# Hypercholesterolemia

## Description&#x20;

Hypercholesterolemia risk is the likelihood that the user has abnormally high cholesterol levels (defined as a total cholesterol (TC)-to-high density lipoprotein (HDL) cholesterol (“good cholesterol”) ratio of 4.1 or higher) and corresponds to the percentage of people with the user’s risk profile that have an abnormally high TC/HDL ratio. BitDoctor.ai determines the user’s risk of hypercholesterolemia based on blood flow patterns and demographic information.

## Participants&#x20;

Adults (18+ years of age) recruited from several hospital health clinics.

## Additional Data Collection

Subjects also received a blood test at the same clinic visit where their cholesterol levels were measured.

## Modeling Approach

Blood flow signal was extracted and processed from facial video, and then blood flow features were extracted from blood flow signal.&#x20;

Feature selection was carried out on blood flow and demographic features to identify features predictive of hypercholesterolemia. A machine-learning based classifier was then created to predict whether an individual has hypercholesterolemia based on these features.&#x20;

The model was created/trained using 80% of the subjects. The distribution of sex and hypercholesterolemia status in this group is summarized in Table 17.

|         Subjects in videos        |        Composition        |
| :-------------------------------: | :-----------------------: |
|          Sex distribution         | 46.5 % Male; 53.5% Female |
| Hypercholesterolemia distribution |            30%            |

&#x20;                                       *Table 17: Hypercholesterolemia distribution of training set*

## Model Performance&#x20;

The Hypercholesterolemia Risk model was then validated for accuracy on an independent portion of the dataset (n=700) that was not used in training - validation set. Then the final accuracy was obtained on an independent portion of the dataset (n=700) that was not used in training - test set. The distribution of sex and hypercholesterolemia status in these groups is summarized in Table 18.

| Subjects in videos                | Composition in Validation | Composition in Test      |
| --------------------------------- | ------------------------- | ------------------------ |
| Sex distribution                  | 47.8% Male; 52.2% Female  | 46.6% Male; 53.4% Female |
| Hypercholesterolemia distribution | 30%                       | 30%                      |

&#x20;                             *Table 18: Hypercholesterolemia distribution of validation and test sets*

The accuracy on the test set calculated as area under the curve was 80.3% as shown in Figure 22.

<figure><img src="https://101746475-files.gitbook.io/~/files/v0/b/gitbook-x-prod.appspot.com/o/spaces%2FbQD4HPZ4Ef0SW88Edu1U%2Fuploads%2FZzgsOcpcqTwbSxNGlFbS%2Fd37.jpg?alt=media&#x26;token=ff48af2f-7874-4082-906e-015a089ec34c" alt="" width="563"><figcaption></figcaption></figure>

&#x20;                                           *Figure 22: AUC of Hypercholesterolemia risk prediction*

Predictions are displayed to the user as a percentage likelihood of having hypercholesterolemia. A percentage of 45% or more suggests a risk of diabetes, while 55% or more suggests high risk of diabetes.
