Skin disease under attack from Novel MAS A.I. platform

Skin disease under attack from Novel MAS A.I. platform

Skin disease under attack from Novel MAS A.I. platform. Qtis for Skincare, is Qtis.AI's flagship product platform to be launched in partnership with Apple Corporation.

Qtis for Skincare, is [Qtis.AI’s_](https://www.qtis.ai/) flagship product platform to be launched in partnership with Apple Corporation.  Qtis, leverages the advanced silicone, which is the Ax BIONOIC silicone, Apples imaging system, and their ever-evolving operating system. [Qtis,](https://www.qtis.ai/) is a new market entrant poised to further mankind’s demand for health and longevity, through its extensive and thoughtful combination of Science, Research, Technology, and now Consumer-facing products. _

84.5 million Americans, that’s one in four, are affected annually with Acne and other (exists over 3,000 known) skin conditions that cause numerous unknown harms. The costs associated with the treatment exceeded $1.2 billion while the US health care systems had $75 billion in medical, preventative, and prescription costs.

This is just one of the many, over 3,000 known skin conditions that affect so many people. But it happens to be the one that starts with adolescence and can affect people their entire lives.

A major challenge is how health care and its underlying processes are increasing bias in the diagnosis and treatment of many skin diseases. This statement is wide in scope and can cause a firestorm of sentiment on both sides of the argument. However, in today’s Medical practice we see the pressure a Clinician is under to take the time to sit and assess the entirety of the conditions, consider the symptomology and recall the best practice, treatment plan. I mean, Physicians are only human. They cannot be expected to recall in long-term memory or know every data point and or its efficacy in any particular case.

Solving this was an approach that has integrated many aspects of machine intelligence from natural language processing (NLP) through computer vision and general machine learning techniques. In the end, we provide this as a means for Dermatologists to remove bias from the workflow, increase treatment options, and overall provide patients with a better life through improved outcomes.

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