{"search_session":{},"preferences":{"l":"en","queryLanguage":"en"},"patentId":"181-313-234-240-092","frontPageModel":{"patentViewModel":{"ref":{"entityRefType":"PATENT","entityRefId":"181-313-234-240-092"},"entityMetadata":{"linkedIds":{"empty":true},"tags":[],"collections":[{"id":10774,"type":"PATENT","title":"University of Munich - Patent Portfolio","description":"","access":"OPEN_ACCESS","displayAvatar":true,"attested":false,"itemCount":1687,"tags":[],"user":{"id":91044780,"username":"Cambialens","firstName":"","lastName":"","created":"2015-05-04T00:55:26.000Z","displayName":"Cambialens","preferences":"{\"usage\":\"public\",\"beta\":false}","accountType":"PERSONAL","isOauthOnly":false},"notes":[{"id":8244,"type":"COLLECTION","user":{"id":91044780,"username":"Cambialens","firstName":"","lastName":"","created":"2015-05-04T00:55:26.000Z","displayName":"Cambialens","preferences":"{\"usage\":\"public\",\"beta\":false}","accountType":"PERSONAL","isOauthOnly":false},"text":"
Search Applicants and Owners separately: \"Ludwig* Maximilian* Univ*\"; \"Ludwig* Maximilian* mun*\"; \"Lud* Maxi* m?n*\"; \"uni* Lud* Maxi*\"
Select more for logical variants. Add to collection. Select all patents in the collection and expand by simple families. Add to collection. Total patents: 216
Search Applicants and Owners separately: \"Ludwig* Maximilian* Univ*\"; \"Ludwig* Maximilian* mun*\"; \"Lud* Maxi* m?n*\"; \"uni* Lud* Maxi*\"
Select more for logical variants. Add to collection. Select all patents in the collection and expand by simple families. Add to collection. Total patents: 216
(a) compiling a gene expression profile of a patient sample by determining the expression level of at least one marker selected from the markers identifiable by their Affymetrix Identification Numbers (affy id) as defined in Tables 1, and/or 2, and
(b) classifying the gene expression profile by means of a machine learning algorithm."],"number":23,"annotation":false,"title":false,"claim":true},{"lines":["The apparatus according to claim 23, wherein the machine learning algorithm is selected from the group consisting of Weighted Voting, K-Nearest Neighbors, Decision Tree Induction, Support Vector Machines, and Feed-Forward Neural Networks, preferably Support Vector Machines."],"number":24,"annotation":false,"title":false,"claim":true},{"lines":["The apparatus according to at least one of the claims 22-24, wherein the apparatus contains a control panel and/or a monitor."],"number":25,"annotation":false,"title":false,"claim":true},{"lines":["A reference data bank for distinguishing AML subtypes with aberrant and prognostically intermediate karyotypes selected from trisomy 8, inv(3), t(3;3), trisomy 11, trisomy 13, trisomy 4, t(1;3), t(6;9), der(S)t(5;11), i(17), del(9q), del(12p), and/or del(20q) obtainable by comprising
(a) compiling a gene expression profile of a patient sample by determining the expression level of at least one marker selected from the markers identifiable by their Affymetrix Identification Numbers (affy id) as defined in Tables 1, and/or 2, and
(b) classifying the gene expression profile by means of a machine learning algorithm."],"number":26,"annotation":false,"title":false,"claim":true},{"lines":["The reference data bank according to claim 26, wherein the reference data bank is backed up and/or contained in a computational memory chip."],"number":27,"annotation":false,"title":false,"claim":true}]}},"filters":{"npl":[],"notNpl":[],"applicant":[],"notApplicant":[],"inventor":[],"notInventor":[],"owner":[],"notOwner":[],"tags":[],"dates":[],"types":[],"notTypes":[],"j":[],"notJ":[],"fj":[],"notFj":[],"classIpcr":[],"notClassIpcr":[],"classNat":[],"notClassNat":[],"classCpc":[],"notClassCpc":[],"so":[],"notSo":[],"sat":[]},"sequenceFilters":{"s":"SEQIDNO","d":"ASCENDING","p":0,"n":10,"sp":[],"si":[],"len":[],"t":[],"loc":[]}}