Sentence examples for make clinical Predictions from inspiring English sources

Although our results appear to be robust, they cannot be used to make clinical predictions.

For the subsection "Using Gene Expression Data to Make Clinical Predictions" (covering studies [6] and [7]), the main challenge is handling the Big Volume of the features (probes).

Table 1 Summary of Studies Covered Sections Data level(s) used Subsections Question level(s) answered Questions to be answered Using Micro Level Data – Molecules Molecular Using Gene Expression Data to Make Clinical Predictions Clinical What sub-type of cancer does a patient have?

The studies shown in this section using MRI data have shown that they can be useful in answering clinical questions as well as making clinical predictions.

All the studies presented in this section will cover data at the patient level and venture to answer clinical level questions including: Prediction of ICU readmission, prediction of patient mortality rate (after ICU discharge and 5 years) and making clinical predictions using data streams.

The C-values in Table 3 show that any weighting method yields a model that discriminates between a "yes" and "no" decision to start taking statins about as well as any other, consistent with Dawes' findings that "improper" linear models that use equal weighting are quite robust for making clinical predictions [44].

The availability of such data in the future will be instrumental in making clinical predictions using evolutionary models of tumor progression.

We then used the imputed data to make clinical outcome predictions with the published models, and the results were compared with the predictions made using the complete test data with no missing data.

Until more data are available, clinicians should be aware of the limitations and current areas of uncertainty regarding DXA and FRAX-derived osteoporotic fracture risk predictions when making clinical decisions in Asian populations.

Most existing predictive models for asthma development in children make predictions at a time unsuitable for making clinical impact.

More specifically, to be useful in routine clinical practice, a good predictive model should use clinical data, make prediction at a time suitable for making clinical impact, have high accuracy, and use an appropriate definition of asthma.