Mella uses the latest sensor technology and machine learning to safely and accurately measure temperature from the axillary (foreleg) region. Real time temperature curves are processed with patient characteristics to predict internal temperature within 0.3 degrees C, 40% more accurate than an FDA-cleared human thermometer at 0.5 desgrees C.Each reading is unique to the patient to provide the highest accuracy possible.
Mella's multiple state of the art temperature sensors create a composite reading, surpassing the conventional thermometer model. Sensors are located throughout the device and run through machine learning models to achieve accuracy that will only improve as we gather more field data.
Machine Learning Model
The Mella machine learning model utilizes state of the art AI techniques to create an accurate prediction of the pet’s temperature. Millions of pet records with temperature data from Banfield Pet Hospital were analyzed and provided the initial dataset for the machine model. Internal live animal trials using mercury thermometers alongside Mella produced data to further build the model. Clinical trials with veterinary hospitals and teaching institutions provide a means of data validation and fine tuning of the model to continuously narrow the error margin.
For more information on the machine learning model, download our breakdown
Integrated for Ease of Use
Using bluetooth connectivity, Mella thermometers can send temperature readings to your desktop or smartphone. The Mella app records the temperature value, date, and time for each patient every time.
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Temperature readings are automatically uploaded into new patient exams or can overwrite open exams. There is no more need to remember temperatures and manually input them before forgetting.
Mella is creating the new gold standard by providing the least fear inducing and accurate way to assess patient vitals. Pet specific thermometers are rare on the market, and no other offers an axillary attachment let alone one as accurate as normal rectal thermometers.