
    Given a patient monitoring system that tracks readmission risk scores across n follow-up assessments, determine the number of possible risk score patterns where each subsequent assessment score must be at least double the previous score while not exceeding the maximum severity score m on the standardized health risk scale. Each risk score must be a positive integer, and the pattern must account for all n scheduled assessments.
    

    
def get_total_number_of_sequences(m, n):
    """
    Given a patient monitoring system that tracks readmission risk scores across n follow-up assessments, determine the number of possible risk score patterns where each subsequent assessment score must be at least double the previous score while not exceeding the maximum severity score m on the standardized health risk scale. Each risk score must be a positive integer, and the pattern must account for all n scheduled assessments.
    

    """
def get_total_number_of_sequences(m, n):
    """
    Given a patient monitoring system that tracks readmission risk scores across n follow-up assessments, determine the number of possible risk score patterns where each subsequent assessment score must be at least double the previous score while not exceeding the maximum severity score m on the standardized health risk scale. Each risk score must be a positive integer, and the pattern must account for all n scheduled assessments.
    

    """
    T = [[0 for i in range(n + 1)] for i in range(m + 1)]
    for i in range(m + 1):
        for j in range(n + 1):
            if i == 0 or j == 0:
                T[i][j] = 0
            elif i < j:
                T[i][j] = 0
            elif j == 1:
                T[i][j] = i
            else:
                T[i][j] = T[i - 1][j] + T[i // 2][j - 1]
    return T[m][n]