
    In a medical imaging system that processes binary feature maps of potential disease indicators, develop a function that identifies and activates the leftmost undetected feature position (represented by 0) in the diagnostic data. The function should take a binary number representing the current feature detection status and return a new value with the leftmost undetected feature now marked as detected (changed from 0 to 1), enabling progressive refinement of disease marker identification in automated image analysis.
    

    
def set_left_most_unset_bit(n):
    """
    In a medical imaging system that processes binary feature maps of potential disease indicators, develop a function that identifies and activates the leftmost undetected feature position (represented by 0) in the diagnostic data. The function should take a binary number representing the current feature detection status and return a new value with the leftmost undetected feature now marked as detected (changed from 0 to 1), enabling progressive refinement of disease marker identification in automated image analysis.
    

    """
def set_left_most_unset_bit(n):
    """
    In a medical imaging system that processes binary feature maps of potential disease indicators, develop a function that identifies and activates the leftmost undetected feature position (represented by 0) in the diagnostic data. The function should take a binary number representing the current feature detection status and return a new value with the leftmost undetected feature now marked as detected (changed from 0 to 1), enabling progressive refinement of disease marker identification in automated image analysis.
    

    """
    if not n & n + 1:
        return n
    (pos, temp, count) = (0, n, 0)
    while temp:
        if not temp & 1:
            pos = count
        count += 1
        temp >>= 1
    return n | 1 << pos