Detection of Dyscalculia Using Machine Learning

The detection of learning disabilities is still tedious and time consuming and a deep research is required for the simplification of the same. Dyscalculia is one of the Specific learning Disorders (SLD) with a specific impairment in Mathematics. Early detection of Dyscalculia is one of these tedious, time consuming tasks. Detection of Dyscalculia is carried out by conducting various tests where every individual test has to be conducted and evaluated manually as the scores of these individual tests alone are not sufficient for detection. For some cases, the scores from these tests are not sufficient. Some extra tests like Curriculum Based Test [CBT's] and/or Wide Range Achievement Test [WRAT] are to be administered. Artificial intelligence (AI) for health care involves the use of complex algorithms to emulate human cognition in the perusal of complicated medical data. The derivatives of Woodcock Johnson Tests of Achievements are used to determine learning disabilities. These tests are conducted by the doctors.