
    Given a medical scan with n distinct anatomical regions of interest, determine the number of different ways these regions can be grouped for parallel processing in an automated disease detection system, where each region can be analyzed either independently or combined with other regions based on tissue similarities. Each anatomical region must be included in exactly one analysis group, and the grouping must ensure comprehensive coverage of all regions for thorough disease screening.
    

    
def bell_number(n):
    """
    Given a medical scan with n distinct anatomical regions of interest, determine the number of different ways these regions can be grouped for parallel processing in an automated disease detection system, where each region can be analyzed either independently or combined with other regions based on tissue similarities. Each anatomical region must be included in exactly one analysis group, and the grouping must ensure comprehensive coverage of all regions for thorough disease screening.
    

    """
def bell_number(n):
    """
    Given a medical scan with n distinct anatomical regions of interest, determine the number of different ways these regions can be grouped for parallel processing in an automated disease detection system, where each region can be analyzed either independently or combined with other regions based on tissue similarities. Each anatomical region must be included in exactly one analysis group, and the grouping must ensure comprehensive coverage of all regions for thorough disease screening.
    

    """
    bell = [[0 for i in range(n + 1)] for j in range(n + 1)]
    bell[0][0] = 1
    for i in range(1, n + 1):
        bell[i][0] = bell[i - 1][i - 1]
        for j in range(1, i + 1):
            bell[i][j] = bell[i - 1][j - 1] + bell[i][j - 1]
    return bell[n][0]