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id
int64 0
100k
| age
int64 10.8k
23.7k
| gender
int64 1
2
| height
int64 55
250
| weight
float64 10
200
| ap_hi
int64 -150
16k
| ap_lo
int64 -70
11k
| cholesterol
int64 1
3
| gluc
int64 1
3
| smoke
int64 0
1
| alco
int64 0
1
| active
int64 0
1
| cardio
int64 0
1
|
---|---|---|---|---|---|---|---|---|---|---|---|---|
0 | 18,393 | 2 | 168 | 62 | 110 | 80 | 1 | 1 | 0 | 0 | 1 | 0 |
1 | 20,228 | 1 | 156 | 85 | 140 | 90 | 3 | 1 | 0 | 0 | 1 | 1 |
2 | 18,857 | 1 | 165 | 64 | 130 | 70 | 3 | 1 | 0 | 0 | 0 | 1 |
3 | 17,623 | 2 | 169 | 82 | 150 | 100 | 1 | 1 | 0 | 0 | 1 | 1 |
4 | 17,474 | 1 | 156 | 56 | 100 | 60 | 1 | 1 | 0 | 0 | 0 | 0 |
8 | 21,914 | 1 | 151 | 67 | 120 | 80 | 2 | 2 | 0 | 0 | 0 | 0 |
9 | 22,113 | 1 | 157 | 93 | 130 | 80 | 3 | 1 | 0 | 0 | 1 | 0 |
12 | 22,584 | 2 | 178 | 95 | 130 | 90 | 3 | 3 | 0 | 0 | 1 | 1 |
13 | 17,668 | 1 | 158 | 71 | 110 | 70 | 1 | 1 | 0 | 0 | 1 | 0 |
14 | 19,834 | 1 | 164 | 68 | 110 | 60 | 1 | 1 | 0 | 0 | 0 | 0 |
15 | 22,530 | 1 | 169 | 80 | 120 | 80 | 1 | 1 | 0 | 0 | 1 | 0 |
16 | 18,815 | 2 | 173 | 60 | 120 | 80 | 1 | 1 | 0 | 0 | 1 | 0 |
18 | 14,791 | 2 | 165 | 60 | 120 | 80 | 1 | 1 | 0 | 0 | 0 | 0 |
21 | 19,809 | 1 | 158 | 78 | 110 | 70 | 1 | 1 | 0 | 0 | 1 | 0 |
23 | 14,532 | 2 | 181 | 95 | 130 | 90 | 1 | 1 | 1 | 1 | 1 | 0 |
24 | 16,782 | 2 | 172 | 112 | 120 | 80 | 1 | 1 | 0 | 0 | 0 | 1 |
25 | 21,296 | 1 | 170 | 75 | 130 | 70 | 1 | 1 | 0 | 0 | 0 | 0 |
27 | 16,747 | 1 | 158 | 52 | 110 | 70 | 1 | 3 | 0 | 0 | 1 | 0 |
28 | 17,482 | 1 | 154 | 68 | 100 | 70 | 1 | 1 | 0 | 0 | 0 | 0 |
29 | 21,755 | 2 | 162 | 56 | 120 | 70 | 1 | 1 | 1 | 0 | 1 | 0 |
30 | 19,778 | 2 | 163 | 83 | 120 | 80 | 1 | 1 | 0 | 0 | 1 | 0 |
31 | 21,413 | 1 | 157 | 69 | 130 | 80 | 1 | 1 | 0 | 0 | 1 | 0 |
32 | 23,046 | 1 | 158 | 90 | 145 | 85 | 2 | 2 | 0 | 0 | 1 | 1 |
33 | 23,376 | 2 | 156 | 45 | 110 | 60 | 1 | 1 | 0 | 0 | 1 | 0 |
35 | 16,608 | 1 | 170 | 68 | 150 | 90 | 3 | 1 | 0 | 0 | 1 | 1 |
36 | 14,453 | 1 | 153 | 65 | 130 | 100 | 2 | 1 | 0 | 0 | 1 | 0 |
37 | 19,559 | 1 | 156 | 59 | 130 | 90 | 1 | 1 | 0 | 0 | 1 | 0 |
38 | 18,085 | 1 | 159 | 78 | 120 | 80 | 1 | 1 | 0 | 0 | 1 | 0 |
39 | 14,574 | 2 | 166 | 66 | 120 | 80 | 1 | 1 | 0 | 0 | 1 | 0 |
40 | 21,057 | 2 | 169 | 74 | 130 | 70 | 1 | 3 | 0 | 0 | 0 | 0 |
42 | 18,291 | 1 | 155 | 105 | 120 | 80 | 3 | 1 | 0 | 0 | 1 | 1 |
43 | 23,186 | 1 | 169 | 71 | 140 | 90 | 3 | 1 | 0 | 0 | 1 | 1 |
44 | 14,605 | 1 | 159 | 60 | 110 | 70 | 1 | 1 | 0 | 0 | 1 | 0 |
