GNS Healthcare Blog

GNS Healthcare Primary Blog

By December 31, 1969

GNS Healthcare Blog

3 Ways Machine Learning is Transforming Drug Development

A recent study revealed that nearly half of all pipeline compounds and close to three quarters of oncology compounds are utilizing biomarker data during the drug development process. The same report indicated that investment in biomarker identification by biopharma has doubled over the past five years and is forecasted to increase over the next half decade. [1] 

Biopharma’s increasing reliance on molecular data (most commonly genomic and proteomic) and the identification of specific biomarkers in the drug development process should not be surprising. Healthcare is transitioning to...

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The Data Analytics Pyramid – Climbing to Optimization & Inference

The availability of data combined with the power of Artificial Intelligence (AI) is causing disruption and raising questions across a number of industries, including healthcare. The electronic medical record has provided digitized health information. Genomic data is now working its way into datasets. There have been impactful innovations in the areas of targeted intervention, drug and device development, software applications, population health approaches, collaboration among healthcare stakeholders and, precision medicine.

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How AI is Replacing Prediction with Discovery Using Data

Hardly a day goes by without someone publishing an article on how artificial intelligence (AI) is revolutionizing the healthcare industry. No doubt AI is impacting multiple areas of the healthcare landscape from biopharma to health systems, to heath plans to patients.

One recent survey reported that 90 percent of pharma companies believe that AI is critical to their success.[1] Another report has 42 percent of healthcare system leaders saying they have or are planning to add AI as a tool for disease management.[2] Some even suggest AI will eventually replace physicians when diagnosing...

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A Powerful Partnership: Artificial Intelligence and Longitudinal Data To Better Understand Multiple Myeloma

More than 30,000 people a year are diagnosed with multiple myeloma in the United States, making it the second most common type of blood cancer. Researchers have yet to find a cure, in part due to the diverse ways the disease manifests itself, but recent advances in cancer research have made it a treatable disease.

The availability of genomic data and power of artificial intelligence is driving more progress in the understanding of multiple myeloma.  Causal machine learning (causal ML) – a powerful form of artificial intelligence – has the ability to reduce the time to study disease and...

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Harnessing New & Traditional Data to Discover Actionable Insights with AI

By Patrick Getzen, Chief Data and Analytics Officer of Blue Cross and Blue Shield of North Carolina

Clashes between the traditional and the novel are as old as time itself. Change is rarely welcomed, so anything new that comes along often faces a rough road to acceptance. However, that is not the case when it comes to the types of data that are now becoming available in the world of healthcare. The merging of new and traditional healthcare data promises to lead to a new era of discovery and offers significant benefits for patients, providers and payers.

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Dr. Stephen Hawking – The History of His Time Was Indeed Too Brief 

 

Is it possible to feel a close, personal connection with someone you’ve never actually met? That was certainly the case for me when it comes to Dr. Stephen Hawking. I was deeply saddened when I heard of his passing this week, not only because the world would no longer benefit from his enormous contributions, but because he inspired me to choose my current career path.

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Population Health to Personalized Medicine: Why Shooting for “Average” Misses the Mark

Current cancer treatments provide benefits to only one out of every four patients. Drugs for Alzheimer’s are ineffective for 70 percent of patients. Medicines for arthritis (50%), diabetes (43%), and asthma (40%) have no benefits for large portions of afflicted individuals. In general, according to a report from the Personalized Medicine Coalition (PMC), many FDA-approved drugs are ineffective on average for nearly half the targeted patient populations.

These sobering statistics are hard to believe in an era of advanced technology, but not so surprising when you get to the core issue....

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3 Ways Causal Machine Learning is Accelerating the Speed of Discovery in Health Care

Imagine if we could approach healthcare with the precision that retailers like Amazon and Netflix use to reach their customers. Imagine if we could grasp the holy grail of precision medicine and harness the ability to match patients with the specific treatment or intervention that is most effective for them as individuals.

How can we scale precision medicine so that every patient is provided with a personally optimized treatment plan? How can we turn data into models of disease progression and drug response, so we can discover novel biomarkers and accelerate drug discovery and development?

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5 Challenges to Applying AI and Machine Learning in Healthcare

While artificial intelligence and machine learning technologies hold plenty of promise in helping to improve patient outcomes and lower costs in health care, making effective use of these technologies requires expertise and experience in handling massive data sets and the tools that extract the right information to answer healthcare’s most difficult questions.

Julie Slezak, EVP of Clinical Analytics at GNS, highlights the key stumbling blocks she sees most often and how to overcome them. Following are five key challenges. Consider this a giant heads-up to anyone employing artificial...

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Why Causal Learning is a Superpower for Healthcare

Most people have never heard of causal learning, but the concept is an important one for the future of healthcare because it holds the key to understanding and fighting disease and improving outcomes. However, to understand how and why causality is so important in the fight for better healthcare, we have to first understand machine learning.

You may be familiar with the term “artificial intelligence”, which is a broader umbrella term that machine learning falls within. An article in Xconomy published earlier this year goes into detail on artificial intelligence (AI) and starts by talking...

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