MIC
Collection
Medical Image Computing
•
4 items
•
Updated
•
1
Error code: UnexpectedError
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ID
int64 | Pregnancies
int64 | Glucose
int64 | BloodPressure
int64 | SkinThickness
int64 | Insulin
int64 | BMI
float64 | DiabetesPedigreeFunction
float64 | Age
int64 | Outcome
int64 |
---|---|---|---|---|---|---|---|---|---|
235 | 4 | 171 | 72 | 29 | 155 | 43.6 | 0.479 | 26 | 1 |
686 | 3 | 130 | 64 | 29 | 155 | 23.1 | 0.314 | 22 | 0 |
568 | 4 | 154 | 72 | 29 | 126 | 31.3 | 0.338 | 37 | 0 |
236 | 7 | 181 | 84 | 21 | 192 | 35.9 | 0.586 | 51 | 1 |
211 | 0 | 147 | 85 | 54 | 155 | 42.8 | 0.375 | 24 | 0 |
564 | 0 | 91 | 80 | 29 | 155 | 32.4 | 0.601 | 27 | 0 |
239 | 0 | 104 | 76 | 29 | 155 | 18.4 | 0.582 | 27 | 0 |
578 | 10 | 133 | 68 | 29 | 155 | 27 | 0.245 | 36 | 0 |
382 | 1 | 109 | 60 | 8 | 182 | 25.4 | 0.947 | 21 | 0 |
368 | 3 | 81 | 86 | 16 | 66 | 27.5 | 0.306 | 22 | 0 |
342 | 1 | 121 | 68 | 35 | 155 | 32 | 0.389 | 22 | 0 |
513 | 2 | 91 | 62 | 29 | 155 | 27.3 | 0.525 | 22 | 0 |
231 | 6 | 134 | 80 | 37 | 370 | 46.2 | 0.238 | 46 | 1 |
115 | 4 | 146 | 92 | 29 | 155 | 31.2 | 0.539 | 61 | 1 |
677 | 0 | 93 | 60 | 29 | 155 | 35.3 | 0.263 | 25 | 0 |
547 | 4 | 131 | 68 | 21 | 166 | 33.1 | 0.16 | 28 | 0 |
237 | 0 | 179 | 90 | 27 | 155 | 44.1 | 0.686 | 23 | 1 |
100 | 1 | 163 | 72 | 29 | 155 | 39 | 1.222 | 33 | 1 |
528 | 0 | 117 | 66 | 31 | 188 | 30.8 | 0.493 | 22 | 0 |
126 | 3 | 120 | 70 | 30 | 135 | 42.9 | 0.452 | 30 | 0 |
290 | 0 | 78 | 88 | 29 | 40 | 36.9 | 0.434 | 21 | 0 |
609 | 1 | 111 | 62 | 13 | 182 | 24 | 0.138 | 23 | 0 |
234 | 3 | 74 | 68 | 28 | 45 | 29.7 | 0.293 | 23 | 0 |
453 | 2 | 119 | 72 | 29 | 155 | 19.6 | 0.832 | 72 | 0 |
703 | 2 | 129 | 72 | 29 | 155 | 38.5 | 0.304 | 41 | 0 |
392 | 1 | 131 | 64 | 14 | 415 | 23.7 | 0.389 | 21 | 0 |
40 | 3 | 180 | 64 | 25 | 70 | 34 | 0.271 | 26 | 0 |
324 | 2 | 112 | 75 | 32 | 155 | 35.7 | 0.148 | 21 | 0 |
147 | 2 | 106 | 64 | 35 | 119 | 30.5 | 1.4 | 34 | 0 |
150 | 1 | 136 | 74 | 50 | 204 | 37.4 | 0.399 | 24 | 0 |
662 | 8 | 167 | 106 | 46 | 231 | 37.6 | 0.165 | 43 | 1 |
371 | 0 | 118 | 64 | 23 | 89 | 32.457464 | 1.731 | 21 | 0 |
477 | 7 | 114 | 76 | 17 | 110 | 23.8 | 0.466 | 31 | 0 |
596 | 0 | 67 | 76 | 29 | 155 | 45.3 | 0.194 | 46 | 0 |
