How AI Has Impacted Healthcare Functionality

The movie I, Robot may have shown us how artificial intelligence (AI) can be beneficial and dangerous at the same time. When applied to the medical industry, overall, AI’s positive impact further outweigh the negatives.    

Up to 400,000 patients in the US die annually due to medical-related errors, according to researchers. Based on the same findings, these deaths could have been prevented if medical facilities used electronic sensors and artificial intelligence technology to monitor and treat the highly vulnerable individuals.  

This fact aside, the healthcare sector has benefitted immensely from the latest strides in technology, and it continues to work on various medical advancements to revolutionize the medical sector.   

What Does AI in Healthcare Mean?

In healthcare, AI doesn’t only mean robotics. Rather, AI application in the healthcare sector aims to create systems that improve the delivery of medical care, enhance diagnostic processes, streamline patient experience, and widen access to healthcare services. Artificial intelligence can likewise lessen the burden of healthcare practitioners, thus reducing medical errors that can lead to fatal mistakes.

Computer systems can now process incoming data and make conclusions based on solid algorithms. These machines can now guide medical practitioners, specifically doctors, to evaluate specific medical vulnerabilities, issue a more accurate diagnosis, and provide a targeted treatment.  

The Impact of AI in the Healthcare Industry

1. Increases Diagnostic Accuracy

Many medical errors could have been prevented with the correct diagnosis and a more efficient data gathering process. AI aims to make the process less laborious and more efficient by using medical case histories as basis for sounder diagnoses. For instance, a specific AI tool diagnosed breast cancer at a higher rate than 11 pathologists. This AI mammogram model can come up with a patient-specific diagnosis that predicts a person’s five-year vulnerability to breast cancer.

In Beijing, China, an AI tool is used to improve the interpretation of X-rays and CT scans, thus being able to detect questionable nodules and lesions in patients suffering from lung cancer. This rings the alarm in advance and allows for early diagnosis, cutting the time it takes for the doctor to send samples to the laboratory and waiting for the results.  

Stanford University researchers have created an AI algorithm that can identify and diagnose skin cancer. Using images of rashes, moles, and lesions, this technology may soon be available on smartphones as a mobile app.

Moreover, an AI system is being developed to provide ambient intelligence in what is foreseen as smart hospitals and homes, ultimately saving thousands of lives in the process.  

2. Helps Develop New Medicines

It takes billions of cash and lots of human hours to develop a specific drug, and only a tenth of these medicines are successfully released in the market. With AI, pharmaceutical companies are slowly recognizing AI’s contributions to providing accurate clinical findings.

For instance, an AI tool recently discovered that triclosan, an additive used in preventing bacterial contamination in personal products like soap and toothpaste, can help fight against parasites that cause malaria. 

3. Improves Hospital Experience

An article published in the Journal of Medical Practice Management in 2016 stated that a high number of hospital patients’ chief complaints are largely front desk-related, such as excessive waiting times, billing concerns, and impassive staff, although there were a few who complained of doctors being perpetually late or having poor manners. The survey was conducted by Vanguard Communications, a marketing and public relations firm for specialty medical practices.

There are attempts at using AI to improve patient experience by acting as a virtual healthcare assistant, assisting (human) hospital staff in processing data in a more efficient manner.  Overall, this is good news to healthcare professionals like nurses, who most often suffer a heavy workload.    

4. Makes Medical Data More Accessible

Missing medical records is one of the key reasons for misdiagnosis. By keeping data in a more organized manner, an AI tool makes sure there are no missing links to a patient’s data, leading to a better overview of medical history and reducing the risk of medical errors.

5. Assists in Surgeries

Some technologically-advanced hospitals are able to harness robots to help perform various surgical procedures. Robots mounted with cameras, mechanical arms and surgical instruments, allow doctors to have a clearer view of the surgical site and its surrounding areas, making surgeons’ work easier. With the help of robots, precision, flexibility, and control beyond human capabilities can be performed by doctors during complex procedures. 

Additional Examples of AI Use in the Medical Industry 

We’ve dropped some bits of concrete examples earlier, and here are additional samples:

• AI as voice to the voiceless: Is it possible to type with your eyes? Yes, if you use eye-tracking glasses that harness AI technology to help people who’ve lost the ability to speak to communicate once again. Through a brain-computer interface (BCI), a patient can connect through their eyes with a computer capable of voicing out their thoughts. This undoubtedly gives off Stephen Hawking vibes.
• AI as emotionally-sensitive robots: It’s quite hard to imagine a robot that’s emotionally expressive, as we’re used to seeing them with a stoic expression. But in 2017, a visually expressive robot named Milo was launched by Dell Technologies to teach students who have autism spectrum disorder to distinguish signs of emotion. Educational facilities in 27 US states currently use these robots.

Risks Associated with Using AI in Healthcare

1. Error-Causing Injuries

As with other systems, AI may not be perfect and could commit mistakes like humans do, and the consequences may be wider in scope or more serious than human error.    

For instance, it may inadvertently miss the abnormal growth in the CT scan or dispense and recommend a different kind of drug. And, because this is a system that’s interconnected with each other, other AI systems in another medical facility may likely suffer from the same mishaps.   

2. Error Caused by Data Availability Problems

AI systems need a large bulk of data from various sources such as fitness trackers, electronic health records, pharmacy records, insurance claims, etc. Unfortunately, no medical data is ever intact or comprehensive, mainly because patients tend to switch from one medical facility or medical specialist to another, and the systems they use may not be compatible. With not enough data, an AI may give out a wrong diagnosis.

3. Data Privacy Issues

There are strict confidentiality rules when it comes to handling (and releasing) patient data. And because AI developers need to collect medical data from patients, this could lead to potential breaches and lawsuits from patients who feel that medical facilities sharing information with a third party violates the law.

4. Can be Very Limited

AI learns from and processes data in which they are trained and exposed. If, for instance, the AI mainly gathers data from a medical center, it may not be able to effectively diagnose or recommend treatments to patients who have availed of the services for the first time.

Final Thoughts 

AI technology is currently being used in medical facilities and other venues in select countries. And, as experts continue to develop more advanced technologies in the healthcare sector, the public hopes that sooner more than later, these cutting-edge and life-saving services are made available to all.