Artificial Intelligence In Medical

AI in medical

Some of the most amazing technology aspects we see in Artificial Intelligence are in the medical industry comes from the swarm or hive philosophy. This strategy is founded on taking the group approach as you might find in the insect world of working toward a common goal. (1) In all of the studies, the addition of swarm concepts and deep learning artificial intelligence has yielded improved results over groups of humans working independently toward Pneumonia studies.

None of us are individually as strong as all of us. Working toward common goals and solutions. This has been especially proven in the current world crisis with the coronavirus. Swarm or hive mentality is oversimplification when it comes to research a better description might be hyper-focused or singularly focused; since to say that insects are smarter might be a bit generous but when focused on one singular task and ignoring all other distraction and not concerning one's self with who gets the credit might yield some greater results.

The AI component should not be overlooked in this study also since maximizing the speed with which we gather the data is a big part of how soon we can find solutions.

If we break the details down, how do we work toward a solution? By taking small bits of data from around the world no matter how seemingly minute and allowing computers to mathematically find commonality and just as important, rule out the unimportant data.

The Swarm AI allows for us to improve our predictive analysis. It makes better use of the data and works on incredibly sophisticated algorithms and is able to utilize doctors to be the eyes and ears of the patients.

The applications for this data in manufacturing, business, and in our real lives, should not be overlooked.

With the COVID 19 virus. Researchers claim to have predicted this before it happened! Bluedot, AI warned its customers to avoid Wuhan on Dec 31. It used world health data to caution it's travelers to avoid the area because of data and the modeling used to track and predict how diseases spread. Some have said it had already spread by that time and the symptoms were slow to reveal themselves but in either case early detection and isolation have proven to be crucial in limiting the spread of the virus.

How quickly the virus was detected and identified was also a limiting factor for the model since it took much longer to identify that this was not just the flu or other regularly seen virus. Since it spreads much quicker and has been more difficult to detect it has complicated matters. The beauty of AI is it can sift through large amounts of data to find common points. (2)

Metabiota is another company using data to track health information. More data will make us healthier and protect us from the outbreak as well as help us predict what will happen and when it will happen.

There are some concerns that data overload can make us paranoid as we receive predictions of every perfect storm scenario. Is too much data healthy? If you're safer hiding at home in your basement from every possible illness are you truly living? Poor data and bad assumptions have created doubt in some of the models.

Artificial Intelligence is gathering data, tracking trends, building simulation models, and assisting to develop treatment plans and more importantly preventive care assessment that will help us live longer and healthier. Imagine predicting drug interactions we are not even aware of today. If a cure comes for cancer AI will be part of that solution. If our data continues on the current path we will see a greater analysis of pre-existing conditions and work to minimize their impact.

With telemedicine, we can monitor more data by remote and maintain better records. If you look at hypertension and compare it with your meals you can track how sodium is impacting your health. High blood pressure can be monitored and compared against your current prescriptions. No longer would you need to wait to go to the doctor to get updates on your health. Now you can get instant updates, predictive analysis and determine your health.

AI is also found in medical manufacturing. Since we have so much more technology going into monitors, pacemakers, etc. Manufacturers have more of a need to inspect, track, identify, and predict data around their parts and devices. The tighter the regulations the more of a need to identify your when problems occur. Along with inspection, you need identification so you can track when a device or component is manufactured. This tracking ability has proven to be crucial when a failure occurs, you need to identify if this is a one-off problem or if it's a batch problem or if it comes down to a complete design and product failure. This can impact the amount of recall or service work you need to address.

From the aspect of hospitals and doctors who rely on trust, it can make or break their business if the patients can't trust the products or solutions that medical personnel are proposing. Failures can crush a medical office when it results in an insurance claim. A single anomaly failure is bad but not as bad as a recall. Large hospitals like to know that the products they use have a long track record and have large paperwork files that show the history of reliability.

The way AI factors in is that you can develop a track record without having one if your inspection is done with proper modeling software. This predicts failure rates and what you are doing to reduce the risk or hazard. Artificial Intelligence works well to analyze short term data to have predictive data regarding failures in the long term.

Determining how patients respond to treatments is probably the most interesting are for AI since it gives patients a historical model to understand how treatments and diseases progress and the effectiveness of drugs works within the patient. We have existing models that show how drugs have negative effects on our organs and that some drugs need to have dosing increased as a disease progresses. Take for example type 2 diabetes. We have a lot of data representing how the disease progresses if you do nothing, we have models of the progress when you get worse or gain weight and we have models showing the benefits of weight loss and exercise. AI now can take these models and factor in dosing for current levels and show the long term effects and the ramifications of each model. We can also factor in homeopathic results in these models and the long term benefits and concerns patients should address when deviating from the prescribed treatment.

The number of Artificial Intelligence patents alone have gone up dramatically over the last 3 years. This graph shows how we are just beginning to understand all the possible applications. The changes in the medical industry and the demand more a quicker turnaround from a new breakthrough until it becomes available is far too long and faced with extensive delays and costly research projects.

AI can be applied to patients, med-devices, drugs, treatment, age-related disease progression, and far more, we will see changes from doctors visits to medical files. AI will allow us to live longer and healthier lives.