Update README.md

README.md

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 ### A 100-patient database that contains in total 100 patients, 372 admissions, and 111,483 lab observations. ###
-### Created by: Uri Kartoun, PhD, Copyright 2014.                                                             ###
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-
-The Problem
-It is difficult and expensive to access Electronic Medical Records (EMRs) due to privacy concerns and technical problems.
-I am a student or a researcher working at a university that does not have yet an access to EMR system and I am interested in evaluating machine learning algorithms.
-Tedious bureaucracy.
-
-I am teaching a computer science course and I wish to let my 150 students to experiment with electronic medical records.
-Not possible due to privacy issues.
-
-I am in a process of founding a company focused on developing a new EMR management platform and I want to demonstrate to a venture capital company and to potential customers the ability of my product to handle big data.
-Current simulated medical databases are limited and are hard to configure.
-
-The Solution
-A database of artificial patients.
-The data is generated according to pre-defined criteria and is not based on any human data.
-
-The database contains the same characteristics that exist in a real medical database such as patients  admission details, demographics, socioeconomic details, labs, medications, etc.
+### Created by: Uri Kartoun, PhD, Copyright 2014 (https://urikartoun.com/).                                               ###
+#############################################################################################################################
 
-The database is customizable. For example, it is possible to generate a population of 100,000 patients of which 60% are male, 40% are African American, 15% are diabetic, specific lab range distributions can be set, etc.
+**The Problem:** It is difficult and expensive to access Electronic Medical Records (EMRs) due to privacy concerns and technical problems. I am a student or a researcher working at a university that does not have yet an access to EMR system and I am interested in evaluating machine learning algorithms. Tedious bureaucracy. I am teaching a computer science course and I wish to let my 150 students to experiment with electronic medical records. Not possible due to privacy issues. I am in a process of founding a company focused on developing a new EMR management platform and I want to demonstrate to a venture capital company and to potential customers the ability of my product to handle big data. Current simulated medical databases are limited and are hard to configure.
 
-The number of records can range from several thousands to millions, depending on the desired configuration.
+**The Solution:** A database of artificial patients. The data is generated according to pre-defined criteria and is not based on any human data. The database contains the same characteristics that exist in a real medical database such as patients  admission details, demographics, socioeconomic details, labs, medications, etc. The database is customizable. For example, it is possible to generate a population of 100,000 patients of which 60% are male, 40% are African American, 15% are diabetic, specific lab range distributions can be set, etc. The number of records can range from several thousands to millions, depending on the desired configuration.