VIAF

Virtual International Authority File

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Leader 00000nz a2200037n 45 0
001 PLWABN|9813193871305606 (VIAF cluster)
005 20230321165850.0
008 230313n||aznnnaabn |a aaa |c
003 PLWABN
035 ‎‡a (PLWABN)9813193871305606‏
010 ‎‡a p 2023049686‏
035 ‎‡a (PL)a1000001183340‏
040 ‎‡a WA N‏ ‎‡c WA N‏
043 ‎‡c MX‏
100 1 ‎‡a Flores-Mejía, Luis Angel‏
370 ‎‡c Meksyk‏
372 ‎‡a Medycyna‏
375 ‎‡a 1‏ ‎‡2 iso5218‏
377 ‎‡a spa‏ ‎‡a eng‏
400 1 ‎‡a Mejía, Luis Angel Flores-‏
670 ‎‡a Accuracy of machine learning algorithms for the assessment of upper-limb motor impairments in patients with post-stroke hemiparesis: a systematic review and meta-analysis / Jorge Fernando Ambros-Antemate, Adriana Reyes-Flores, Liliana Argueta-Figueroa, Rafael Ramírez-Ramírez, Marciano Vargas-Treviño, Jaime Gutiérrez-Gutiérrez, Eduardo Pérez-Campos Mayoral, Eduardo Pérez-Campos, Luis Angel Flores-Mejía, Rafael Torres-Rosas. W: Advances in Clinical and Experimental Medicine. Vol. 31, nr 12 (2022).‏
670 ‎‡a Researchgate‏
919 ‎‡a accuracyofmachinelearningalgorithmsfortheassessmentofupperlimbmotorimpairmentsinpatientswithpoststrokehemiparesisasystematicreviewandmetaanalysis‏ ‎‡A Accuracy of machine learning algorithms for the assessment of upper-limb motor impairments in patients with post-stroke hemiparesis: a systematic review and meta-analysis‏ ‎‡9 1‏
946 ‎‡a b‏ ‎‡9 1‏
947 ‎‡a MX‏ ‎‡9 1‏
947 ‎‡a Meksyk‏ ‎‡9 1‏
948 ‎‡a spa‏ ‎‡9 1‏
970 ‎‡a medycyna‏ ‎‡A Medycyna‏ ‎‡9 1‏
996 ‎‡2 BNCHL|10000000000000000184597
996 ‎‡2 ISNI|0000000078267750
996 ‎‡2 DNB|1057153729
996 ‎‡2 WKP|Q977666
996 ‎‡2 SUDOC|084579730
996 ‎‡2 BNCHL|10000000000000000116296
996 ‎‡2 SUDOC|077266986
996 ‎‡2 DNB|1057221856
996 ‎‡2 NTA|13150018X
996 ‎‡2 LC|n 90706910
996 ‎‡2 WKP|Q960103
996 ‎‡2 NTA|327194383
996 ‎‡2 BNCHL|10000000000000000048847
996 ‎‡2 LC|n 2014052223
996 ‎‡2 SUDOC|153435976
996 ‎‡2 WKP|Q60316636
996 ‎‡2 BNCHL|10000000000000000143291
996 ‎‡2 WKP|Q5983297
996 ‎‡2 WKP|Q10321709
996 ‎‡2 DNB|1237002931
996 ‎‡2 LC|n 93051793
996 ‎‡2 WKP|Q27507661
996 ‎‡2 ISNI|0000000060553329
996 ‎‡2 BNE|XX823080
996 ‎‡2 NTA|260059307
996 ‎‡2 LC|no2021075892
996 ‎‡2 WKP|Q29640668
996 ‎‡2 DNB|1097299171
996 ‎‡2 WKP|Q87587352
996 ‎‡2 WKP|Q88939300
996 ‎‡2 SUDOC|145736318
996 ‎‡2 WKP|Q27530902
996 ‎‡2 WKP|Q122478879
996 ‎‡2 BIBSYS|90903793
996 ‎‡2 WKP|Q1402349
996 ‎‡2 WKP|Q55728856
996 ‎‡2 WKP|Q88289495
996 ‎‡2 DNB|1184824231
996 ‎‡2 BNCHL|10000000000000000028292
996 ‎‡2 WKP|Q129250971
996 ‎‡2 DNB|1060662353
996 ‎‡2 BNCHL|10000000000000000162044
996 ‎‡2 WKP|Q64819096
996 ‎‡2 BNE|XX1745283
996 ‎‡2 LC|no2009004868
996 ‎‡2 WKP|Q125301232
996 ‎‡2 BNCHL|10000000000000000075442
996 ‎‡2 BNE|XX1051861
996 ‎‡2 BNCHL|10000000000000000195148
996 ‎‡2 ISNI|0000000388729279
996 ‎‡2 WKP|Q2465298
996 ‎‡2 WKP|Q86299275
996 ‎‡2 WKP|Q1146506
996 ‎‡2 WKP|Q33529105
996 ‎‡2 BNC|981058612753506706
996 ‎‡2 LC|no2014015353
996 ‎‡2 JPG|500669601
996 ‎‡2 WKP|Q5982618
996 ‎‡2 LC|no2014114502
996 ‎‡2 DNB|1102220752
996 ‎‡2 WKP|Q109326824
996 ‎‡2 WKP|Q3840966
996 ‎‡2 BNE|XX1204958
996 ‎‡2 NTA|087258358
996 ‎‡2 BNE|XX949465
996 ‎‡2 SUDOC|276448324
996 ‎‡2 BNCHL|10000000000000000043224
996 ‎‡2 WKP|Q5984442
996 ‎‡2 WKP|Q20022981
996 ‎‡2 ISNI|0000000031556037
996 ‎‡2 SUDOC|175019045
996 ‎‡2 BAV|495_107048
996 ‎‡2 WKP|Q122417216
996 ‎‡2 WKP|Q20873577
996 ‎‡2 WKP|Q99883999
996 ‎‡2 WKP|Q57931376
996 ‎‡2 BNE|XX5601167
996 ‎‡2 WKP|Q107451700
996 ‎‡2 WKP|Q6700213
996 ‎‡2 LC|ns2014002187
996 ‎‡2 WKP|Q91741213
996 ‎‡2 BNE|XX1662390
996 ‎‡2 DNB|1193590345
996 ‎‡2 BNCHL|10000000000000000049839
996 ‎‡2 WKP|Q351430
996 ‎‡2 LC|n 2009181428
996 ‎‡2 BNCHL|10000000000000000819748
996 ‎‡2 BNCHL|10000000000000000087803
996 ‎‡2 BNCHL|10000000000000000087804
996 ‎‡2 DNB|1057126365
996 ‎‡2 BNC|981061001003306706
996 ‎‡2 WKP|Q63430730
996 ‎‡2 DNB|119216558
996 ‎‡2 JPG|500274122
996 ‎‡2 WKP|Q100311365
996 ‎‡2 WKP|Q41250893
996 ‎‡2 WKP|Q102211956
996 ‎‡2 WKP|Q967283
996 ‎‡2 WKP|Q105082933
996 ‎‡2 WKP|Q59688377
996 ‎‡2 WKP|Q93431064
996 ‎‡2 WKP|Q47545581
996 ‎‡2 WKP|Q5963276
996 ‎‡2 ISNI|0000000431000812
996 ‎‡2 BNCHL|10000000000000000801459
997 ‎‡a 0 0 lived 0 0‏ ‎‡9 1‏