734 | 2 | 105 | 75 | 29 | 155 | 23.3 | 0.56 | 53 | 0 |
680 | 2 | 56 | 56 | 28 | 45 | 24.2 | 0.332 | 22 | 0 |
414 | 0 | 138 | 60 | 35 | 167 | 34.6 | 0.534 | 21 | 1 |
303 | 5 | 115 | 98 | 29 | 155 | 52.9 | 0.209 | 28 | 1 |
455 | 14 | 175 | 62 | 30 | 155 | 33.6 | 0.212 | 38 | 1 |
394 | 4 | 158 | 78 | 29 | 155 | 32.9 | 0.803 | 31 | 1 |
631 | 0 | 102 | 78 | 40 | 90 | 34.5 | 0.238 | 24 | 0 |
620 | 2 | 112 | 86 | 42 | 160 | 38.4 | 0.246 | 28 | 0 |
347 | 3 | 116 | 72 | 29 | 155 | 23.5 | 0.187 | 23 | 0 |
635 | 13 | 104 | 72 | 29 | 155 | 31.2 | 0.465 | 38 | 1 |
593 | 2 | 82 | 52 | 22 | 115 | 28.5 | 1.699 | 25 | 0 |
192 | 7 | 159 | 66 | 29 | 155 | 30.4 | 0.383 | 36 | 1 |
96 | 2 | 92 | 62 | 28 | 155 | 31.6 | 0.13 | 24 | 0 |
197 | 3 | 107 | 62 | 13 | 48 | 22.9 | 0.678 | 23 | 1 |
30 | 5 | 109 | 75 | 26 | 155 | 36 | 0.546 | 60 | 0 |
401 | 6 | 137 | 61 | 29 | 155 | 24.2 | 0.151 | 55 | 0 |
247 | 0 | 165 | 90 | 33 | 680 | 52.3 | 0.427 | 23 | 0 |
273 | 1 | 71 | 78 | 50 | 45 | 33.2 | 0.422 | 21 | 0 |
672 | 10 | 68 | 106 | 23 | 49 | 35.5 | 0.285 | 47 | 0 |
468 | 8 | 120 | 72 | 29 | 155 | 30 | 0.183 | 38 | 1 |
90 | 1 | 80 | 55 | 29 | 155 | 19.1 | 0.258 | 21 | 0 |
549 | 4 | 189 | 110 | 31 | 155 | 28.5 | 0.68 | 37 | 0 |
144 | 4 | 154 | 62 | 31 | 284 | 32.8 | 0.237 | 23 | 0 |
214 | 9 | 112 | 82 | 32 | 175 | 34.2 | 0.26 | 36 | 1 |
10 | 4 | 110 | 92 | 29 | 155 | 37.6 | 0.191 | 30 | 0 |
13 | 1 | 189 | 60 | 23 | 846 | 30.1 | 0.398 | 59 | 1 |
253 | 0 | 86 | 68 | 32 | 155 | 35.8 | 0.238 | 25 | 0 |
345 | 8 | 126 | 88 | 36 | 108 | 38.5 | 0.349 | 49 | 0 |
244 | 2 | 146 | 76 | 35 | 194 | 38.2 | 0.329 | 29 | 0 |
28 | 13 | 145 | 82 | 19 | 110 | 22.2 | 0.245 | 57 | 0 |
732 | 2 | 174 | 88 | 37 | 120 | 44.5 | 0.646 | 24 | 1 |
557 | 8 | 110 | 76 | 29 | 155 | 27.8 | 0.237 | 58 | 0 |
367 | 0 | 101 | 64 | 17 | 155 | 21 | 0.252 | 21 | 0 |
630 | 7 | 114 | 64 | 29 | 155 | 27.4 | 0.732 | 34 | 1 |
696 | 3 | 169 | 74 | 19 | 125 | 29.9 | 0.268 | 31 | 1 |
712 | 10 | 129 | 62 | 36 | 155 | 41.2 | 0.441 | 38 | 1 |
689 | 1 | 144 | 82 | 46 | 180 | 46.1 | 0.335 | 46 | 1 |
633 | 1 | 128 | 82 | 17 | 183 | 27.5 | 0.115 | 22 | 0 |
275 | 2 | 100 | 70 | 52 | 57 | 40.5 | 0.677 | 25 | 0 |
669 | 9 | 154 | 78 | 30 | 100 | 30.9 | 0.164 | 45 | 0 |
