6 Applications of AI in Healthcare

Artificial intelligence (AI) is being used for a variety of healthcare purposes, including disease detection, drug discovery, delivery of health services, and management of chronic conditions. Learn more now.

The impact of artificial intelligence (AI) on healthcare is staggering. According to Forbes, the market value of AI in healthcare is projected to reach $6.6 billion by 2021. It’s driving innovations in disease detection, drug discovery, delivery of health services, and management of chronic conditions.

Here are six ways AI is reshaping healthcare now, and for the future.

Virtual assistants

The global healthcare virtual assistant market is expected to reach $1.76 billion by 2025.

According to research by the American College of Physicians, primary care doctors spend up to 50 percent of their day completing administrative tasks. Virtual assistants are AI-based systems that interact with humans to perform various tasks.

In the healthcare industry, virtual assistants are used in transforming various health processes to improve healthcare delivery. Virtual assistants can converse, ask and answer questions, gather and assess vital signs, monitor a patient’s responses, and take note of improvement or decline. Likewise, they can call to check on you, make sure you’re taking your prescribed medication, and sense changes that require clinical attention.

Hiring a VA can handle all the tasks that may be overburdening your staff, not only that will make their lives easier but will save you money too.

Robotic-assisted therapy

Artificial intelligence is also being applied to surgical robotics. Surgeons must always be precise when performing surgical tasks like incisions. These tasks are not only challenging but repetitive as well, so to assist them, they are using collaborative robots.

AI can determine patterns within surgical procedures to improve best practices and to improve surgical robots’ accuracy. Surgical robots can control the depth, trajectory, and speed of their movements with great precision. They’re especially well-suited for operations that require the same, repetitive movements as they’re able to work without fatigue. Collaborative robots eliminate the risk of hand tremors and unintended or accidental movements.

Drug discovery

Close to 50 percent of late-stage clinical trials fail due to ineffective targets, resulting in only 15 percent of drugs moving from Phase 2 to approval. A survey conducted by BenchSci, a startup in Toronto that provides machine-learning tools to scientists, found that 41 percent of the 330 drug-discovery researchers were unfamiliar with the uses of AI.

Meanwhile, researchers at Boston biotechnology company Berg have come up with a platform to unearth previously unknown cancer mechanisms. They did this by conducting tests on more than 1,000 cancerous and healthy human cells. They used an AI platform to create biological and outcomes data from patients to highlight key distinctions between diseased and healthy cells.

By using AI, the team was able to identify the role of certain naturally-occurring molecules in cancer metabolism. This led to them discovering how a new drug works. The drug, BPM31510, is now in Phase 2 of its clinical trials, testing it to people diagnosed with advanced pancreatic cancer. The company is also using the same AI system to look for drug targets for other conditions, like Parkinson’s disease and diabetes.

Digital consultations

Digital health consultation tools have progressed in popularity, thanks to smartphones and people’s need for 24/7 accessible healthcare. Multiple applications have been developed so patients can consult the doctor online, check for symptoms, monitor their health, and get advice. AI is being used through smartphone applications as a way to identify, detect, and treat health concerns from a distance.

Health monitoring

According to Frost & Sullivan, patient monitoring is increasing its capacities by great margins with predictive analytics, maturation of sensors, and artificial intelligence. They said that the ability of these innovations to assess patients at the moment and point toward their possible future condition had multiple healthcare systems investing more than $566 million.

For example, wearables and embedded biosensors, like glucose monitors, blood pressure monitors, and ECG monitors help in managing chronic conditions and population health, both in and out of the hospital.

Meanwhile, digital pills and nanorobots help monitor medication adherence. Advanced materials and smart fabrics are opening new frontiers in cardiac monitoring. Lastly, brain-computer interfaces allow direct monitoring and analysis of key health metrics to assess patients’ emotional, psychological, and cognitive state.

EHRs

According to a study by the American Medical Association (AMA), physicians typically spend nearly six hours a day on EHR. They devote time to medical practice management tasks, like clinical documentation, billing, coding, order entry, inbox management, and security procedures. To address this, Google came up with “Suki,” an AI assistant that uses voice technology. Only a year after its launch, Suki had been adopted across many clinics and hospitals. It works to accurately improve the retrieval of medical information from EHRs into Google’s advanced AI and machine learning systems.

It can lower the average time a physician spends time writing notes on EHRs from more than 13 minutes to just three minutes.

AI technology contributes significant value to the healthcare industry, from diagnoses to treatments. Everybody should expect that AI will continue to reshape the industry over the next several years.