
    In a hospital's patient monitoring system, develop a function to determine if a specific vital sign reading represents a dominant pattern in a patient's sequential measurements. The function should analyze a sorted array of vital sign readings and a critical threshold value to identify if that value appears in more than half of all measurements taken during the monitoring period. This analysis is crucial for detecting persistent abnormal patterns that may require immediate medical attention.
    

    
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 monitoring system, develop a function to determine if a specific vital sign reading represents a dominant pattern in a patient's sequential measurements. The function should analyze a sorted array of vital sign readings and a critical threshold value to identify if that value appears in more than half of all measurements taken during the monitoring period. This analysis is crucial for detecting persistent abnormal patterns that may require immediate medical attention.
    

    """
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 monitoring system, develop a function to determine if a specific vital sign reading represents a dominant pattern in a patient's sequential measurements. The function should analyze a sorted array of vital sign readings and a critical threshold value to identify if that value appears in more than half of all measurements taken during the monitoring period. This analysis is crucial for detecting persistent abnormal patterns that may require immediate medical attention.
    

    """
    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