Bayesian network in differential diagnosis of head and neck cancer
Principal Investigator
Name
Kamila Bukirova
Degrees
Ph.D.
Institution
Near East University
Position Title
Student
Email
About this CDAS Project
Study
PLCO
(Learn more about this study)
Project ID
PLCO-571
Initial CDAS Request Approval
Feb 7, 2020
Title
Bayesian network in differential diagnosis of head and neck cancer
Summary
Bayesian network (BN) is not a novel probability model in AI which is used in various fields from data mining and text classification through strategic planning to medical diagnosis. The latter application was developed a lot and became appealing for many researchers though, there is still a lot of ground to cover. The lack of the studies on the use of BNs can be explained with two reasons: medical professionals are not so much aware of BNs, its advantages and possible application; awared professionals are interested in any other field or may, perhaps, consider themselves not enough capable to make the analysis for the medical diagnosis. However, there are a lot of clinical conditions which still remain understudied and still require to be differentiated from other diseases with similar clinical manifestations or/and laboratory findings or/and risk factors. The future of BNs is undoubtedly bright but we live today and current patients along with current doctors on-site need some tool to make differential diagnosis more availbale and effective.
The research I am working on is related to the diffential diagnosis of head and neck cancer with the use of BN, I am planning to work with the doctors from Near East Hospital (TRNC) who have expertise in head and neck tumors.There is a great need in a big data which is not impossible to obtain from any other source except for this database. The large amount of patients obviously will increase the precision and reliability of the results.
The research I am working on is related to the diffential diagnosis of head and neck cancer with the use of BN, I am planning to work with the doctors from Near East Hospital (TRNC) who have expertise in head and neck tumors.There is a great need in a big data which is not impossible to obtain from any other source except for this database. The large amount of patients obviously will increase the precision and reliability of the results.
Aims
1. The major aim is to write my Ph.D. thesis which will not just gather dust on the shelves in my room and in the university library but will make me feel proud for the work I have done.
2. The second aim, perhaps, more ambitious and that is why more desired, is to implement the elaborated network into the medical practice. Thus, it will hopefully make the future diagnosis of the patients with different head and neck tumors easier.
Collaborators
Prof. Dr. Ilker Etikan, Near East University
Dr. Chibuke Sopuru, Girne American University