In the previous blog we discussed the fundamental concept of what Machine Learning is and how it can be applied in the modern world of Pharmaceuticals and Healthcare, further to this we explored CMS Open Payments, the federal program that collects information about the payments drug and device companies make to their potential clients.
(more…)
From the outset, the term “Machine Learning” can seem very daunting to those unfamiliar with the technicalities of what this actually means, or so it seemed to me when I was initially assigned to develop a use case for one of these algorithms during my time here at RxDataScience. From a quick study into the topic, Machine Learning (ML), put simply, is a branch of Artificial Intelligence (AI) that allows a system to automatically learn and improve itself without being explicitly instructed to, by using past and present data to predict certain outcomes [1]. The following video provides a gentle introduction into what ML is all about:
(more…)
Two gone, two battling a lifelong battle, like many Americans. With the stigma and bias surrounding the topic, the mental health community struggles to move forward. The research and treatment is at least a decade behind common chronic conditions, mainly because no one wants to talk about mental health due to the complexity and lack of understanding.
(more…)
As mentioned in my previous exert, I will be delving further into the complexity of the algorithm I used in my study. Following some research into decision trees and the impact they have had on healthcare and pharma I found that their presence has been assisting across the field since the early 90’s in the form of Evidence Based Medicine (EBM). The stages detailed in this process where summarised to:
(more…)
Coming from a background in computer science, I was familiar with Machine Learning and its capabilities although admittedly I had never considered the impact it could have on the world of healthcare. Subsequent to joining the team here at RxDataScience, I was tasked with implementing a decision tree, in order to detect what activity a person, in a room was undertaking using data collected via a radio frequency identification tag and sensors mounted in corners of the room.
(more…)
The ETL (extract, transform and load) process by which organizations prepare data for storage is an essential part of modern database systems, particularly used for business intelligence applications. The problem is that it can be inefficient and slow — too slow for companies to do real-time and streaming analytics.
(more…)
IMS Health’s Longitudinal Access and Adjudication Data (LAAD) has revolutionized how companies view data, and structures the information in an easier way for all parties involved. In short, “LAAD is an anonymized patient sample dataset that captures longitudinal pharmacy (both retail and specialty) and medical claims. It was used to quantify payer channel distribution, co-pay card penetration, and low-income subsidy prevalence for these products.”
(more…)
Introduction to Machine Learning with Random Forest (Pharma/Genetics)
To pick up where we left off last blog post, we discussed the potential of predictive analytics in the genetics of cancer. I aim to achieve this by using the aforementioned Random Forest classification algorithm.
(more…)
Within the first decade of the 21st century, the use of big data became very popular in many big industries. The methods for capturing big data have since evolved from traditional data lake systems to more integrated technologies that combine big data with all other systems within a company.1
(more…)
Our last blog post explored the implications of a recent study on artificial intelligence (AI) and machine learning business application. While the healthcare industry can expect incredible benefits from the adoption of AI technology, it remains under-adopted and receives below-average attention when compared to other industries.
This post aims to highlight the areas within healthcare where AI has potential. This technology can improve operations, patient experiences, medical procedures, and solve regulatory challenges.
(more…)
