This diabetes dataset is from AIM '94

Dataset Characteristics

Multivariate, Time-Series

Subject Area


Associated Tasks


Attribute Type

Categorical, Integer

# Instances


# Attributes



Additional Information

Diabetes patient records were obtained from two sources: an automatic electronic recording device and paper records. The automatic device had an internal clock to timestamp events, whereas the paper records only provided "logical time" slots (breakfast, lunch, dinner, bedtime). For paper records, fixed times were assigned to breakfast (08:00), lunch (12:00), dinner (18:00), and bedtime (22:00). Thus paper records have fictitious uniform recording times whereas electronic records have more realistic time stamps. Diabetes files consist of four fields per record. Each field is separated by a tab and each record is separated by a newline. File Names and format: (1) Date in MM-DD-YYYY format (2) Time in XX:YY format (3) Code (4) Value The Code field is deciphered as follows: 33 = Regular insulin dose 34 = NPH insulin dose 35 = UltraLente insulin dose 48 = Unspecified blood glucose measurement 57 = Unspecified blood glucose measurement 58 = Pre-breakfast blood glucose measurement 59 = Post-breakfast blood glucose measurement 60 = Pre-lunch blood glucose measurement 61 = Post-lunch blood glucose measurement 62 = Pre-supper blood glucose measurement 63 = Post-supper blood glucose measurement 64 = Pre-snack blood glucose measurement 65 = Hypoglycemic symptoms 66 = Typical meal ingestion 67 = More-than-usual meal ingestion 68 = Less-than-usual meal ingestion 69 = Typical exercise activity 70 = More-than-usual exercise activity 71 = Less-than-usual exercise activity 72 = Unspecified special event The diabetes files consist of four fields per record. Each field is separated by a tab and each record is separated by a newline.File Names and format:(1) Date in MM-DD-YYYY format(2) Time in XX:YY format(3) Code(4) Value

102 citations


Michael Kahn


This dataset is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) license.

This allows for the sharing and adaptation of the datasets for any purpose, provided that the appropriate credit is given.

By using the UCI Machine Learning Repository, you acknowledge and accept the cookies and privacy practices used by the UCI Machine Learning Repository.

Learn More