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Readme.md file changes #7

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27 changes: 13 additions & 14 deletions README.md
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Expand Up @@ -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.

Expand Down Expand Up @@ -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">