heart-shaped pills coming out of a bottle

It’s incredibly important to understand how drugs interact with each other to keep patients out of dangerous and deadly situations. South Korea’s KAIST University recently shared that it’s developed a deep learning system to precisely predict interactions between certain drugs. With an accuracy rate of 92.4, this tech can predict 192,284 drug-to-drug interactions. But it doesn’t stop there. In its most recent iteration, it can predict drug-to-food interactions as well.

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Cell phone next to a report

A team of Russian scientists created an AI-based algorithm that can estimate your expected lifespan more accurately than past models. The algorithm draws on activity tracking from smartphones and smartwatches to monitor your health. But it’s not a catch all. The people who created it say it can’t take into account things like genes, diet, and various other factors, so it should always be coupled with your doctor’s perspective.

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Diabetes medical equipment

Using smartphone technology, a group of Harvard scientists are making it possible for people to monitor their blood potassium levels at home without drawing blood. The scientists developed a machine learning algorithm to detect potassium abnormalities in the blood. How does it work? They attach electrodes to a smartphone to record an ECG. Then, the machine learning algorithm flags subtle changes in the ECGs that correlated with blood potassium levels.

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Children playing with sidewalk chalk

An autism diagnostic tool that you can use on your phone is headed toward FDA approval. How does it work? Parents answer several basic questions about their child and then upload a video of their child performing basic tasks at home. Then a machine learning algorithm sifts through the information to predict the likelihood of autism.

What are the implications? It can take a long time for parents to figure out if their children have autism and get them help early enough to make a difference. This tool will help the first problem. The second problem, the shortage of care, is still a concern.

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Doctor wearing a stethescope

When dealing with a long-term ailment, like asthma, it means a lot of trips to the doctor. But what if you could reduce those trips by enabling yourself to monitor your symptoms or your child’s symptoms from home? That’s what this wireless stethoscope, StethoMe, aims to do. It monitors heartbeat, body temperature, and lung sounds. If it finds something unusual as it compares those numbers against its repository of information, then it will ping your family doctor. The creators are currently looking for funding to commercialize the tool.

What are the implications? It reports respiratory issues to your doctor faster and saves you time and potentially money by reducing the number of your visits to the doctor.

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It’s easy for lung doctors to find larger nodules that are developing into cancer, but often when discovered, those cancerous nodules have advanced too far and the doctors can’t save the patients’ lives. Now there’s an AI that can help doctors identify smaller cancerous nodules earlier. The earlier the detection, the higher the likelihood of patient survival.
What are the implications? Not only does this identify the cancerous nodules earlier and increase life expectancy, but it also saves doctors up to four and a half hours a day in analyzing scans—time that can be used to research cancer treatments and to better treat and communicate with patients.

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A company named Montfort won the Henry Ford Health System’s AI challenge. Its product? An app that daily records and analyzes data from patients who suffer with diseases like Parkinson’s and normal pressure hydrocephalus (NPH). It non-invasively tracks how patients use their smart devices and also links to wearables in order to measure motor, cognitive, affective, and physiological indicators. This easily accessible daily data helps doctors to better assess patients and tailor their approaches to individual needs.

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For some people, working with health insurance and healthcare providers to figure out billing post a doctor’s visit can be an impressively frustrating experience. If you’re one of those people and need to visit the doctor frequently for testing, ask yourself this, what if you could conduct some of your routine medical testing from home—with your very own smart device—and simply send your doctor the results? How would this change your life? That’s what this AI is hoping to help you do, conduct approved medical test from home.
It’s starting with urinalysis, a test that can give insights to people dealing with various health problems, like infections, chronic illnesses, and pregnancy-related complications. How it works is you take a picture of your sample and use it in conjunction with a dip stick to test for certain conditions. For some people, this tool will significantly reduce the number of doctor’s visits they need to make, and they can easily share the test results with the appropriate medical personnel. For everyone else, hopefully this tool soon expands to other offerings, bringing more relief to people experiencing healthcare red-tape fatigue.

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Lots of us at one point or another experience an unusual heartbeat. One second your heart is happily, quietly, and regularly lubb-dupping away (I promise I didn’t make lubb-dupp up), and the next second, it’s bizarrely off. If this irregular heartbeat bothers you enough, you’ll go get it checked out, and your doctor will likely send you home with a Holter heart monitor to wear for 24 hours—but then, of course, your heart does absolutely nothing out of the ordinary in those 24 hours, and your doctor tells you that you’re probably just fine.

But what if you could wear something that would monitor your heart all the time and also identify when something’s off? This AI tech, which is now FDA approved, does just that. It collects your data and identifies when a heartbeat is unusual for whatever activity you’re doing. It can read your heart rate every five seconds, 24/7, if need be. So when your heartbeat doesn’t make sense, it tells you to take an EKG immediately through your device. Also, on a similar front, researchers led by Andrew Ng are adjusting an AI so it can speed up and improve irregular-heartbeat diagnoses. All of this to better learn what your heart’s rhythm is telling you.

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It sounds morbid to predict the likelihood of someone dying within the next year. But when you think about identifying these people so they can experience their last days in their own homes sans rigorous and painful treatments that probably won’t prolong their lives, it takes on a different hue. This AI aims to change that.
According to this article, many physicians give people more hopeful diagnoses than their situations may merit. It seems nice to give someone hope while they receive devastating news, but the unintended consequences may not be. A hopeful diagnosis may prolong treatment and lead to a poorer end-of-life experience, a situation they might not choose if they understood the likelihood of their earlier passing. Eighty percent of people in the United States say they’d like to pass away in their own homes if possible, but up to sixty percent end up dying while receiving aggressive medical treatments.

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