45 | 20,652 | 1 | 160 | 73 | 130 | 85 | 1 | 1 | 0 | 0 | 0 | 1 |
46 | 21,940 | 2 | 173 | 82 | 140 | 90 | 3 | 1 | 0 | 0 | 0 | 1 |
47 | 20,404 | 1 | 163 | 55 | 120 | 80 | 1 | 1 | 0 | 0 | 1 | 0 |
49 | 18,328 | 2 | 175 | 95 | 120 | 80 | 1 | 1 | 0 | 0 | 1 | 0 |
51 | 17,976 | 1 | 164 | 70 | 130 | 90 | 1 | 1 | 0 | 0 | 1 | 0 |
52 | 23,388 | 2 | 162 | 72 | 130 | 80 | 1 | 1 | 1 | 0 | 1 | 1 |
53 | 18,126 | 1 | 165 | 70 | 140 | 90 | 1 | 1 | 0 | 0 | 1 | 1 |
54 | 19,848 | 1 | 157 | 62 | 110 | 70 | 1 | 1 | 0 | 0 | 0 | 0 |
56 | 18,274 | 1 | 178 | 68 | 110 | 80 | 1 | 1 | 0 | 0 | 1 | 1 |
57 | 21,475 | 2 | 171 | 69 | 140 | 90 | 1 | 1 | 0 | 0 | 1 | 1 |
58 | 20,556 | 2 | 159 | 63 | 120 | 60 | 1 | 1 | 0 | 0 | 1 | 1 |
59 | 19,764 | 1 | 154 | 50 | 170 | 80 | 3 | 1 | 0 | 0 | 1 | 1 |
60 | 17,471 | 1 | 162 | 64 | 140 | 90 | 1 | 1 | 0 | 0 | 1 | 1 |
61 | 18,207 | 1 | 162 | 107 | 150 | 90 | 2 | 1 | 0 | 0 | 1 | 1 |
62 | 18,535 | 2 | 168 | 69 | 120 | 80 | 1 | 1 | 0 | 0 | 0 | 0 |
63 | 16,864 | 2 | 175 | 70 | 120 | 80 | 2 | 1 | 0 | 0 | 1 | 0 |
64 | 16,045 | 1 | 170 | 69 | 120 | 70 | 1 | 1 | 0 | 0 | 1 | 0 |
65 | 18,238 | 1 | 160 | 75 | 100 | 60 | 1 | 1 | 0 | 0 | 0 | 0 |
66 | 18,338 | 1 | 169 | 84 | 150 | 100 | 1 | 1 | 0 | 0 | 1 | 1 |
67 | 19,575 | 2 | 166 | 85 | 150 | 100 | 1 | 1 | 0 | 0 | 1 | 1 |
68 | 14,507 | 1 | 165 | 77 | 135 | 90 | 3 | 3 | 0 | 0 | 1 | 1 |
69 | 19,679 | 1 | 152 | 79 | 130 | 90 | 1 | 1 | 0 | 0 | 1 | 1 |
70 | 21,787 | 2 | 165 | 73 | 125 | 90 | 1 | 1 | 0 | 0 | 0 | 0 |
71 | 17,407 | 1 | 171 | 76 | 90 | 60 | 1 | 2 | 0 | 0 | 1 | 0 |
72 | 22,748 | 1 | 165 | 90 | 120 | 80 | 1 | 1 | 0 | 0 | 0 | 1 |
73 | 15,901 | 2 | 172 | 84 | 140 | 90 | 1 | 1 | 1 | 0 | 1 | 1 |
74 | 20,431 | 1 | 164 | 64 | 180 | 90 | 1 | 1 | 1 | 0 | 1 | 1 |
77 | 19,105 | 1 | 159 | 58 | 110 | 70 | 1 | 1 | 0 | 0 | 1 | 0 |
79 | 20,960 | 2 | 165 | 75 | 180 | 90 | 3 | 1 | 0 | 0 | 1 | 1 |
81 | 20,330 | 2 | 187 | 115 | 130 | 90 | 1 | 1 | 0 | 1 | 1 | 0 |
83 | 22,587 | 1 | 170 | 85 | 120 | 80 | 1 | 1 | 0 | 0 | 1 | 0 |
86 | 20,649 | 2 | 169 | 71 | 120 | 80 | 1 | 1 | 0 | 0 | 1 | 1 |
87 | 21,752 | 1 | 148 | 80 | 130 | 90 | 1 | 1 | 0 | 0 | 1 | 1 |
88 | 19,148 | 2 | 170 | 69 | 130 | 80 | 1 | 1 | 0 | 0 | 1 | 0 |
90 | 22,099 | 2 | 171 | 97 | 150 | 100 | 3 | 1 | 1 | 0 | 1 | 1 |
92 | 19,739 | 1 | 152 | 76 | 160 | 100 | 1 | 2 | 0 | 0 | 1 | 1 |
94 | 20,882 | 1 | 157 | 53 | 110 | 70 | 1 | 1 | 0 | 0 | 0 | 1 |
95 | 23,589 | 1 | 155 | 57 | 120 | 80 | 1 | 1 | 0 | 0 | 1 | 1 |
