
    In a hospital's patient readmission analysis system, determine if a specific risk score represents the predominant risk level in a sorted sequence of patient readmission assessments. Given a sorted array of standardized risk scores from patient records and a target risk score value, develop a function to verify if this risk score appears in more than half of the total patient cases being analyzed. The risk scores are derived from a combination of medical history and current vital signs, standardized on a numerical scale.
    

    
def binary_search(arr, low, high, x):
    if high >= low:
        mid = (low + high) // 2
        if (mid == 0 or x > arr[mid - 1]) and arr[mid] == x:
            return mid
        elif x > arr[mid]:
            return binary_search(arr, mid + 1, high, x)
        else:
            return binary_search(arr, low, mid - 1, x)
    return -1

def is_majority(arr, n, x):
    """
    In a hospital's patient readmission analysis system, determine if a specific risk score represents the predominant risk level in a sorted sequence of patient readmission assessments. Given a sorted array of standardized risk scores from patient records and a target risk score value, develop a function to verify if this risk score appears in more than half of the total patient cases being analyzed. The risk scores are derived from a combination of medical history and current vital signs, standardized on a numerical scale.
    

    """
def binary_search(arr, low, high, x):
    if high >= low:
        mid = (low + high) // 2
        if (mid == 0 or x > arr[mid - 1]) and arr[mid] == x:
            return mid
        elif x > arr[mid]:
            return binary_search(arr, mid + 1, high, x)
        else:
            return binary_search(arr, low, mid - 1, x)
    return -1

def is_majority(arr, n, x):
    """
    In a hospital's patient readmission analysis system, determine if a specific risk score represents the predominant risk level in a sorted sequence of patient readmission assessments. Given a sorted array of standardized risk scores from patient records and a target risk score value, develop a function to verify if this risk score appears in more than half of the total patient cases being analyzed. The risk scores are derived from a combination of medical history and current vital signs, standardized on a numerical scale.
    

    """
    i = binary_search(arr, 0, n - 1, x)
    if i == -1:
        return False
    if i + n // 2 <= n - 1 and arr[i + n // 2] == x:
        return True
    else:
        return False