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Diagnosing Dyslexia

For over 100 years, dyslexia has confounded everyone even though it affects one in five people. Initially, those affected sought help from physicians because it was mistaken for an eye problem. Although it was later found to be a language problem, the medical field still “owns” dyslexia to this day due to this historical accident.

This is why families still turn to physicians to get a diagnosis. Psychologists also administer lengthy test batteries to diagnose dyslexia. Their neuropsychological evaluations cost several thousand dollars per person. Some families pay neurologists for brain scans. Schools in some states are now mandated to use dyslexia screeners developed by pediatricians and education publishers.

None of these diagnostic tools yield blueprints for intervention because they cannot get to the root of dyslexia for each person. Therefore, we have to first understand what dyslexia really is.

What Dyslexia Really Is


Dyslexia is a language condition that results in difficulty reading. The linguistic system in the brain is immensely complex, like a massive computer operating system with millions of lines of code. When a person has dyslexia, or difficulty reading, some processes in her linguistic system are not running efficiently. Therefore, to resolve her dyslexia, we have to first find a way to locate these processing inefficiencies, or bits and bytes of error in the code.

The only way to identify these processing inefficiencies is with AI technology because of three obstacles: the complexity of the linguistic system, the super-rapid speed of language processing, and the huge computing capacity needed to cross-reference billions of datapoints to derive an accurate diagnosis. Human specialists cannot overcome these obstacles.

Dysolve® AI has already succeeded in overcoming these obstacles to correct language processing inefficiencies. When these inefficiencies are corrected sufficiently, the struggling reader no longer struggles with reading, or dyslexia.

Therefore, AI technology shows that dyslexia can be operationalized as language processing inefficiencies. The latter can be identified, measured and corrected, so that the general condition of reading difficulty, dyslexia, no longer persists.

The Dyslexia Label


There is presently no consensus on the definition of dyslexia in research. In fact, a 2014 metasurvey of dyslexia studies recommends discontinuing the use of the “dyslexia” label (The Dyslexia Debate, Cambridge University Press). Dysolve® AI-generated data on struggling readers show that their condition is more accurately and usefully defined in terms of language processing inefficiencies. These are students who cannot pass school reading assessments and need extra support. But “language processing inefficiencies” are not easy for the public to grasp as a concept. A problem needs a memorable name to mobilize action. So we will continue to use the word “dyslexia”—even as we acknowledge this label’s deficiencies.

The End of Dyslexia Stigma


Understanding dyslexia as a temporary, correctible problem should end the stigma associated with it. Dyslexia no longer needs to be a permanent “disability” or “disorder.” It is a neurological condition because it involves how the brain processes language. But advances in technology can change the way the brain works.

Do Former Struggling Readers Still Have Dyslexia?


Do struggling readers still have dyslexia after this AI correction? No. Graduates of the Dysolve® AI program read on grade level, do not take longer than typical to complete schoolwork, and no longer need reading supports. Since they can now perform as well as, if not better than, their typical peers, they no longer have this “disability.” A disability is defined as a condition that restricts one’s ability to carry out the functions of daily living, in this case as a learner. Former struggling readers may still have scattered remnants of language processing inefficiencies, but these are no longer severe enough to impede them from reading and learning.


Coral PS Hoh is a clinical linguist with a PhD in Linguistics. For the past 30 years, she worked with children and adults with dyslexia, learning disabilities and other language-based disorders. The U.S. and other countries granted her AI patents for the diagnosis and treatment of these disorders. She is an author and referee for peer-reviewed journals and the architect of Dysolve®.

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