From 1e8a32dad203129f3534a022648ae811f87c6508 Mon Sep 17 00:00:00 2001
From: Serim Hande Tarcan <46164107+HandeTarcan@users.noreply.github.com>
Date: Fri, 22 Nov 2019 20:21:50 +0300
Subject: [PATCH] Update README.md

I'm a doctor and I had trouble understanding the goal of the project. Therefore, I made some changes to increase the readability, make the file more understandable, and strengthen the idea behind the project. I also should add that I would definitely want to talk about and work on the project, if possible, since it is one of the most creative ML projects in medicine I have seen so far.
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 README.md | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

diff --git a/README.md b/README.md
index f86fa1e..a8fb924 100644
--- a/README.md
+++ b/README.md
@@ -1,5 +1,5 @@
 # pySickleCell
 Python-based standalone application for sickle cell disease prediction
 
-Description: A prevalent genetic disorder Sickle cell disease (SCD) has been affecting people thus resulting in multiple acute and chronic complications including pain crises, stroke, and kidney disease. It has been seen that the patients who suffer with SCD tend to lead to organ failure among other chronic organ dysfunctioning. Although it is not feasible and possible to detect cute physiological deterioration which lead to organ failure.
-A solution to earlier identification of this which could potentially cut down the mortality is usage of machine learning techniques through which the failure of organs occurring from physio markers are recognised and with the project’s further extension, forewarning of the order in which organ failure could occur over a span of time could be signaled. 
+Description: A prevalent genetic disorder sickle cell disease (SCD), which is the most common inherited blood disorder in the United States, has been affecting millions of people worldwide, resulting in multiple acute and chronic complications including pain crises, stroke, and kidney disease. It has been seen that SCD tends to lead to organ failure more compared to other chronic organ dysfunctionings. It is not feasible and possible to detect acute physiological deterioration which leads to organ failure, though.
+A solution to earlier identification of this problem, which could potentially cut down the mortality rate, is the usage of the machine learning techniques that are recognizing, with the help of physiological markers, which organs are failing and forewarning of the order in which organ failure could occur over a span of time at the further extension of the project.