title: Decision Making Based on Fuzzy Aggregation Operators for Medical Diagnosis from Dental X-ray images.
abstract: Medical diagnosis is considered as an important step in dentistry treatment which assists clinicians to give their decision about diseases of a patient. It has been affirmed that the accuracy of medical diagnosis, which is much influenced by the clinicians' experience and knowledge, plays an important role to effective treatment therapies. In this paper, we propose a novel decision making method based on fuzzy aggregation operators for medical diagnosis from dental X-Ray images. It firstly divides a dental X-Ray image into some segments and identified equivalent diseases by a classification method called Affinity Propagation Clustering (APC+). Lastly, the most potential disease is found using fuzzy aggregation operators. The experimental validation on real dental datasets of Hanoi Medical University Hospital, Vietnam showed the superiority of the proposed method against the relevant ones in terms of accuracy.
authors: University of Information and Communication Technology, Thai Nguyen, Vietnam.
authors: Tran Thi
authors: TT
authors: Ngan
authors: University of Information and Communication Technology, Thai Nguyen, Vietnam.
authors: Tran Manh
authors: TM
authors: Tuan
authors: VNU University of Science Vietnam National University, Hanoi, Vietnam. sonlh@vnu.edu.vn.
authors: Le Hoang
authors: LH
authors: Son
authors: University of Information and Communication Technology, Thai Nguyen, Vietnam.
authors: Nguyen Hai
authors: NH
authors: Minh
authors: Techno India College of Technology, Kolkata, India.
authors: Nilanjan
authors: N
authors: Dey
mesh_terms: D000465:Algorithms; D000066491:Clinical Decision-Making / Q000379:methods*; D003813:Dentistry / Q000379:methods*; D017143:Fuzzy Logic; D006801:Humans; D011856:Radiographic Image Enhancement / Q000379:methods*; D015203:Reproducibility of Results; D014965:X-Rays
keywords: Decision making; Dental X-Ray image; Dental diagnosis; Fuzzy operators; Medical diagnosis