0188-9532
0188-9532
S0188-95322020000300101
10.17488/rmib.41.3.1
Mexico
00
12
2020
00
12
2020
41
3
[
2007
17
10
10
1537-45
]
[
2010
26
1
1
721-44
]
[
2006
11
23-24
23-24
1085-92
]
[
2011
5
3
3
185-207
]
[
2006
359
4
4
1107-24
]
[
2002
14
2
2
140-8
]
[
2014
94
2
2
355-82
]
[
2002
60
S20-9
]
[
2010
24
17
17
1861-75
]
[
2006
24
6
6
667-72
]
[
2012
3
]
[
1991
1
4
4
379-86
]
[
2003
32
7
7
1201-17
]
[
2006
16
3
3
]
[
1972
94
4
4
1394-5
]
[
1972
94
25
25
8649-64
]
[
2011
3
1
1
33-53
]
[
1974
60
5
5
1877-84
]
[
1990
94
18
18
7162-70
]
[
2015
]
[
2006
78
3
3
235-62
]
[
2007
1
2
2
89-119
]
[
2002
74
1
1
47-97
]
[
2009
87
1
1
]
[
2017
]
[
2008
31
3
3
591-601
]
[
2006
83
2-3
2-3
81-90
]
[
2001
2
2
2
91-9
]
[
1992
20
^sSuppl 1
^sSuppl 1
Suppl 1
S1-S16
]
[
2016
31
2
2
206-13
]
[
2006
]
[
2006
26
159-90
]
[
2018
1
]
[
2009
361-2
]
[
1992
2
]
[
2000
10
10
10
2323-37
]
[
2003
67
4
4
]
[
1999
81
119-29
]
[
1987
4
9
9
973-7
]
[
2019
206-20
]
[
2000
2
^sSuppl 1
^sSuppl 1
Suppl 1
S35-41
]
[
2010
10
5
5
4558-76
]
[
2002
6
5
5
633-41
]
[
2015
8
1
1
171-92
]
[
2005
2
4
4
267-80
]
[
1999
46
5
5
604-32
]
[
2005
48
4
4
531-4
]
[
2000
]
[
1988
84
4
4
1013-23
]
[
2015
8
6
6
759-68
]
[
1968
4
1
1
79-86
]
[
2009
2
]
[
2001
449-77
]
[
2020
21
46
46
1−6
]
[
2015
3939-45
]
[
2019
273-5
]
[
2018
91-6
]
[
2020
53
80-7
]
[
2013
14
35
35
2349−2353
]
[
2013
37
55-60
]
[
2019
10
1
1
]
[
2016
3
1
1
1345-59
]
[
2018
270-9
]
[
2016
2818-26
]
[
2020
]
[
2020
]
[
2017
33
21
21
3387-95
]
[
2018
251-303
]
[
2004
44
1
1
1-12
]
[
2006
1015-21
]
[
2012
17
9
9
3558-78
]
[
2001
76
2
2
161-209
]
[
1996
77
15
15
3244-7
]
[
1990
94
12
12
4862-6
]
[
2011
16
9
9
3770-85
]
[
2007
75
1
1
]
[
2005
94
18
18
1881011-4
]
[
1999
18
1
1
1-24
]
[
2004
78-86
]
[
1997
245-53
]
[
2012
24
2
2
441-51
]
[
2020
]
[
Azure Machine Learning
2019
]
[
2019
110
12-22
]
[
2020
10
1
1
978-86
]
[
1995
14
2
2
1137-45
]
[
2016
37
3
3
181-200
]
[
2001
410
6825
6825
277-84
]