5 Real-World Applications of AI in Medicine
Artificial intelligence (AI) has been a much-hyped topic in the world of technology recently. If you know how powerful and important AI is, it’s no wonder it’s attracting so much attention and intrigue. We all know all the amazing things AI has done for cybersecurity, but do you ever think about its impact on our healthcare? Many world-renowned engineers, data scientists, developers, and doctors are working together to build AI-dependent systems and gadgets that will better and improve the medicine world. Spoiler alert – they are very much succeeding. So, let’s talk about some of the most promising real-world applications of AI in Medicine today!
AI: The Hero of Clinical Judgment and Disease Diagnosis
There is no successful treatment without a correct diagnosis. However, it’s not always easy to get it right. Fortunately, the appliance of AI in the diagnostic process proved to be extremely beneficial. Doctors are using AI-based software that is designed to identify whether a patient has a certain disease before recognizable symptoms show.
The question is – how do these programs work? They use Machine Learning (ML), specifically Deep Learning algorithms, that can help with automatic disease diagnosing by reading digitalized data. This digitalized data represents millions of examples of different diseases, their progress, treatments, etc. Therefore, with the help of AI, the diagnostic process is much faster and easier. Now, let’s see in which areas of medicine is this applied!
AI-Based Cancer Detection Solutions
AI plays a huge role in detecting brain tumors and breast and lung cancer by reading the CT scans. Believe it or not, there are more interesting and innovative strategies used for this purpose. For example, Freenome detects cancer in its early stages using molecular biology and ML. The model can be trained to recognize which biomarker patterns indicate the stage, type, and most successful therapy methods for certain cancer. AI can aid in the decoding of hidden patterns, eventually leading to the recognition of disease-related patterns.
Additionally, researchers at Stanford University used an AI algorithm to detect skin cancer – more precisely, they used it to classify skin lesions in skin images. They then compared it to a dermatologist’s work and got amazing results – the performance of this AI-based algorithm was on a human level and it was very successful!
Prevention of Diabetic Retinopathy
Another amazing real-world application of AI in medicine is the detection and prevention of Diabetic retinopathy. Diabetic retinopathy (DR) is an eye condition that affects diabetics. It’s the leading cause of blindness globally, with approximately 415 million people with diabetes at risk. It can be treated if it’s diagnosed at the early stages, but if it’s not it can cause irreversible blindness. Fortunately, a Google research team has developed a Deep Learning algorithm that can detect symptoms of DR in retinal photographs. This automated, high-accuracy screening technology has the potential to help doctors evaluate more patients and rapidly refer those who require assistance to a specialist.
Detecting Asthma Attacks Faster Than Ever
Besides cancer and diabetic treatments, AI also found its way to help those who suffer from asthma. Propeller Health is another effective AI system that can identify asthma attacks based on patient prescription data and environmental factors. It monitors every dosage the patient takes and learns about his asthma. Propeller makes tracking, understanding, and managing asthma simple. Additionally, this system allows you to observe how your triggers and symptoms change over time.
AI & Drug Development – The Collab We All Need
Drug development is a time-consuming and extremely expensive process. That’s why more and more medical and pharmaceutical companies are relying on AI in order to reduce R&D costs and errors that can be very pricey. The good news is artificial intelligence has a great impact on all stages of drug development, especially in those that include analytical processing.
For example, in the second stage of this complex process – discovering the drug candidates – ML algorithms play a big role by learning to anticipate the appropriateness of a molecule based on structural fingerprints and chemical characteristics. Then they sort through millions of possible molecules to identify the best ones — those with the fewest negative effects.
Medicine has been introduced to deep learning models that are based on attention mechanisms and graph neural networks, which help identify drug combinations and speed up the process of getting a drug approved. As Andrea Deac explained, thanks to graph neural networks that were used for drug combinations, there have been significant improvements in the drug development pipeline. It has improved the pre-pre-clinical research and shortened the entire process of getting a new medicine approved for years.
Another great AI-supported invention in the world of pharmacy is the PillCam. The PillCam is a little plastic capsule that looks like a big vitamin or fish oil tablet. It has a small camera and light inside that allows it to take color close-ups of your digestive tract, particularly the small intestine. It also features an antenna for transmitting pictures to a wireless recorder on a sensor belt that patients need to wear. On a 12-hour tour through your insides, the latest version of the PillCam takes two to six frames per second or more than 50,000 pictures.
Despite the fact that it can photograph the whole digestive tract, the PillCam’s primary purpose is to discover abnormalities in the small bowel, which can be difficult to reach with standard endoscopy or colonoscopy. It’s very good at detecting hidden bleeding, anemia, and lesions as tiny as 0.07 mm.
Virtual Nursing Assistant – Beneficial for Both Patients and the Doctors
Everybody knows how exhausting and time-consuming hospital visits can be. We would all like to avoid them as much as possible, right? Well, Junaid Kalia thinks Virtual Nursing Assistant seems like a great solution. The best thing about VNA is it’s available 24/7, so it’s constantly monitoring its patients and giving feedback whenever there is even
the slightest change. This kind of AI-powered assistance is personalized, so every patient can tailor it to their specific needs. It can aid in the diagnosis of disease based on symptoms, the monitoring of health status, and the scheduling of doctor’s visits. Additionally, it has the ability to keep any chronic condition from worsening. This is especially good for older patients who commute to the hospital often – they are taken care of 24/7 and from the comfort of their homes!
Real-World Applications of AI in Medicine: Making the World a Better Place
Ai is definitely making our world a better place, especially when it comes to medicine. As you can see, all these AI-based algorithms and programs are improving the whole healthcare industry – from hospital visits to detecting and preventing life-threatening diseases. With technology developing at a rapid pace, just imagine where AI will be in the forthcoming decade. It seems everything’s possible!