vertebral | synthetic features on linear models | Machine Learning library

I have dataset in the form of xml and I want to convert tis into tabular form so that I can move further in my project. Given are the data set and I have also mentioned the code which I have written.

I created a simple word feature detector. So far been able to find particular features (jumbled within) the string, but the algorithm get confused with certain sequences of words. Let me illustrate:

I have the following data frame:

I am doing an analysis of automated volumetric fat measurements in different body compartments on abdominal CT scans. Measurements are taken at consecutive vertebral levels for each patient's scan, and each patient has multiple compartments measured separately (subcutaneous and visceral). Prior research has identified the ratio of visceral/subcutaneous fat measurements to be of particular interest.

I am having a difficult time trying to calculate this ratio in my dataset. In this example code there are six entries per patient. Each entry is associated with a measured fat volume of a compartment at a vertebral level.

What I want to do is create a new measurement type - 'vat/sat' - that is just a ratio of the two measures at each of the three vertebral levels. In essence, I am trying to insert three new observations per patient that are associated with a new factor level and value that is an operation of other values. Any help is greatly appreciated.

I have the following data frame:

i'm searching for a Javascript framework that can help me to add legends to images i have in my database. What i have : -> a JSON file that contains all the legends with its coordinates on the image.

Ex. i have this image : 225_4.png

the JSON content that suits the image : {image": "225_4.png", "height": 37.16999999999996, "width": 65.46599999999998, "y": 67.57999999999993, "x": -62.54000000000005, "legend": "Vertebral _RL_ foramen _RL_ "}

it's a web app so i'm developping in Javascript.