The answer to the question “Will AI replace doctors?” has become a lot clearer amid the spread of the coronavirus. The pandemic gripped the whole world just a couple of months into 2020. As the number of infected citizens continues to rise, nations are facing shortages of beds, machines, and even healthcare professionals.
It has become apparent that doctors don’t have to worry about intelligent machines replacing them, at least for now. Instead, they should look into employing AI machines to help lighten their load. To prove the point, here are five areas in the healthcare sector where AI could make a huge difference.
1. Early Detection of Eye Diseases and Conditions
Joint research of the Moorfields Eye Hospital in London and Google’s DeepMind led to the development of an AI system that can identify 50 common eye conditions. The researchers fed the system with around 15,000 optical coherence tomography (OCT) or eye scans.
At the end of the trial, the AI system effectively detected eye problems such as diabetic eye disease and glaucoma. What’s impressive, though, is that the AI machine has an accuracy rate of 94.5%. So, if rolled out, the system could immensely help doctors prioritize patients with a more urgent need for treatment. The AI system can also recommend methods of treatment depending on the patient’s condition.
2. Improvement in Detecting Metastatic Breast Cancer
Yet another development made by Google is the Lymph Node Assistant (LYNA), which can quickly detect metastatic breast cancer by examining slide samples. Currently, pathologists spend so much time analyzing every detail of the slides, with patients waiting two to ten days for the results.
With LYNA’s deep learning algorithm, however, the time it took to read and analyze slides was only 116 seconds for unassisted mode and 61 seconds for assisted mode. Patients could get results within the day, and this could potentially make a difference in the outcome of the cancer treatment.
3. Quick Processing of Abnormal Chest X-Rays
AI can lessen the average time for abnormal chest X-rays to receive a radiologist’s opinion. Researchers at the University of Warwick developed an AI system that could read abnormalities in X-rays. Also, it could set a priority or urgency level in terms of how soon an expert radiologist needs to look at the result. The researchers used an anonymized dataset that contains half a million chest X-rays. They also employed the natural language processing (NLP) algorithm so the machine can read radiological reports.T
4. Timely and Accurate Mental Health Assessment
More than 750,000 people die due to suicide each year, according to the World Health Organization (WHO). AI could help bring this number down and make a remarkable difference in the lives of suicidal people. In fact, a recent study used machine learning (ML) methods and found that overdose suicide rates were underreported by about 33%. The accuracy at which this AI system can identify a suicidal person stands at 92.3% to 94.6%.
5. Accurate Evaluation and Diagnosis of Common Pediatric Diseases
A study went as far as claiming that the AI system they developed has an accuracy that is comparable to an experienced pediatrician in diagnosing common childhood illnesses. It can help determine if the stomachache a child complains about is appendicitis or gastroenteritis. Both diseases have different levels of urgency. The researchers extracted a total of 101.6 million key data points from more than 1.3 million patients using NLP and other deep learning techniques.
While AI won’t replace doctors, it could change so many aspects of the healthcare industry for the better. Patients would be better prioritized depending on the urgency of their sickness. Diagnoses would be more accurate and a lot quicker, which could significantly change the outcome of the patient. If developed correctly, AI systems could augment global healthcare status, and we could respond better to outbreaks.