title: Prediction of care class by local additive reference to prototypical examples.
abstract: The public long-term care insurance program for the elderly in Japan set out in 2000 toward establishing a new system whereby citizens can be assured that they will receive care and be supported by the society as a whole. The insurance program includes computer-aided certification processes to estimate the needs for nursing care for clients. In this work, we show the applicability of an adaptive local nonlinear approximation method associated with the Japanese national database for automatic inference of the care class.
authors.affiliation: Department of Micro System Technology, Ritsumeikan University, Shiga, Japan. tmiyano@se.ritsumei.ac.jp
authors.forename: Takaya
authors.initials: T
authors.lastname: Miyano
authors.forename: Takako
authors.initials: T
authors.lastname: Tsutsui
authors.forename: Yoichi
authors.initials: Y
authors.lastname: Seki
authors.forename: Sadanori
authors.initials: S
authors.lastname: Higashino
authors.forename: Hitoshi
authors.initials: H
authors.lastname: Taniguchi
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D020000:Decision Support Systems, Clinical; D003936:Diagnosis, Computer-Assisted / Q000379:methods*; D003953:Diagnosis-Related Groups; D005260:Female; D015577:Geriatric Assessment / Q000379:methods*; D006297:Health Services Accessibility; D006299:Health Services for the Aged / Q000145:classification*; D006801:Humans; D007564:Japan; D008297:Male; D009313:National Health Programs; D020380:Needs Assessment; D009732:Nursing Care / Q000145:classification* / Q000379:methods; D013813:Therapy, Computer-Assisted / Q000379:methods