Rationalizing the effort of our intensive care staff by predicting patient condition indicators in real time is a challenge because of an impressive number of externally imposed and internally unavoidable restrictions. Patient data privacy requirements, variety of types and lack of standardization within one type of equipment, limited availability of “pure” examples of this or that patient condition patterns – just to name a few complexity factors.
Computational approaches to model…Continue
Added by Sergey Lukyanchikov on December 14, 2020 at 3:00am — No Comments
Author: Sergey Lukyanchikov
Challenges of real-time AI/ML computations
We will start from the examples that we faced as Data Science practice at InterSystems:
Added by Sergey Lukyanchikov on September 20, 2020 at 12:30pm — No Comments
ML Toolkit for InterSystems IRIS, besides Python/R/Julia, allows orchestrating cloud-based advanced analytics services, such as Microsoft Azure Data Factory and Machine Learning:…Continue
Added by Sergey Lukyanchikov on August 18, 2020 at 12:13am — No Comments
Of late, a buzzword in marketing and analytics circles is CDP or Customer Data Platform. Chief Marketing Officers now have this new weapon in their arsenal to serve customers in an even better, faster and more granular manner.
A CDP is a “data unifying software”. Adding it on top of your martech stack helps manage your…
Added by Hemant Warudkar on August 13, 2019 at 2:12am — No Comments
Summary: McKinsey says platform companies will represent 30% of global business revenue by next year (2020). In Part 1 of this article we started to lay out some important lessons learned and examples for you to follow. Here are the rest.
McKinsey says platform companies will represent 30% of global…Continue
Added by William Vorhies on April 15, 2019 at 7:43am — No Comments
Summary: McKinsey says platform companies will represent 30% of global business revenue by next year (2020). Here are some lessons and examples to help mature companies evaluate where they can create AI/ML-enabled platforms to remain competitive. This is a long topic so this will be Part 1 of 2.
Added by William Vorhies on April 8, 2019 at 9:29am — No Comments
Summary: A new business model strategy based around intermediary platforms powered by AI/ML is promising the most direct path to fastest growth, profitability, and competitive success. Adopting this new approach requires a deep change in mindset and is quite different from just adopting AI/ML to optimize your current operations.
Added by William Vorhies on April 1, 2019 at 9:29am — No Comments
Summary: The shortage of data scientists is driving a growing number of developers to fully Automated Predictive Analytic platforms. Some of these offer true One-Click Data-In-Model-Out capability, playing to Citizen Data Scientists with limited or no data science expertise. Who are these players and what does it mean for the profession of data science?
A business intelligence platform is used by healthcare organizations to build helpful healthcare applications that assist them in ensuring the provision of quality healthcare to patients. BI platforms help control healthcare costs and provide several benefits to healthcare organizations such as analysis capability, providing information on delivery, and integration.
Healthcare BI platforms offer a very useful function called financial analytics. The availability of the financial…Continue
Added by Ankit Jain on April 6, 2016 at 10:30am — No Comments
Years ago, when I made a switch from procedural to object oriented programming, concepts such as function overloading fascinated me. The simplicity a single function changing and behaving based on the types of values passed to it spoke volumes to its simplicity and elegance. Being a bit nostalgic I am going to say “those were the good old days!”. Today, the word Analytics is certainly an overloaded term in the data world! It is used to define work done by data scientists to…Continue
Added by Naghman Waheed on November 3, 2015 at 7:42am — No Comments