How is artificial intelligence used in the medical field

techmanga June 27, 2021 0 Comments



How Can Artificial Intelligence Help Healthcare?


Throughout the years we’ve been watching AI percolate throughout a diverserange of industries, from fintech and AI-powered investment banking to smartfarming technologies. As we noted in our earlier articles on trends inartificial intelligence, healthcare is where machine learning and deeplearning will pave the way to a new era of better drugs and smarter healthcaremanagement.Machines are becoming as good as humans in their ability to interpret medicalimages. About 40% of healthcare providers reportedly use some form of AI-powered, computer-assisted diagnostics like chatbots or apps that offerpersonalized health advice based on a patient’s data, biometric inputs fromwearables, or the rich datasets contained in today’s electronic healthcarerecords (EHRs).While the investment opportunity for artificial intelligence has largelybelonged to venture capitalists up until now, the rapid growth of AI-poweredhealthcare solutions means retail investors can now build an investmentstrategy around this emerging technology. Forget IBM and Dr. Watson – we’retalking about real pure-play investments in AI healthcare companies.

The AI Healthcare Investment Thesis


With more than 3,000 “AI startups” around the globe focused on using machinelearning, deep learning, and other AI technologies to solve problems,investment opportunities have been limited to a handful of computer visionstocks, a few pick-and-shovel investments in AI chips, and a handful ofcompanies that provide AI-powered solutions to healthcare organizations. Onereason that the healthcare industry gets so much attention is because of itssize.In 2018, the global healthcare market reached a value of $8.5 trillion, with$3.65 trillion spent in the United States alone. There are very few trillion-dollar industries out there. If you’re able to capture even the tiniestpercentage of that number, you can easily have a billion-dollar business.There are also the feel-good aspects around investments that help democratizehealth care, improve the quality of life, and help save lives. Healthierpeople live longer, so more healthcare resources will be required to take careof tomorrow’s elderly. In the long run, investors can do well by doing good.

How Will Artificial Intelligence in Healthcare Transform Clinical


Experiences?Healthcare is one of the top industries impacted by artificial intelligencefor other reasons as well. The global healthcare sector is not only massivebut it’s also complex, full of inefficiencies, and has loads of patient datareadily available in shoddy form. Imagine what AI systems can achieve in asector where old-school data warehousing still hasn’t been mastered. Add tothat the hefty price tag associated with anything medical (in the US theaverage hospital stay costs $10,700 and the average doctor earns $294,000 ayear) and even tiny incremental efficiencies will make a huge difference tothe bottom line. Among the many potential benefits, AI applications promise toimprove patient outcomes, shorten drug development and clinical trials, andempower preventive and precision medicine. Besides the feel-good aspects ofdemocratizing health care, the resulting efficiency gains are translated intohard dollars for investors in AI healthcare companies.

Medical Imaging and Diagnostics


One of the area of healthcare that’s quietly being transformed by AI ismedical imaging. Deep learning algorithms can interpret medical images betterthan humans now. All imaging technologies stand to be improved – X-rays,ultrasounds, MRIs, and other types of scans – by AI algorithms that can offera diagnosis or even prognosis. It was wishful thinking that a behemoth likeIBM would dominate in this emerging market. It’s really the startups that arethe future of medical imaging, particularly in oncology, where AI is becomingat least as good doctors in spotting tumors.A startup called Tempus is using deep learning techniques to predict whichtumors might respond favorably to immunotherapy treatment – Credit: TempusMedical imaging has become such a large market that startups are now carvingout niches for themselves. Some use machine learning to sharpen images, oremploy natural language processing to extract information from health recordsfor more precise diagnostics. Others focus on medical imaging big data forresearch purposes. A startup called Vara Healthcare provides an end-to-endworkflow that starts from when a medical image is taken and ends when adiagnosis has been made. Another company called MaxQ is looking to gaincompetitive advantage by partnering with industry giants like IBM Watson andGE Healthcare. (We were surprised to see MaxQ pull its IPO filing in June2019. The company remained in private hands since then.) We’ve covered atleast 26 companies with FDA-approved AI algorithms, five of which we highlightin our piece on 5 Small Global Stocks With FDA Approved AI Algorithms.Medical imaging became one of the largest markets for AI healthcare use cases,but other diagnostic applications are also catching up. A number of AIstartups are working on solutions for blood testing, urinalysis, and big dataalgorithms for early detection of diseases. Retail investors will want tocheck a promising pure-play stock in this space, Renalytix AI.

