You have a text corpus stored in corpus variable. Your task is to display the vector for the 'medical' unigram in a TF-IDF model with unigrams, bigrams, and trigrams. To do this:

1. Import the TfidfVectorizer class to create a TF-IDF model.
2. Instantiate the TfidfVectorizer class as tfidf_vectorizer and configure it to include unigrams, bigrams, and trigrams.
3. Use the appropriate method of tfidf_vectorizer to generate a TF-IDF matrix from the 'Document' column in the corpus and store the result in tfidf_matrix.
4. Convert tfidf_matrix to a dense array and create a DataFrame from it, setting the unique features (terms) as its columns. Store the result in the tfidf_matrix_df variable.
5. Display the vector for 'medical' as an array.