
    In a hospital's readmission prediction system, develop an algorithm that calculates the expected risk pattern value at position n in the patient return sequence, where each value is determined by the frequency of previous readmissions following the Newman-Conway pattern. The value at each position follows the rule where for n > 2, the nth number is equal to P(P(n-1)) + P(n-P(n-1)), where P(x) represents the value at position x in the sequence.
    

    
def sequence(n):
    """
    In a hospital's readmission prediction system, develop an algorithm that calculates the expected risk pattern value at position n in the patient return sequence, where each value is determined by the frequency of previous readmissions following the Newman-Conway pattern. The value at each position follows the rule where for n > 2, the nth number is equal to P(P(n-1)) + P(n-P(n-1)), where P(x) represents the value at position x in the sequence.
    

    """
def sequence(n):
    """
    In a hospital's readmission prediction system, develop an algorithm that calculates the expected risk pattern value at position n in the patient return sequence, where each value is determined by the frequency of previous readmissions following the Newman-Conway pattern. The value at each position follows the rule where for n > 2, the nth number is equal to P(P(n-1)) + P(n-P(n-1)), where P(x) represents the value at position x in the sequence.
    

    """
    if n == 1 or n == 2:
        return 1
    else:
        return sequence(sequence(n - 1)) + sequence(n - sequence(n - 1))