7 | 10 | 115 | 72 | 29 | 155 | 35.3 | 0.134 | 29 | 0 |
289 | 5 | 108 | 72 | 43 | 75 | 36.1 | 0.263 | 33 | 0 |
25 | 10 | 125 | 70 | 26 | 115 | 31.1 | 0.205 | 41 | 1 |
296 | 2 | 146 | 70 | 38 | 360 | 28 | 0.337 | 29 | 1 |
285 | 7 | 136 | 74 | 26 | 135 | 26 | 0.647 | 51 | 0 |
571 | 2 | 130 | 96 | 29 | 155 | 22.6 | 0.268 | 21 | 0 |
654 | 1 | 106 | 70 | 28 | 135 | 34.2 | 0.142 | 22 | 0 |
519 | 6 | 129 | 90 | 7 | 326 | 19.6 | 0.582 | 60 | 0 |
652 | 5 | 123 | 74 | 40 | 77 | 34.1 | 0.269 | 28 | 0 |
396 | 3 | 96 | 56 | 34 | 115 | 24.7 | 0.944 | 39 | 0 |
552 | 6 | 114 | 88 | 29 | 155 | 27.8 | 0.247 | 66 | 0 |
337 | 5 | 115 | 76 | 29 | 155 | 31.2 | 0.343 | 44 | 1 |
27 | 1 | 97 | 66 | 15 | 140 | 23.2 | 0.487 | 22 | 0 |
43 | 9 | 171 | 110 | 24 | 240 | 45.4 | 0.721 | 54 | 1 |
364 | 4 | 147 | 74 | 25 | 293 | 34.9 | 0.385 | 30 | 0 |
553 | 1 | 88 | 62 | 24 | 44 | 29.9 | 0.422 | 23 | 0 |
295 | 6 | 151 | 62 | 31 | 120 | 35.5 | 0.692 | 28 | 0 |
403 | 9 | 72 | 78 | 25 | 155 | 31.6 | 0.28 | 38 | 0 |
516 | 9 | 145 | 88 | 34 | 165 | 30.3 | 0.771 | 53 | 1 |
76 | 7 | 62 | 78 | 29 | 155 | 32.6 | 0.391 | 41 | 0 |
489 | 8 | 194 | 80 | 29 | 155 | 26.1 | 0.551 | 67 | 0 |
733 | 2 | 106 | 56 | 27 | 165 | 29 | 0.426 | 22 | 0 |
251 | 2 | 129 | 84 | 29 | 155 | 28 | 0.284 | 27 | 0 |
467 | 0 | 97 | 64 | 36 | 100 | 36.8 | 0.6 | 25 | 0 |
129 | 0 | 105 | 84 | 29 | 155 | 27.9 | 0.741 | 62 | 1 |
257 | 2 | 114 | 68 | 22 | 155 | 28.7 | 0.092 | 25 | 0 |
The dataset originates from the National Institute of Diabetes and Digestive and Kidney Diseases and aims to predict the presence or absence of diabetes through diagnostic measurements. The dataset selection adheres to specific constraints imposed on instances drawn from a more extensive database. Notably, all patients represented in this dataset are females aged at least 21, with a Pima Indian heritage.
git clone git@hf.co:datasets/MuGeminorum/Pima
from datasets import load_dataset
dataset = load_dataset("MuGeminorum/Pima")
for item in dataset["train"]:
print(item)
for item in dataset["validation"]:
print(item)
for item in dataset["test"]:
print(item)
https://www.modelscope.cn/datasets/MuGeminorum/Pima
[1] Pima Indians Diabetes Database
[2] Chapter IV ‐ Medical Signal Segmentation and Classification