Sentence examples for categorized the time from inspiring English sources

We categorized the time to wound healing reported by the patient as < 1 week, 1 2 weeks, and > 2 weeks.

We categorized the time the health worker had worked in the facility at more than two years based on an inflection point seen in the data.

Although the accuracy of self-reported time of complete healing is uncertain, it should not have had a substantial impact on the results, since we categorized the time to healing.

We categorized the time of sample collection as morning (after midnight 1159 hours), afternoon (1200 1800 hours), and evening (1801 2359 hours), and calculated the geometric mean (GM) concentration for each collection time.

Instead of categorizing the time between surgeries into four groups we also investigated the time interval between the two THA procedures in each patient as a continuous variable.

However, categorizing the time axis into blocks of time effectively removes an important variable describing outcomes in the dynamic process of treatment, namely the continuity of change over time.

We categorized the predictor time to target temperature into tertiles of time from restoration of spontaneous circulation to esophageal temperature of not more than 34°C (<120, 120 to 220, and >220 minutes) because the assumption of a linear effect did not hold when used as a continuous variable despite standard transformations.

Calendar time was modelled using a restricted cubic spline, thereby avoiding linearity assumptions and loss of information from categorizing the continuous time variable [ 15].

In general, these damage identification methods can be categorized into the time and frequency domain approaches.

Clinical research projects (called clinical projects in brief) were defined based on two variables ("Type of research" and "Main content") categorized at the time of data collection using all available information (see Appendix 1 for details).

First, we learn how to categorize the sales time series into 'predictable' and 'random' based on structural, shape and relational features related to the products and the environment using meta learning approach.