Table 1. Overview of DATA-CARE and point allocation for scoring.
| Criteria | Score* | ||
|---|---|---|---|
| + |
± |
− |
|
| Study population | |||
| Recruitment | 5 | 2.5 | 0 |
| Inclusion and exclusion criteria | 5 | 2.5 | 0 |
| Baseline study population | 5 | 2.5 | 0 |
| Data | |||
| Data acquisition | 3 | 1.5 | 0 |
| Data set size and balance | 3 | 1.5 | 0 |
| Missing data | 3 | 1.5 | 0 |
| Data preprocessing | 3 | 1.5 | 0 |
| Feature derivation | 3 | 1.5 | 0 |
| Algorithm | |||
| Algorithm architecture | 5 | 2.5 | 0 |
| Algorithm development | 5 | 2.5 | 0 |
| Algorithm evaluation | 5 | 2.5 | 0 |
| Outcome | |||
| Definition of outcome | 5 | 2.5 | 0 |
| Method and setting of outcome assessment | 5 | 2.5 | 0 |
| Outcome labelling | 5 | 2.5 | 0 |
| Report transparency | |||
| Presentation of data and findings | 5 | 2.5 | 0 |
| Reporting of results | 5 | 2.5 | 0 |
| Statistical analysis | 5 | 2.5 | 0 |
Adapted from Hayden et al and de Jonge et al with permission.12 25 26
*
Scoring symbols refer to maximum score (+), average score (±) and minimum score (−).
DATA-CARE, Data Assessment Tool for Algorithm Critical Appraisal and Robust Evidence.