
    In a hospital's patient readmission risk assessment system, develop an algorithm that analyzes a patient's historical hospital visits to calculate their readmission risk score. Given the total number of previous hospital visits (n), the system needs to evaluate visits in decreasing intervals, starting from the most recent visit and stepping back by intervals of 2, until no more historical data remains relevant. The risk score is computed as the sum of weighted factors (n - 2*i) where i starts at 0 and increases until reaching n/2, with more recent visits carrying higher weight in the calculation. This weighted sum helps identify patterns in hospital readmissions, particularly focusing on the frequency and recency of visits, to determine the likelihood of future readmissions.
    

    
def sum_series(n):
    """
    In a hospital's patient readmission risk assessment system, develop an algorithm that analyzes a patient's historical hospital visits to calculate their readmission risk score. Given the total number of previous hospital visits (n), the system needs to evaluate visits in decreasing intervals, starting from the most recent visit and stepping back by intervals of 2, until no more historical data remains relevant. The risk score is computed as the sum of weighted factors (n - 2*i) where i starts at 0 and increases until reaching n/2, with more recent visits carrying higher weight in the calculation. This weighted sum helps identify patterns in hospital readmissions, particularly focusing on the frequency and recency of visits, to determine the likelihood of future readmissions.
    

    """
def sum_series(n):
    """
    In a hospital's patient readmission risk assessment system, develop an algorithm that analyzes a patient's historical hospital visits to calculate their readmission risk score. Given the total number of previous hospital visits (n), the system needs to evaluate visits in decreasing intervals, starting from the most recent visit and stepping back by intervals of 2, until no more historical data remains relevant. The risk score is computed as the sum of weighted factors (n - 2*i) where i starts at 0 and increases until reaching n/2, with more recent visits carrying higher weight in the calculation. This weighted sum helps identify patterns in hospital readmissions, particularly focusing on the frequency and recency of visits, to determine the likelihood of future readmissions.
    

    """
    if n < 1:
        return 0
    else:
        return n + sum_series(n - 2)