GNS Healthcare Blog

GNS Healthcare Primary Blog

By December 31, 1969

GNS Healthcare Blog

Location, Location, Location: AI Identifies Tumor Sidedness as Key Indicator of Progression in Metastatic Colorectal Cancer

Location matters, especially when it comes to tumors in colon cancer. The issue of “sidedness” – whether tumors are located on the right or left side of the intestine – and what impact that has on the progression of metastatic colorectal cancer (CRC) has been a topic of discussion in the clinical community for several years. A complete understanding of sidedness has not been well understood by researchers and clinicians. Is sidedness an independent driver, confounded by other factors, or a simply a surrogate for other determinants?  By leveraging artificial intelligence (AI) and causal...

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How AI and Precision Medicine are Converging to Create the Perfect Storm for Change

Four out of ten people with asthma don’t respond to their prescribed medicine. The same is true for half of arthritis sufferers. For cancer patients, the number is worse, with nearly eight out of ten patients failing to benefit from an FDA approved drug1.

What does this mean for healthcare? It means on average, half the treatments launched and prescribed in our three trillion dollar a year healthcare system are not effective for those they are intended to help. While these drugs have been rigorously developed, the fact is they simply don’t work for everybody.

And drugs are not the only...

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Now that we have data, how do we leverage it to deliver precision medicine?

 

The efforts to generate and gather healthcare data have paid off. Approximately 61% of Americans are using wearable devices to track their health1, nearly 87% of doctors use electronic health record (EHR) systems in their offices2, and as of May 2018, there are more than 96 thousand clinical trial sites in the US generating clinical data3. These millions of data points mean that as much as 30% of the entire world’s stored data is generated in the healthcare industry4. Due to this abundance, we are on the precipice of making precision medicine a reality by better understanding disease and...

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How the next generation of data is moving the needle to make precision medicine a reality

The growth of “big data” has revealed one undeniable truth: the more data available, the better the insights and the more that you can learn.  That is certainly the case in the healthcare industry where biopharma, health plans and providers are generating, consuming and collecting more data than ever before.

Traditional data sources like electronic health system records (EHR), claims, and labs spurred a wave of population health efforts in the early 2000's. These programs promised to reduce costs and improve outcomes for patients, but were based on models of care for a hypothetical average...

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How Precision Medicine Is Driving the Conversation Across the Healthcare Ecosystem

Not so long ago key stakeholders in the healthcare industry tended to operate in their own separate worlds. Biopharma companies, health plans, providers and healthcare consumers certainly interacted, but in most cases they each focused on dealing with their own specific challenges.

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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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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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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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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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