title: Contribution of artificial intelligence to the knowledge of prognostic factors in laryngeal carcinoma.
abstract: Many studies have investigated prognostic factors in laryngeal carcinoma, with sometimes conflicting results. Apart from the importance of environmental factors, the different statistical methods employed may have influenced such discrepancies. A program based on artificial intelligence techniques is designed to determine the prognostic factors in a series of 122 laryngeal carcinomas. The results obtained are compared with those derived from two classical statistical methods (Cox regression and mortality tables). Tumor location was found to be the most important prognostic factor by all methods. The proposed intelligent system is found to be a sound method capable of detecting exceptional cases.
authors.affiliation: ENT Department, Valencia University General Hospital, Valencia University Medical School, Spain. ezapater@ctv.es
authors.forename: E
authors.initials: E
authors.lastname: Zapater
authors.forename: S
authors.initials: S
authors.lastname: Moreno
authors.forename: M A
authors.initials: MA
authors.lastname: Fortea
authors.forename: A
authors.initials: A
authors.lastname: Campos
authors.forename: M
authors.initials: M
authors.lastname: Armengot
authors.forename: J
authors.initials: J
authors.lastname: Basterra
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000428:Alcohol Drinking / Q000009:adverse effects; D000465:Algorithms; D001185:Artificial Intelligence; D001706:Biopsy; D003198:Computer Simulation; D003663:Decision Trees; D006801:Humans; D007822:Laryngeal Neoplasms / Q000175:diagnosis* / Q000209:etiology / Q000401:mortality* / Q000628:therapy; D015993:Life Tables; D008875:Middle Aged; D009367:Neoplasm Staging; D011379:Prognosis; D016016:Proportional Hazards Models; D012307:Risk Factors; D012907:Smoking / Q000009:adverse effects; D016019:Survival Analysis; D014139:Tracheostomy