universal biometric ID.

In some early AI applications, fairness and bias were also concerns,

But the technology may also improve medical equity.

Although the deployment of AI in healthcare is just beginning,

But it is becoming more common. The research firm predicts that global healthcare IT spending will reach $140 billion in 2021,

Businesses cite artificial intelligence and robotic process automation (RPA) as major spending.

In 2020, healthcare costs are close to 20) (19.7%) of the U.S. economy (approximately $4.1 trillion).

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

Top 10 application scenarios of AI in healthcare in 2022

Below are 10 major areas where AI use cases for healthcare are currently being developed and deployed.

(1) Medical management

Administrative expenses are estimated to be 15% to 25% of total medical expenses.

Tools to improve and simplify administration are valuable to insurers, payers, and providers.

However, identifying and reducing fraud may offer the most immediate payoff,

as healthcare fraud can occur on many levels and be perpetrated by various parties.

In some worst-case scenarios, fraud can result in insurance companies charging for services not provided,

Or cause surgeons to perform unnecessary surgeries to pay higher insurance benefits.

Insurance companies may also pay more for defective equipment or testing kits.

AI can be a useful tool in preventing fraud from happening.

Just as banks typically use algorithms to detect unusual transactions,

Health insurance companies can do the same.

McKinsey & Company research has found savings through algorithm-driven “smart auditing” of insurance claims.

(2) Public health

AI is already being used across the public health sector.

These include: Machine learning algorithms are being applied to large public health datasets, and the Centers for Disease Control and Prevention (CDC) has compiled many ways in which artificial intelligence can be applied to analyze the COVID-19 outbreak and its public health.

Natural language processing is being used in public health.

More and more diagnostic imaging data are used for population analysis and prediction.

Apply consumer data science and behavioral “push” technologies to create “precise” or personalized pushes to facilitate medical visits, medical compliance, and more.

(3) Medical Research

Finding new drugs to treat diseases can be complicated.

And computer-aided drug design is a very complex field.

In some cases, the goal is to repurpose existing drugs.

In a recent example, artificial intelligence analyzes images of cells to see which drugs are most effective for patients with neurodegenerative diseases.

When there is a positive response to these treatments, the neurons will change shape.

However, traditional computers are too slow to detect these differences.

Pharmaceutical supplier Bayer AG believes that 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 efficient.

(4) Medical training

AI could also change the way medical students receive part of their education.

These include the following: In one example, an AI tutor helped medical students as they were learning to remove a brain tumor.

The system uses machine learning algorithms to teach students safe and effective techniques and then evaluates their learning performance.

People with AI systems learned skills 2.6 times faster and learned 36% better than those without AI.

Healthcare facilities in the US and UK have also deployed AI-based patient services to facilitate virtual and remote training.

This approach is especially useful when the Covid-19 pandemic inhibits group gatherings.

AI supports the practice of multiple skills, such as comforting distressed patients or delivering messages.

(5) Medical professional support

AI is also used to support medical professionals in clinical settings,

These include: Artificial intelligence applied to support the admission of professionals in medical facilities.

A pilot project at the university uses algorithms to determine whether a patient is at risk high enough to require ICU care, experiencing a code-related event, or requires a rapid response team.

They assess the likelihood of these events occurring within six to 18 hours, helping doctors make more confident decisions.

AI-based applications are being developed to support nurses,

provide decision support, sensors inform them of patient needs,

As well as providing robotic assistance in challenging or dangerous situations in the field.

(6) Provide direct support to patients

AI is also being used to provide direct support to patients:

Hospitals use AI chatbots to check in with patients, helping them get necessary information faster.

When the AI ​​system chatted with patients, the engagement rate for patients using oncology services was 94 percent.

Clinicians who tried the tool agreed that it extended the care they provided.

Chatbots are able to check patients’ symptoms, recovery, and more.

Many people are accustomed to using text messages to chat, which increases patient acceptance.

Chatbots also reduce the challenges patients may face when seeking treatment.

People can use them to find hospitals or clinics, make appointments and describe needs.

It is estimated that as many as half of patients do not take their medicines as prescribed.

However, AI can increase the chances of patients taking their medicines on time.

Some platforms use intelligent algorithms to advise medical professionals when and through what channels to communicate with patients about adherence.

There are even medication reminder chatbots.

In a recent example, researchers collaborated and used artificial intelligence to help find the best medicines for people with type 2 diabetes.

These algorithms helped more than 83% of patients choose the correct treatment plan,

This is true even when the patient needs to take multiple medications at the same time.

(7) Telemedicine

Telemedicine in the form of virtual doctor visits has become more common since the COVID-19 pandemic led to travel restrictions.

In addition to this, AI also supports other forms of telemedicine,

These include: Applying predictive artificial intelligence to remotely monitor and alert providers of high-risk changes that could lead to patient falls.

Some facilities currently using AI for surveillance rely on it to detect everything from heart disease to diabetes.

Hospitals are also using the technology to monitor Covid-19 patients,

This makes it easier to decide which patients can receive home care and which require hospitalization.

(8) Diagnosis

AI is also used in diagnostics in healthcare centers,

Among them: An artificial intelligence system for breast cancer detection can detect current problems and the likelihood that patients will develop the disease in the next few years.

Some applications of AI in healthcare could also detect mental illness.

The researchers used the trained algorithm,

Identify people with depression by listening to them or scanning their social media feeds.

(9) Surgery

AI won’t eliminate surgical problems, but it has the potential to reduce them,

Improve patient and surgeon outcomes at the same time.

The following example illustrates this: A startup recently raised $39.5 million in Series A funding.

The company has an AI-powered video solution designed to help surgeons understand what went wrong and what went right during surgery.

They can then study these videos and make improvements in the future.

Applications of AI 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 AI will not replace human surgical expertise.

However, they can act as a partner to the surgeon, increasing the likelihood of successful surgery.

(10) Hospital Nursing Top 10 AI application scenarios in the medical field

In addition to the diagnostic use cases described above, clinicians must also meet patient care needs, as well as stock medical supplies and deliver goods. Top 10 AI application scenarios in the medical field.

AI-powered collaborative robots are starting to ease that burden.

By 2023, 50% of U.S. suppliers are expected to invest in robotic process automation.

Some examples of robotic process automation in hospitals include: A hospital recently deployed five robots.

These 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.

Robots not only support medical functions but also perform tasks such as weeding and trash removal.