What precisely is huge data? A report delivered to the U.S. Congress in August 2012 defines huge knowledge as “large volumes of high speed, complex, and variable knowledge that need advanced techniques and technologies to alter the capture, storage, distribution, management and analysis of the information” [6]. huge knowledge encompasses such characteristics as selection, speed and, with respect specifically to care, truthfulness [20, 21, 22, 23]. Existing analytical techniques are often applied to the large quantity of existing (but presently unanalyzed) patient- related health and medical knowledge to achieve a deeper understanding of outcomes, that then are often applied at the purpose of care. Ideally, individual and population knowledge would inform every medical man and her patient throughout the decision-making method and facilitate verify the foremost applicable treatment possibility for that specific patient. Advantages to care By digitizing, combining and effectively exploitation huge knowledge, care organizations starting from single-physician offices and multi-provider teams to massive hospital networks and responsible care organizations stand to appreciate important advantages [2]. Potential advantages embody detection diseases at earlier stages once they are often treated additional simply and effectively; managing specific individual and population health and detection health care fraud additional quickly and with efficiency. varied queries are often addressed with huge knowledge analytics. sure developments or outcomes could also be expected and/or calculable supported large amounts of historical knowledge, like length of keep (LOS); patients WHO can opt for elective surgery; patients WHO probably won\'t like surgery; complications; patients in danger for medical complications; patients in danger for infection, MRSA, C. difficile, or alternative hospital-acquired illness; illness/disease progression; patients in danger for advancement in illness states; causative factors of illness/disease progression; and attainable co-morbid conditions (EMC Consulting). McKinsey estimates that huge knowledge analytics will alter over $300 billion in savings annually in U.S. healthcare, 2 thirds of that through reductions of roughly 8 May 1945 in national care expenditures. Clinical operations and R & D square measure 2 of the biggest areas for potential savings with $165 billion and $108 billion in waste severally [24]. McKinsey believes huge knowledge may facilitate scale back waste and unskillfulness within the following 3 areas: Clinical operations: Comparative effectiveness analysis to work out additional clinically relevant and cost-efficient ways that to diagnose and treat patients. BOARD_SIZE = eight def under_attack(col, queens): # (col, queens) what\'s their meaning? What do i would like to jot down it this field? left = right = mountain pass for r, c in reversed(queens): # What will reversed means that during this loop? For what re.

1. What precisely is huge data? A report delivered to the U.S. Congress in August 2012 defines
huge knowledge as “large volumes of high speed, complex, and variable knowledge that need
advanced techniques and technologies to alter the capture, storage, distribution, management and
analysis of the information” [6]. huge knowledge encompasses such characteristics as selection,
speed and, with respect specifically to care, truthfulness [20, 21, 22, 23]. Existing analytical
techniques are often applied to the large quantity of existing (but presently unanalyzed) patient-
related health and medical knowledge to achieve a deeper understanding of outcomes, that then
are often applied at the purpose of care. Ideally, individual and population knowledge would
inform every medical man and her patient throughout the decision-making method and facilitate
verify the foremost applicable treatment possibility for that specific patient.
Advantages to care
By digitizing, combining and effectively exploitation huge knowledge, care organizations
starting from single-physician offices and multi-provider teams to massive hospital networks and
responsible care organizations stand to appreciate important advantages [2]. Potential advantages
embody detection diseases at earlier stages once they are often treated additional simply and
effectively; managing specific individual and population health and detection health care fraud
additional quickly and with efficiency. varied queries are often addressed with huge knowledge
analytics. sure developments or outcomes could also be expected and/or calculable supported
large amounts of historical knowledge, like length of keep (LOS); patients WHO can opt for
elective surgery; patients WHO probably won't like surgery; complications; patients in danger
for medical complications; patients in danger for infection, MRSA, C. difficile, or alternative
hospital-acquired illness; illness/disease progression; patients in danger for advancement in
illness states; causative factors of illness/disease progression; and attainable co-morbid
conditions (EMC Consulting). McKinsey estimates that huge knowledge analytics will alter over
$300 billion in savings annually in U.S. healthcare, 2 thirds of that through reductions of roughly
8 May 1945 in national care expenditures. Clinical operations and R & D square measure 2 of
the biggest areas for potential savings with $165 billion and $108 billion in waste severally [24].
McKinsey believes huge knowledge may facilitate scale back waste and unskillfulness within the
following 3 areas:
Clinical operations: Comparative effectiveness analysis to work out additional clinically relevant
and cost-efficient ways that to diagnose and treat patients.
BOARD_SIZE = eight
def under_attack(col, queens): # (col, queens) what's their meaning? What do i would like to jot
down it this field?
left = right = mountain pass

