The process of identifying a disease, condition, or injury from its signs and symptoms through the use of artificial intelligence (AI) and machine learning.
Here’s How It Works:
Collecting Initial Evidence
The patient interview starts with gathering initial symptoms, risk factors, and demographic data. Additional input regarding the symptoms' occurrence or severity helps the engine be even more precise. The AI engine is backed by a comprehensive library of thousands of medical conditions and covers multiple specialties, including pediatrics.
The AI engine uses initial evidence to construct a dynamic interview based on probabilistic models and reasoning techniques. It was developed by our data scientists, who collaborated closely with hundreds of medical experts.
Sniffle’s AI knows exactly when to stop asking questions. The AI engine observes correlations between patients’ symptoms and hundreds of diseases. With every answer from the user, it becomes more accurate when assessing the most probable conditions.
Finally, the AI engine presents the Aignosis with the most probable causes of the symptoms, paired with the suggested level of care. The causes with the highest level of probability are presented first. Combined with the answers from the intelligent interview, recommendations are unique to each situation.