EFFICIENT AND ACCURATE ABNORMALITY MINING FROM RADIOLOGY REPORTS WITH CUSTOMIZED FALSE POSITIVE REDUCTION

ABSTRACT
Obtaining datasets labeled to facilitate model development is a challenge for most machine learning tasks. The difficulty is heightened for medical imaging, where data itself is limited in accessibility and labeling requires costly time and effort by trained medical specialists. Medical imaging studies, however, are often accompanied by a medical report produced by a radiologist, identifying important features on the corresponding scan for other physicians not specifically trained in radiology. We propose a methodology for approximating..

 

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Roam @ AIDS2018: Machine Learning to Predict HIV Outcomes

TL;DR Roam recently collaborated with ViiV Healthcare to explore models predicting HIV health outcomes, and presented the project’s core methods and results at the AIDS2018 conference.

Supervised machine learning to predict HIV outcomes using electronic health record and insurance claims data

As the lead of the Clinical Data Science team at Roam Analytics, I have the privilege of

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Advantages of Individual Predictions

Plans in healthcare have historically been priced in bulk, which is done to alleviate risk to individuals by putting money into pools. When predicting for this cost, it is typical to use aggregated features such as historical account cost and account demographics.

Growing capabilities to handle big and unstructured data as well as advances in modeling make individual-level predictions increasingly feasible and an attractive alternative to modeling at the aggregate level. Individual-level models can utilize medical data including

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Five Ways You’re Already Using Machine Learning: A Day with AI

Machine learning can seem like a scary term, bringing to mind images of the techno-dystopias portrayed in The MatrixTerminator, and Black Mirror. However, far from these dark narratives, machine learning has been reaching ordinary people for a long time in simple, common, and helpful ways. Here are five such ways you’re (probably) already using

 

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Leveraging Technology in Data Acquisition to Transform the ROI on Risk Adjustment

Chart retrieval is one of the major pain points cited by risk-bearing organizations as an impediment to risk adjustment, HEDIS/quality, and other key initiatives. This time consuming and expensive process is typically done manually via fax, mail, or by sending chart abstractors in person to provider offices. Many organizations use chart retrieval vendors, but

 

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HCA Meets “Quadruple Aim” With AI-powered Cancer App

Artificial intelligence is helping healthcare organization to lighten the administrative burden on frontline staff, reports Diagnostics World, a publication of the Cambridge Healthtech Institute.

If platforms built on artificial intelligence (AI) are to be useful and scalable for healthcare settings that are typically chaotic and strapped for IT talent, there are a few prerequisites. Solve a problem. Be easy to implement and minimally disruptive. And offer a tangible return on investment—ideally, help organizations meet their “quadruple aim” of

 

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Tools for Reproducible Real-World Data Analysis

The oncologist struggled to find the right words. The scientific publication upon which she based her most recent treatment recommendation for the patient sitting in front of her had just been retracted from a prestigious journal. She reflected on a lengthy discussion with this patient six months prior considering the trade-offs between treatment options. Balancing the evidence of efficacy, value of hope, and

 

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