2. for r, c in reversed(queens): # What will reversed means that during this loop? For what reson
will we want r and c (their that means is zero by default?)?
left, right = left-1, right+1
if c in (left, col, right):
come True
come False
def solve(n):
if n == 0: come [[]]
smaller_solutions = solve(n-1) # For what reasons will we ought to write smaller_solutions?
come [solution+[(n,i+1)] # what's answer (is it a operate or what?)? what's worth of i?
for i in range(BOARD_SIZE)
for answer in smaller_solutions
if not under_attack(i+1, solution)]
for answer in solve(BOARD_SIZE): print answer
Solution
What precisely is huge data? A report delivered to the U.S. Congress in August 2012 defines
huge knowledge as “large volumes of high speed, complex, and variable knowledge that need
advanced techniques and technologies to alter the capture, storage, distribution, management and
analysis of the information” [6]. huge knowledge encompasses such characteristics as selection,
speed and, with respect specifically to care, truthfulness [20, 21, 22, 23]. Existing analytical
techniques are often applied to the large quantity of existing (but presently unanalyzed) patient-
related health and medical knowledge to achieve a deeper understanding of outcomes, that then
are often applied at the purpose of care. Ideally, individual and population knowledge would
inform every medical man and her patient throughout the decision-making method and facilitate
verify the foremost applicable treatment possibility for that specific patient.
Advantages to care
By digitizing, combining and effectively exploitation huge knowledge, care organizations
starting from single-physician offices and multi-provider teams to massive hospital networks and
responsible care organizations stand to appreciate important advantages [2]. Potential advantages
embody detection diseases at earlier stages once they are often treated additional simply and
effectively; managing specific individual and population health and detection health care fraud
additional quickly and with efficiency. varied queries are often addressed with huge knowledge
analytics. sure developments or outcomes could also be expected and/or calculable supported
large amounts of historical knowledge, like length of keep (LOS); patients WHO can opt for

3. elective surgery; patients WHO probably won't like surgery; complications; patients in danger
for medical complications; patients in danger for infection, MRSA, C. difficile, or alternative
hospital-acquired illness; illness/disease progression; patients in danger for advancement in
illness states; causative factors of illness/disease progression; and attainable co-morbid
conditions (EMC Consulting). McKinsey estimates that huge knowledge analytics will alter over
$300 billion in savings annually in U.S. healthcare, 2 thirds of that through reductions of roughly
8 May 1945 in national care expenditures. Clinical operations and R & D square measure 2 of
the biggest areas for potential savings with $165 billion and $108 billion in waste severally [24].
McKinsey believes huge knowledge may facilitate scale back waste and unskillfulness within the
following 3 areas:
Clinical operations: Comparative effectiveness analysis to work out additional clinically relevant
and cost-efficient ways that to diagnose and treat patients.
BOARD_SIZE = eight
def under_attack(col, queens): # (col, queens) what's their meaning? What do i would like to jot
down it this field?
left = right = mountain pass
for r, c in reversed(queens): # What will reversed means that during this loop? For what reson
will we want r and c (their that means is zero by default?)?
left, right = left-1, right+1
if c in (left, col, right):
come True
come False
def solve(n):
if n == 0: come [[]]
smaller_solutions = solve(n-1) # For what reasons will we ought to write smaller_solutions?
come [solution+[(n,i+1)] # what's answer (is it a operate or what?)? what's worth of i?
for i in range(BOARD_SIZE)
for answer in smaller_solutions
if not under_attack(i+1, solution)]
for answer in solve(BOARD_SIZE): print answer