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Radimal Initial Assessment - Maximizing Efficiency and Accuracy in Veterinary Practice
Radimal Initial Assessment - Maximizing Efficiency and Accuracy in Veterinary Practice
Alan Weissman avatar
Written by Alan Weissman
Updated over a week ago

Many vets these days are wondering about how to best utilize AI tools in their workflow. At every veterinary conference, it seems like AI is one of the most discussed and debated topics. If you've felt some combination of skepticism and curiosity, this article is for you!

In order to provide the best radiology experience in supporting your patient treatment, Radimal provides both the Initial Assessment tool and the ability to 'Request' Specialist Consultations from your dashboard. Here's what clients say they like about each:

Radimal Initial Assessment: Fast (<10 minutes), inexpensive, doesn't cover all conditions, and isn't definitive, results can be adjusted based on the GP's expertise

Specialist Consultation: Fast (<1 Hour), reasonably priced, covers all conditions and is definitive, results based on the Specialist's expertise, GP can ask follow-up questions

Radimal Initial Assessment is an AI-powered tool that is designed to assist GP's with patient treatment by reviewing x-ray images, providing a risk assessment and preliminary insights as specified by 'Possible Indications'. None of the information provided is meant to be definitive (that's what specialists are for!) and the tool nonetheless empowers GP's to have information quickly as part of their radiology workflow.

Once you acquire images, you'll see that Radimal starts scanning them in your dashboard:

The scanning animation lets you know that the system is working! Once complete (<10 mins), you'll see results in your dashboard. Here's three examples of what you might see:

Example 1 - In this 'Low Risk' example, Radimal Initial Assessment has identified the possibility of Spondylosis and Stifle degeneration, which are common and don't normally cause great concern for GP's.

Example 2 - In the above 'Medium Risk' example, Radimal Initial Assessment has identified the possibility of Left Atrial Enlargement, a condition that might be reason for moderate concern for the GP.

Example 3 - 'High Risk' means that the Radimal Initial Assessment has identified the possibility of Congestive Heart Failure (among other possible conditions) for which a GP might have a high level of concern.

Working with the Initial Assessment tool

The best results come from GPs working with the Initial Assessment tool to verify or change Possible Indications. Clicking on a patient's Initial Assessment results will bring you to the Initial Assessment workflow which enables you to perform the following functions:

  • Remove any indications that you do not feel are medically accurate

  • Add any relevant or concerning indications that were not discovered by the scan

  • Generate a PDF report of the Initial Assessment results, with your changes (if any)

  • Request a Specialist Consultation, with your Initial Assessment results taken into consideration

While the workflow is straightforward and easy to use, there is nevertheless sometimes confusion as to how to best interpret the results:

Misconception: Radimal Initial Assessment replaces the need for a Specialist Consultation

Truth: Radimal Initial Assessment results are not definitive, and are best utilized in conjunction with a GPs specific medical knowledge, possibly the help of a Radiology Specialist, to guide treatment. It is in no way a replacement for a Radiology Specialist, and for any uncertainty, Radimal provides the ability to 'Request' as Specialist Consultation.

Misconception: The results have something wrong, so I shouldn't use this anymore

Truth: Results from Radimal Initial Assessment (and AI tools in general) are designed to improve the overall accuracy of a Doctor in detecting the presence or absence of conditions in x-rays across a large number of patients and images. For any given patient result, it is not a question of 'correct/incorrect' but rather 'can these results help me'. According to research from human medicine, the answer is a resounding YES.

Misconception: The quality of image acquisition doesn't matter to the AI

Truth: Both image quality (such as lighting adjustments on the x-ray machine) and acquisition quality (such as patient positioning) greatly affect the quality of Radimal Initial Assessment results. Additionally, the number of images is a determining factor in not only what can be identified, but how accurately. We recommend 2-3 high-quality images of each body region (thorax, abdomen, etc) for which the GP would like to receive results.

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