Big Data Analytics


It’s no secret that an AI algorithm is only as good as the data you feed it.In the last few years, plenty of companies have come along that applyartificial intelligence to the trove of digitized data that has been created.These data science companies are able to provide insights into everything fromfinancing and trading to selling more sodas. In industries that haven’t seen alot of operational innovation over the years, like healthcare, there’s lots oflow-hanging fruit for healthcare data analytics companies. Big data pairedwith AI can help shrink down the size of medical devices or power apps thathelp manage our healthcare. Some companies offer enterprise systems withlearning algorithms that ingest millions of data points to enable value-basedcare, a system that rewards healthcare providers based on outcomes rather thansheer volume under the old fee-based paradigm. Other companies combine bigdata algorithms with sensors to allow patient monitoring inside hospitals orhelp keep track of patients’ progress remotely.Credit: University of Illinois at Chicago

What is Artificial Intelligence in Healthcare?


Artificial intelligence in healthcare refers to the use of complex algorithmsdesigned to perform certain tasks in an automated fashion. When researchers,doctors and scientists inject data into computers, the newly built algorithmscan review, interpret and even suggest solutions to complex medical problems.Applications of Artificial Intelligence in healthcare are endless. That muchwe know.We also know that we’ve only scratched the surface of what AI can do forhealthcare. Which is both amazing and frightening at the same time.At the highest level, here are some of the current technological applicationsof AI in healthcare you should know about (some will be explored further inthe article while some use cases have gotten their own standalone articles onHealthcareWeekly already).Medical diagnostics: the use of Artificial Intelligence to diagnose patientswith specific diseases. Check out our roundup report from industry expertshere. Also, a report AI platform was announced in March 2019 which is expectedto help identify and anticipate cancer development.Drug discovery: There are dozens of health and pharma companies currentlyleveraging Artificial Intelligence to help with drug discovery and improve thelengthy timelines and processes tied to discovering and taking drugs all theway to market. If this is something you’re interested in, check our reporttitled Pharma Industry in the Age of Artificial Intelligence: The Future isBright.Clinical Trials: Clinical Trials are, unfortunately, a real mess. Mostclinical trials are managed offline with no integrated solutions that cantrack progress, data gathering and drug tria outcomes. Read about howArtificial Intelligence is reshaping clinical trials here. Also, you may alsobe interested in the Healthcare Weekly podcast episode with Robert Chu, CEO @Embleema where we talk about how Embleema is using AI and blockchain torevolutionize clinical trials. If Blockchain in healthcare is your thing, youmay also be interested in our Global “Blockchain in Healthcare” Report: the2019 ultimate guide for every executive.Pain management: This is still an emergent focus area in healthcare. As itturns out, by leveraging virtual reality combined with artificialintelligence, we can create simulated realities that can distract patientsfrom the current source of their pain and even help with the opioid crisis.You can read more about how this works here. Another great example of where AIand VR meet is the Johnson and Johnson Reality Program which we’ve covered atlength here. In short, J&J has created a simulated environment which usedrules-based algorithms to train physicians in a simulated environment to getbetter at their job.Improving patient outcomes: Patients outcomes can be improved through a widevariety of strategies and outcomes driven by artificial intelligence. To beginwith, check our report on 10 ways Amazon’s Alexa is revolutionizing healthcareand our Healthcare Weekly Podcast with Helpsy’s CEO Sangeeta Agarwal. Helpsyhas developed the first Artificial Intelligence nurse in the form of a chatbotwhich assists patients at every stage of the way in their battle with cancer.These are just a few examples – and they’re only meant to quickly give you aflavor of what artificial intelligence in healthcare is all about. Let’s diginto more specific examples that every healthcare executive should be aware ofin 2019.

How is artificial intelligence used in the medical field?


Artificial intelligence in the medical field relies on the analysis andinterpretation of huge amounts of data sets in order to help doctors makebetter decisions, manage patient data information effectively, createpersonalized medicine plans from complex data sets and discover new drugs.Let’s look at each of these amazing use-cases in more details.

