Update README.md

README.md

@@ -10,28 +10,27 @@ What is Survival Analysis?
 ------------------------
 
 **Survival Analysis** involves estimating when an event of interest, \( T \)
-would take places given some features or covariates \( X \). In statistics
-and ML these scenarious are modelled as regression to estimate the conditional
-survival distribution, \( \mathbb{P}(T>t|X) \). As compared to typical
-regression problems, Survival Analysis differs in two major ways:
-
-* The Event distribution, \( T \) has positive support ie.
-  \( T \in [0, \infty) \).
-* There is presence of censoring ie. a large number of instances of data are
+would take place given some features or covariates \( X \). In statistics
+and ML, these scenarios are modelled as regression to estimate the conditional
+survival distribution, ℙ (T > t | X).   
+As compared to typical regression problems, Survival Analysis differs in two major ways:
+
+* The Event distribution, \( T \) has positive support i.e. T ∈ [0, ∞).
+* There is presence of censoring i.e. a large number of instances of data are
   lost to follow up.
 
 Deep Survival Machines
 ----------------------
 
-<img width=50% src=https://ndownloader.figshare.com/files/25259852>
+<img width=80% src=https://ndownloader.figshare.com/files/25259852>
 
 
-**Deep Survival Machines (DSM)** is a fully parametric approach to model
-Time-to-Event outcomes in the presence of Censoring first introduced in
+**Deep Survival Machines (DSM)** is a **fully parametric** approach to model
+Time-to-Event outcomes in the presence of Censoring, first introduced in
 [\[1\]](https://arxiv.org/abs/2003.01176).
 In the context of Healthcare ML and Biostatistics, this is known as 'Survival
 Analysis'. The key idea behind Deep Survival Machines is to model the
-underlying event outcome distribution as a mixure of some fixed \( k \)
+underlying event outcome distribution as a mixure of some fixed \( K \)
 parametric distributions. The parameters of these mixture distributions as
 well as the mixing weights are modelled using Neural Networks.
 
@@ -115,5 +114,5 @@ GNU General Public License for more details.
 You should have received a copy of the GNU General Public License
 along with Deep Survival Machines.  If not, see <https://www.gnu.org/licenses/>.
 
-<img style="float: right;" width ="200px" src="https://www.cmu.edu/brand/downloads/assets/images/wordmarks-600x600-min.jpg">
-<img style="float: right;padding-top:50px" src="https://www.autonlab.org/user/themes/auton/images/AutonLogo.png"> 
+<img style="float: left; padding-top:25px" width ="150px" src="https://www.cmu.edu/brand/downloads/assets/images/wordmarks-600x600-min.jpg">
+<img style="float: right;padding-top:25px" width = "150px" src="https://www.autonlab.org/user/themes/auton/images/AutonLogo.png">