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Performing Health Care Tasks Using Automation

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2023-05-09 13:48:08
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Artificial intelligence (AI) is great at automation, which can make it ideal for tasks in health care. It never deviates from the procedure, never gets tired, and never makes mistakes as long as the initial procedure is correct.

Unlike humans, AI never needs a vacation or a break or even an eight-hour day (not that many in the medical profession have that, either). Consequently, the same AI that interacts with a patient for breakfast will do so for lunch and dinner as well. So, at the outset, AI has some significant advantages if viewed solely on the bases of consistency, accuracy, and longevity.

Working with medical records

The major way in which an AI helps in medicine is medical records. In the past, everyone used paper records to store patient data. Each patient might also have a blackboard that medical personnel use to record information daily during a hospital stay. Various charts contain patient data, and the doctor might also have notes. Having all these sources of information in so many different places made it hard to keep track of the patient in any significant way. Using an AI, along with a computer database, helps make information accessible, consistent, and reliable. Products such as Google Deepmind Health enable personnel to mine the patient information to see patterns in data that aren’t obvious.

Doctors don’t necessarily interact with records in the same way that everyone else does. The use of products such as IBM’s WatsonPaths helps doctors interact with patient data of all sorts in new ways to make better diagnostic decisions about patient health. You can see a video on how this product works.

Medicine is about a team approach, with many people of varying specialties working together. However, anyone who watches the process for a while soon realizes that these people don’t communicate among themselves sufficiently because they’re all quite busy treating patients. Products such as CloudMedX take all the input from the all parties involved and performs risk analysis on it. The result is that the software can help locate potentially problematic areas that could reduce the likelihood of a good patient outcome. In other words, this product does some of the talking that the various stakeholders would likely do if they weren’t submerged in patient care.

Predicting the future

Some truly amazing predictive software based on medical records includes CareSkore, which actually uses algorithms to determine the likelihood of a patient’s requiring readmission into the hospital after a stay. By performing this task, hospital staff can review reasons for potential readmission and address them before the patient leaves the hospital, making readmission less likely. Along with this strategy, Zephyr Health helps doctors evaluate various therapies and choose those most likely to result in a positive outcome — again reducing the risk that a patient will require readmission to the hospital. This video tells you more about Zephyr Health.

In some respects, your genetics form a map of what will happen to you in the future. Consequently, knowing about your genetics can increase your understanding of your strengths and weaknesses, helping you to live a better life. Deep Genomics is discovering how mutations in your genetics affect you as a person. Mutations need not always produce a negative result; some mutations actually make people better, so knowing about mutations can be a positive experience, too. Check out this video for more details.

Making procedures safer

Doctors need lots of data to make good decisions. However, with data being spread out all over the place, doctors who lack the ability to analyze that disparate data quickly often make imperfect decisions. To make procedures safer, a doctor needs not only access to the data but also some means of organizing and analyzing it in a manner reflecting the doctor’s specialty. One such product is Oncora Medical, which collects and organizes medical records for radiation oncologists. As a result, is these doctors can deliver the right amount of radiation to just the right locations to obtain a better result with a lower potential for unanticipated side effects.

Doctors also have trouble obtaining necessary information because the machines they use tend to be expensive and huge. An innovator named Jonathan Rothberg has decided to change all that by using the Butterfly Network. Imagine an iPhone-sized device that can perform both an MRI and an ultrasound. The picture on the website is nothing short of amazing.

Creating better medications

Everyone complains about the price of medications today. Yes, medications can do amazing things for people, but they cost so much that some people end up mortgaging homes to obtain them. Part of the problem is that testing takes a lot of time. Performing a tissue analysis to observe the effects of a new drug can take up to a year. Fortunately, products such as 3Scan can greatly reduce the time required to obtain the same tissue analysis to as little as one day.

Of course, better still would be the drug company having a better idea of which drugs are likely to work and which aren’t before investing any money in research. Atomwise uses a huge database of molecular structures to perform analyses on which molecules will answer a particular need. In 2015, researchers used Atomwise to create medications that would make Ebola less likely to infect others. The analysis that would have taken human researchers months or possibly years to perform took Atomwise just one day to complete. Imagine this scenario in the midst of a potentially global epidemic. If Atomwise can perform the analysis required to render the virus or bacteria noncontagious in one day, the potential epidemic could be curtailed before becoming widespread.

Drug companies also produce a huge number of drugs. The reason for this impressive productivity, besides profitability, is that every person is just a little different. A drug that performs well and produces no side effects on one person might not perform well at all and could even harm a different person. Turbine enables drug companies to perform drug simulations so that the drug companies can locate the drugs most likely to work with a particular person’s body. Turbine’s current emphasis is on cancer treatments, but it’s easy to see how this same approach could work in many other areas.

Medications can take many forms. Some people think they come only in pill or shot form, yet your body produces a wide range of medications in the form of microbiomes. Your body actually contains ten times as many microbes as it does human cells, and many of these microbes are essential for life; you’d quickly die without them. Whole Biome is using a variety of methods to make these microbiomes work better for you so that you don’t necessarily need a pill or a shot to cure something. Check out this video for additional information.

Some companies have yet to realize their potential, but they’re likely to do so eventually. One such company is Recursion Pharmaceuticals, which employs automation to explore ways to use known drugs, bioactive drugs, and pharmaceuticals that didn’t previously make the grade to solve new problems. The company has had some success in helping to solve rare genetic diseases, and it has a goal of curing 100 diseases in the next ten years (obviously, an extremely high goal to reach).

About This Article

This article is from the book: 

About the book author:

John Paul Mueller is a freelance author and technical editor. He has writing in his blood, having produced 100 books and more than 600 articles to date. The topics range from networking to home security and from database management to heads-down programming. John has provided technical services to both Data Based Advisor and Coast Compute magazines.

Luca Massaron is a data scientist specialized in organizing and interpreting big data and transforming it into smart data by means of the simplest and most effective data mining and machine learning techniques. Because of his job as a quantitative marketing consultant and marketing researcher, he has been involved in quantitative data since 2000 with different clients and in various industries, and is one of the top 10 Kaggle data scientists.