96 | 21,874 | 2 | 179 | 95 | 150 | 90 | 1 | 1 | 0 | 0 | 1 | 1 |
97 | 23,433 | 1 | 156 | 58 | 110 | 70 | 1 | 1 | 0 | 0 | 1 | 0 |
100 | 21,934 | 1 | 157 | 77 | 140 | 90 | 1 | 1 | 0 | 0 | 1 | 1 |
103 | 16,039 | 2 | 180 | 90 | 140 | 90 | 2 | 2 | 0 | 0 | 0 | 0 |
104 | 20,484 | 1 | 158 | 75 | 130 | 90 | 1 | 1 | 0 | 0 | 0 | 1 |
105 | 20,397 | 2 | 188 | 105 | 120 | 80 | 1 | 1 | 0 | 0 | 1 | 1 |
106 | 21,865 | 1 | 160 | 68 | 140 | 90 | 1 | 1 | 0 | 0 | 1 | 1 |
107 | 18,241 | 1 | 173 | 82 | 140 | 90 | 1 | 1 | 0 | 0 | 1 | 1 |
108 | 20,370 | 2 | 164 | 74 | 140 | 85 | 1 | 1 | 0 | 0 | 0 | 1 |
109 | 16,591 | 1 | 159 | 49 | 120 | 70 | 1 | 1 | 0 | 0 | 1 | 0 |
111 | 19,029 | 1 | 155 | 64 | 120 | 70 | 1 | 1 | 0 | 0 | 1 | 0 |
113 | 19,642 | 1 | 158 | 75 | 120 | 80 | 1 | 1 | 0 | 0 | 1 | 1 |
114 | 19,570 | 1 | 152 | 110 | 160 | 90 | 1 | 1 | 0 | 0 | 1 | 1 |
115 | 22,636 | 1 | 178 | 93 | 130 | 90 | 1 | 1 | 0 | 0 | 0 | 1 |
116 | 18,352 | 1 | 156 | 55 | 100 | 60 | 1 | 1 | 0 | 0 | 1 | 0 |
117 | 21,909 | 1 | 156 | 75 | 150 | 90 | 2 | 2 | 0 | 0 | 1 | 1 |
119 | 19,663 | 2 | 166 | 94 | 140 | 90 | 2 | 3 | 0 | 0 | 1 | 1 |
121 | 23,204 | 1 | 151 | 92 | 130 | 90 | 1 | 1 | 0 | 0 | 0 | 1 |
122 | 19,480 | 2 | 172 | 87 | 120 | 80 | 1 | 1 | 0 | 0 | 0 | 0 |
123 | 23,230 | 1 | 160 | 82 | 140 | 100 | 1 | 1 | 0 | 0 | 1 | 0 |
124 | 19,557 | 1 | 164 | 103 | 140 | 90 | 3 | 3 | 0 | 0 | 0 | 1 |
125 | 18,752 | 2 | 173 | 76 | 150 | 90 | 1 | 1 | 0 | 0 | 1 | 1 |
126 | 22,821 | 2 | 168 | 80 | 160 | 100 | 1 | 1 | 0 | 0 | 1 | 0 |
127 | 15,946 | 2 | 185 | 88 | 133 | 89 | 2 | 3 | 0 | 0 | 1 | 0 |
129 | 21,076 | 1 | 158 | 53 | 110 | 70 | 1 | 1 | 0 | 0 | 1 | 0 |
131 | 19,258 | 2 | 165 | 65 | 110 | 70 | 1 | 1 | 0 | 0 | 1 | 0 |
132 | 18,410 | 1 | 165 | 99 | 150 | 110 | 1 | 1 | 0 | 0 | 0 | 1 |
133 | 21,860 | 2 | 170 | 100 | 120 | 80 | 1 | 1 | 0 | 0 | 0 | 1 |
134 | 17,363 | 1 | 167 | 71 | 120 | 80 | 2 | 1 | 0 | 1 | 1 | 1 |
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Age in Days, not years
Original Dataset from Kaggle(link here), only fixed CSV formatting
Dataset downloaded from here, and uploaded here, on HuggingFace.
Cardiovascular contains 70k samples(no duplicates!) which can be used to train an AI model to predict if a patient has heart disease or not.
You can find a somewhat trained model using the ANNA library here, it's not recommended for deployment though.
For more information on the dataset, view the original page here.
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