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Machine translation
1. (WO2005104768) SYSTEM AND METHOD FOR AUTOMATIC GENERATION OF A HIERARCHICAL TREE NETWORK AND THE USE OF TWO COMPLEMENTARY LEARNING ALGORITHMS, OPTIMIZED FOR EACH LEAF OF THE HIERARCHICAL TREE NETWORK
Latest bibliographic data on file with the International Bureau   

Pub. No.:    WO/2005/104768    International Application No.:    PCT/US2005/014522
Publication Date: 10.11.2005 International Filing Date: 27.04.2005
IPC:
G06Q 50/00 (2006.01)
Applicants: HUMANA INC. [US/US]; 500 West Main Street, Louisville, KY 40204 (US) (For All Designated States Except US).
KIL, David, H. [US/US]; (US) (For US Only).
POTTSCHMIDT, David, B. [US/US]; (US) (For US Only)
Inventors: KIL, David, H.; (US).
POTTSCHMIDT, David, B.; (US)
Agent: EAVES, James, C., Jr.; Greenebaum Doll & McDonald PLLC, 3500 National City Tower, 101 South Fifth Street, Louisville, KY 40202 (US)
Priority Data:
60/565,579 27.04.2004 US
Title (EN) SYSTEM AND METHOD FOR AUTOMATIC GENERATION OF A HIERARCHICAL TREE NETWORK AND THE USE OF TWO COMPLEMENTARY LEARNING ALGORITHMS, OPTIMIZED FOR EACH LEAF OF THE HIERARCHICAL TREE NETWORK
(FR) SYSTEME ET PROCEDE DE GENERATION AUTOMATIQUE D'UNE STRUCTURE ARBORESCENTE HIERARCHIQUE ET UTILISATION DE DEUX ALGORITHMES D'APPRENTISSAGE COMPLEMENTAIRES, OPTIMISES POUR CHAQUE NOEUD TERMINAL DE LA STRUCTURE ARBORESCENTE HIERARCHIQUE
Abstract: front page image
(EN)A system and method that generates a hierarchical tree network and uses linear-plus-nonlinear learning algorithms to form a consensus view on a member’s future health status. Each least in the hierarchical tree network is homogeneous in clinical characteristics, experience period, and available data assets. Optimization is performed on each leaf so that features and learning algorithms can be tailored to local characteristics specific to each leaf.
(FR)L'invention concerne un système et un procédé qui permettent de générer une structure arborescente hiérarchique et utilisent des algorithmes d'apprentissage non linéaires pour élaborer une opinion générale sur un état de santé futur d'un membre. Chaque noeud terminal de la structure arborescente hiérarchique est homogène en termes de caractéristiques cliniques, de période d'expérience et de patrimoines de données disponibles. On optimise chaque noeud terminal de telle façon que les caractéristiques et algorithmes d'apprentissage puissent être adaptés aux caractéristiques locales de spécifiques à chaque noeud terminal.
Designated States: AE, AG, AL, AM, AT, AU, AZ, BA, BB, BG, BR, BW, BY, BZ, CA, CH, CN, CO, CR, CU, CZ, DE, DK, DM, DZ, EC, EE, EG, ES, FI, GB, GD, GE, GH, GM, HR, HU, ID, IL, IN, IS, JP, KE, KG, KM, KP, KR, KZ, LC, LK, LR, LS, LT, LU, LV, MA, MD, MG, MK, MN, MW, MX, MZ, NA, NI, NO, NZ, OM, PG, PH, PL, PT, RO, RU, SC, SD, SE, SG, SK, SL, SM, SY, TJ, TM, TN, TR, TT, TZ, UA, UG, US, UZ, VC, VN, YU, ZA, ZM, ZW.
African Regional Intellectual Property Organization (BW, GH, GM, KE, LS, MW, MZ, NA, SD, SL, SZ, TZ, UG, ZM, ZW)
Eurasian Patent Organization (AM, AZ, BY, KG, KZ, MD, RU, TJ, TM)
European Patent Office (AT, BE, BG, CH, CY, CZ, DE, DK, EE, ES, FI, FR, GB, GR, HU, IE, IS, IT, LT, LU, MC, NL, PL, PT, RO, SE, SI, SK, TR)
African Intellectual Property Organization (BF, BJ, CF, CG, CI, CM, GA, GN, GQ, GW, ML, MR, NE, SN, TD, TG).
Publication Language: English (EN)
Filing Language: English (EN)