AI in healthcare market growth


Growth opportunities may be hard to come by without significant investmentfrom companies, but a major opportunity exists in the self-running engine forgrowth within the artificial intelligence sector of healthcare.AI applications within the healthcare industry have the potential to create$150 billion in savings annually for the United States, a recent Accenturestudy estimates, by 2026. With AI in healthcare funding reading historic highsof $600m in equity funding (Q2’18) there are huge projected equity fundingdeals and equity deals as the years continue.“We always overestimate the change that will occur in the next two years andunderestimate the change that will occur in the next 10” – Bill GatesSaliently, AI represents a significant opportunity for bottom line growth withthe introduction of AI into the healthcare sector, with a combined expected2026 value of $150bn: * Robot-Assisted Surgery * Virtual Nursing Assistants * Administrative Workflow Assistance * Fraud Detection * Dosage Error Reduction * Connected Machines * Clinical Trial Participant Identifier * Preliminary Diagnosis * Automated Image DiagnosisThe growth, however, is not unexpected and with the needs of the healthcareindustry of which AI fits the gap – it’s a match made in heaven.With the predicted 2026 value of robot-assisted surgery, virtual nursingassistants and administrative workflow assistance are expected to be valuedat $40bn, $20bn and $18bn respectively, it’s the numbers that come with claimsthat are the most impressive.

What are some applications of artificial intelligence systems in


healthcare?Despite some setbacks and limitations, Artificial Intelligence in healthcareare virtually announced every day. In this section, we will cover some of themost remarkable and revolutionary uses of AI in healthcare with anunderstanding that this list is by no means complete and definitely a work inprogress.

iCAD – Breast density via mammography


iCAD announced the launch of iReveal back in 2015 with the goal to monitorbreast density via mammography to support accurate decisions in breast cancerscreening.With an estimated 40% of women in the US having dense breast tissue that canblock the mammography from viewing potential cancerous tissue, the issue ishuge and a solution was imperative.The technology uses AI to assess breast density in order to identify patientsthat may experience reduced sensitivity to digital mammography due to densebreast tissue.Ken Ferry, CEO of iCAD stated that “With iReveal, radiologists may be betterable to identify women with dense breasts who experience decreased sensitivityto cancer detection with mammography.”Mr. also Ferry added that “The increasing support for the reporting of breastdensity across the US, there is a significant opportunity to drive adoption ofiReveal by existing users of the PowerLook AMP platform and with newcustomers, which represents an incremental $100 million market opportunityover the next few years. Longer-term, we plan to integrate the iRevealtechnology into our Tomosynthesis CAD product, which is the next large growthopportunity for our Cancer Detection business.”Ultimately, the system remains at the forefront of breast canceridentification in women in the U.S. and with so many lives expected to besaved, I think everyone can agree what a fantastic use of AI it is.

Neural Analytics – Device for paramedic stroke diagnosis


Neural Analytics, a medical device company tackling brain health, announced adevice for paramedic stroke diagnosis back in 2017, revolutionising the waythat paramedics diagnose stroke victims.Neural Analytic’ Lucid M1 Transcranial Doppler Ultrasound System tackles theissues of expensive and time-consuming stroke diagnosis for patients thatsuffer blood flow disorders.This ultrasound system is designed for measuring cerebral blood flowvelocities. This is no joke. Is successful, this technology will change howearly doctors can detect stroke and could drastically improve patientoutcomes.The use of Transcranial Doppler (TCD), a type of ultrasound, allows for AI toassess the brain’s blood vessels from outside the body, preventing the needfor more invasive tests. The AI software helps physicians detect stroke andother brain disorders caused by blood flow issues, increasing the capabilityof correct clinical decisions.

Mayo Clinic – AI cervical cancer screenings


Mayo Clinic, an organization focused on the development of patient care andhealth technology, has developed an artificial intelligence based solution toidentify precancerous changes in a woman’s cervix.The machine learning-based solution uses an algorithm taught with the use ofover 60,000 cervical images from the National Cancer Institute (NCI) for easeof identification of precancerous signs. Researchers state that the algorithmfunctions at a much higher success rate than a trained human expert with 91%compared to 69% of correctly identified signs.With the company continuously updating the algorithm, we can expect to see aneven higher percentage of correct clinical decisions in the very near future.It’s an exciting time for all involved within the industry.Interestingly enough, in March 2019, Mayo Clinic and Leidos announced buildinga tech accelerator on Mayo Clinic’s campus in Jacksonville within the LifeSciences Incubator campus. The campus is a med-tech hub designated to advancenew ideas and products from the research lab, through product development, forthe improvement of human health and well-being which includes variousArtificial Intelligence initiatives.

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