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5 Uses of AI in Medical Imaging

by Mark
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1. Better Data Storage

For most healthcare systems around the world, medical images accounts for the greatest degree of storage space required to save data for analysis. According to openmedscience.com, 97% of all medical imaging data stored can never be analyzed given the amount of complexities that arise in reading it.

With Artificial intelligence, the need to store such vast amounts of data will diminish, because the computerized efficiency will help in visualizing and understanding the problems within using much thinner slices of data.

2. Personalizing Treatment

Cost-efficiency is as big a goal for healthcare systems as it is for you. You would like to have a disease-curing plan which is very personalized to the situation of your health, keeping diabetes, weakness, and other genetic issues in mind.

Traditional cloud PACS may ignore these previously existing issues on account of them not being shown on the recent scans, but you can rely on AI to give you a permuted plan that you can follow with ease. Not only will such treatments save time, chances of them being effective become much greater.

3. Concise Information Provision

Given how cloud PACS or DICOM requires volumes of data, it becomes exceptionally difficult to sort the data and find information relevant to you. As a paying patient, you have every right to demand that your data is stored securely and accessed readily, and AI is the way to do just that in the future.

First of all, it will reduce the need to store all the data a certain imaging and its reports have established. Instead of going through present records, AI can be used to rescan present images and highlight the important health factors shown by them. The rescans can then be eliminated, meaning that nothing more than the images and customer history will be needed.

The more concise the storage, the better you can expect your healthcare management to be.

4. Assist Human Radiologists

One issue with AI software is that at present its capacity of correctly identifying a disease through data is not perfect, and it might never be. However, with advancements brought in by IBM and Vision you can expect the doctors of the future to be sitting with their AI buddies who will actively help you in figuring out your medical status.

The importance of AI here can be acquainted to data once again, where a bot/computer can store in information of such high volumes that finding the correct case among all available combinations is much easier. If, for example, a case is very rare and radiologists in your area have not be frequently exposed to them, but the relevant data has been fed to the AI machine, its matching becomes a high probability.

5. Preliminary Scans

For recurrent issues in patients, preliminary scans, radiology cloud PACS storage, and questions can take up a lot of time. You can say goodbye to that inconvenience with AI because all your information will be readily provided and you can proceed in a much more orderly fashion with your cure.

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