Category Archives: Data Science

Chronic Illness Landscape

With all the money spent (about 7 trillion USD) on healthcare worldwide, the premature death share due to chronic illness out of total deaths has increased from 50% to 60% and is projected to become 70% by year 2020.

While developed world is spending 80% of their healthcare budget of 5 trillion dollars on 65 years plus aged population trying to deal with chronic illness, developing countries have 80% of the worlds’ chronic illness patients with not even 10% of global healthcare funds.

Type of chronic illness and the reason for chronic illness is different for the developed and developing world. Developed world has much lower premature death rate (0.3%) and most of the chronic illness are due to sedentary life style and processed food. Developing world is suffering due to poor living / working conditions, low nutrient diet and changing life style leading to very high premature death rate (0.5%).

It is clear that developed world has almost half of premature death rate as compared to developing countries despite much higher ageing population, sedentary life and high intake of processed food. Most of it was made possible with help of better medications to keep cholesterol, sugar and blood pressure levels in control.

While medicines are available in developed world at affordable prices now but patients are not getting cured as they are not able to identify the disease onset and also complete the prescriptions as advised by the doctors. Prescription adherence can help patients to get cured much faster at lower cost with minimal side effects.

Impact of prescription non adherence is most visible in Tuberculosis patients. 50% of TB patients become drug resistant due to prescription non adherence and 25% of them die as they are not able to complete the 2nd line of treatment due to severe side effects.

While medicines help to get the vitals in control, permanent cure for chronic illness lies in addressing the Root causes of chronic illness:

  • Poor diet (high sodium, sugar and fat, low micro nutrients)
  • Low physical activity
  • Poor living & working conditions (high pollution, high stress, low socialisation, lack of sleep)
  • High alcohol consumption and smoking

It is possible to stay healthy at all times by following correct food, sleep and exercise pattern but, in the event of any chronic illness it is good to complete recommended prescription immediately to get cured fast.

With delayed or wrong treatment, getting cured will take much longer, cost many times, lead to much more pain and eventually premature death.

Our IoT and AI driven health monitoring system helps to detect disease onset at early stage and prescription compliance solutions help patients get cured with first line medications much faster at lower cost with minimal side effects.

Predivtive Analytics

IOT Data Analytics & Insight

Customer Churn - Decision TreeIOT Data Analytics & Insight

Statistical Concepts

•  Descriptive and Inferential Statistics

•  Basic Statistics – Mean, Mode, Median, Standard Deviation

•  Classification, Rules of Association, Regression Analysis, Cluster Analysis

•  Algorithms – K-means, TwoStep, Kohonen Net, Apriori and GRI

•  Probability Theory

 

 R Programming

•  Introduction to R Programming – R Studio, Shiny

•  IOT Data Analytics & Insight

•  Project work:

o  Vehicle Analysis – IOT Sensors

o  American Football Analysis

o  Stock Market Analysis

 

Predictive Analytics using Data Mining Tool Rapid Miner

•  Operationalize Predictive Decisions

•  Advanced Analytics – Machine Learning, IOT

•  Project work:

o  Marketing Analytics to predict highest conversions

o  Customer Churn Prediction to design Retention

o  Predictive Maintenance for high uptime using IOT

 

IOT, Big Data Analytics and Insights

•  Real-time Big Data Analytics – Kafka, Spark, Hadoop

  • Smart Transportation – IOT, Beacon & Bluetooth Low Energy Mobile App

•  Manufacturing & Supply Chain Optimization

•  Root Cause Analysis

•  Key Analytics by major Verticals

Analytics & Insight through R Programming and Rapid Miner – One Day hands on Program with Project work

http://learn.profileq.net/

One Day Data Analytics Program to get you started on your data science career with focus on R Programming, Rapid Miner to do Root Cause and Predictive Analytics

Faculty              : Arun Thakur, SVP & Head Big Data Analytics   http://in.linkedin.com/in/thakurarun

Venue               : CH7 Natasha Golf View, Inner Ring Road, Domlur, Bangalore 560071

Program Dates: Saturdays during Nov & Dec 2015 from 10am to 6pm.

Register            : http://goo.gl/forms/QCOFNSD6hw , INR 4,000 per participant (includes lunch, tea)

 

Program Content

 

Statistical Concepts

•             Descriptive and Inferential Statistics

•             Basic Statistics – Mean, Mode, Median, Standard Deviation

•             Classification, Rules of Association, Regression Analysis, Cluster Analysis

•             Algorithms – K-means, TwoStep, Kohonen Net, Apriori and GRI

•             Probability Theory

 

 

R Programming

•             Introduction to R Programming – R Studio, Shiny

•             Data Analytics & Visualization

•             Project work:

o             Vehicle Analysis

o             American Football Analysis

o             Stock Market Analysis

 

Predictive Analytics using Data Mining Tool Rapid Miner

•             Operationalize Predictive Decisions

•             Advanced Analytics – Machine Learning

•             Project work:

o             Marketing Analytics to predict highest conversions

o             Customer Churn Prediction to design Retention

o             Predictive Maintenance for high uptime

 

Big Data, Analytics and Insights

•             Real-time Big Data Analytics – Kafka, Spark, Hadoop

•             Manufacturing & Supply Chain Optimization

•             Root Cause Analysis

•             Key Analytics by major Verticals