set.rfcdata: Ultrasound profile preparation for random forest...

In Morphonodepredictivemodel/morphonode: The Morphonode Predictive Model for ultrasound signatures detection and malignancy prediction in vulvar cancer

Ultrasound profile preparation for random forest classification

Description

Prepare a new ultrasound profile for RFC prediction. This function includes missing values check and fix (see set.missing).

Usage

set.rfcdata(u, levels = NULL, ref = NULL, ...)

Arguments

u	New ultrasound profile generated by new.profile.
levels	A list of length 14, corresponding to the levels of each ultrasound variable. Needed for categorical variables (factors); for continuous variables, it should assume the nominal value of 0. The default levels variable mpm.levels can be used.
ref	Reference ultrasound features dataset as a (n, 14) data.frame, with n being the number of subjects (rows). The default simulated dataset mpm.us can be used.
...	Currently ignored.

Value

A list of 2 objects:

1. "ultrasound", ultrasound features vector;

2. "missing", indices of missing values (empty if no missing values are found).

Author(s)

Fernando Palluzzi [e-mail]

References

Fragomeni SM, Moro F, Palluzzi F, Mascilini F, Rufini V, Collarino A, Inzani F, Giacò L, Scambia G, Testa AC, Garganese G (2022). Evaluating the risk of inguinal lymph node metastases before surgery using the Morphonode Predictive Model: a prospective diagnostic study. Ultrasound xx Xxxxxxxxxx xxx Xxxxxxxxxx. 00(0):000-000. <https://doi.org/00.0000/00000000000000000000>

See Also

See set.rbmdata for robust binomial model data preparation. See also us.predict to launch all morphonode modules at once.

Examples

# Prepare a simulated malignant ultrasound profile
x <- new.profile(us.simulate(y = 1))

# Set the new profile for RFC prediction
u <- set.rfcdata(x, ref = mpm.us[, 2:15], levels = mpm.levels)
print(u)

Morphonodepredictivemodel/morphonode documentation built on Feb. 15, 2023, 4:51 a.m.