The Potential Application of Fuzzy Mathematics to Understanding Transcriptomic Changes in Dementia.
Advisor(s)
Dr. Jane Wu; Northwestern University
Discipline
Medical and Health Sciences
Start Date
21-4-2021 10:25 AM
End Date
21-4-2021 10:40 AM
Abstract
With our rapidly progressively aging society, neurodegenerative diseases including dementia have become one of the leading health challenges in our society. Significant advances have been made in our understanding of neuropathology and clinical manifestations of dementia. A vast amount of data has come from genetic, pathologic and molecular studies of brain samples from dementia patients and control subjects, however the underlying pathobiology and neural damage in dementia remain unclear. Researching this connection and developing a more lenient scale of diagnosing dementia through Fuzzy Mathematics would enable treatment for Dementia patients to improve. Fuzzy Mathematics enables it’s classifiers to have degrees of membership, as in normal sets a value either belongs or does not, but in fuzzy mathematics there is a range of values that can fit. Diagnosing dementia is not straightforward, as if it were there would be a single test out there capable of determining whether a patient has it. Doctors use medical history, physical examinations, laboratory tests and many other methods in order to determine if a person has Dementia. The goal is to decide if it is possible to use Fuzzy Mathematics to label how the transcriptomic changes affect Dementia, and through this work on creating a better system to diagnose it.
The Potential Application of Fuzzy Mathematics to Understanding Transcriptomic Changes in Dementia.
With our rapidly progressively aging society, neurodegenerative diseases including dementia have become one of the leading health challenges in our society. Significant advances have been made in our understanding of neuropathology and clinical manifestations of dementia. A vast amount of data has come from genetic, pathologic and molecular studies of brain samples from dementia patients and control subjects, however the underlying pathobiology and neural damage in dementia remain unclear. Researching this connection and developing a more lenient scale of diagnosing dementia through Fuzzy Mathematics would enable treatment for Dementia patients to improve. Fuzzy Mathematics enables it’s classifiers to have degrees of membership, as in normal sets a value either belongs or does not, but in fuzzy mathematics there is a range of values that can fit. Diagnosing dementia is not straightforward, as if it were there would be a single test out there capable of determining whether a patient has it. Doctors use medical history, physical examinations, laboratory tests and many other methods in order to determine if a person has Dementia. The goal is to decide if it is possible to use Fuzzy Mathematics to label how the transcriptomic changes affect Dementia, and through this work on creating a better system to diagnose it.