Artificial intelligence (AI) has reshaped many global industries over the past several years. Through algorithmic learning, AI has the power to isolate relevant data, identify patterns within, and generate comprehensive analyses with the aid of extensive computer knowledge.
In other words, AI is smarter than us.
More recently, AI has begun its integration into our healthcare, revolutionizing the medical field and shifting deep-held notions of what practicing medicine really means. While some may find the impact of AI in healthcare eerie, the truth is that AI benefits healthcare in a vast number of ways.
Use of artificial intelligence in public healthcare.
AI Supports Medical Imaging Analysis
Broadly, AI and its various branches—machine learning (ML), natural language processing (NLP), and deep learning (DL)—allow medical professionals and healthcare stakeholders to analyze large data patterns. These patterns, which can form from image data, medical claims, or clinical research trials, are complex and otherwise undetectable by manual human effort. But with the insight of AI algorithms, these patterns can be used to identify and resolve specific healthcare needs quickly and accurately.
Specifically, AI can review images and scans, providing radiologists and cardiologists with essential insight. This insight allows doctors to better prioritize cases, avoid potential errors, and establish more precise diagnoses.
AI Organizes Data
Many clinicians have a hard time keeping up with rapidly-changing medical advances on their own, mainly due to the enormous amount of medical data and health records that already exist. And especially in a large healthcare setting, medical data can come in all sorts of complicated, unstructured formatting. Organizing such disparate material is practically impossible.
But thanks to AI and machine learning, electronic health records (EHRs) and all other data can be quickly scanned, organized, and made ready to provide clinicians with quick and accurate answers whenever needed. Regardless of data format, AI can search for, collect, store, and standardize any medical data it receives.
AI Improves Medicine Development
Already, AI supercomputers are capable of analyzing databases of molecular structures to predict which medicines will or will not be effective for many different diseases. But AtomNet took things further by incorporating convolutional neural networks into the mix.
A technology closely related to the one that powers self-driving cars, convolutional neural networks have the capacity to analyze millions of experimental measurements and protein structures. This type of analysis can then be used to predict which molecules will bind to specific proteins. Notably, this AI method was used in 2015 to develop an effective treatment for the Ebola virus.
AI Can Predict Kidney Disease
Often difficult to detect by clinicians, acute kidney injury (AKI) is a life-threatening condition that can make patients deteriorate rapidly. Early detection and treatment is vital for these cases in order to reduce the need for long-term kidney dialysis. Fortunately, in 2019 DeepMind Health and the VA produced a ML tool with the power to predict more than 90% of AKI cases 48 hours earlier than doctors using traditional care methods.
Going forward, DeepMind Health hopes to make their ML tool user-friendly and available for installation in medical units so that clinicians everywhere can make quicker, more effective treatment decisions relating to kidney disease.
AI Supports Emergency Medical Staff
When it comes to heart attacks, time is critical. From the moment you call 911 to the moment the ambulance arrives, every second counts. It’s crucial that the emergency dispatcher who takes the 911 call recognizes the symptoms of cardiac arrest and facilitates appropriate urgency.
This is where AI comes in. With its ability to analyze both verbal and nonverbal cues, the AI tool Corti can recognize and evaluate a 911 caller’s voice, filter through any background noise, and cross-reference the patient’s medical history in order to determine the likeliness of a heart attack. The more Corti is used, the more it trains itself by listening to calls and identifying crucial factors.
AI Furthers Cancer Research and Treatment
Radiation therapy, the current treatment for cancer, is difficult and exhausting. And before most medical centers had a digital database to collect and organize EHRs, the process was even more of a challenge. But thanks to AI, Oncora Medical has created a platform able to juggle all the complex factors that go into cancer research and radiation treatment.
The platform is able to collect relevant medical data, evaluate quality of care, optimize treatments, and generate comprehensive oncology outcomes, imaging, and data. It does all this by automatically generating clinical notes, and then integrating them with EHRs. Overall, the AI tool not only saved time for clinicians by managing all documentation, but it improved health outcomes for patients.
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