Kaggle is a website to host coding competitions related to machine learning, big data, or otherwise all things data science.
Newly launched on Kaggle is a healthcare-related competition! A group of health institutions provided a large data set consisting of three patients’ interictal and preictal (up to 1 hour before) EEG tracings in raw data. The goal? Predict which “unknown” EEGs are preictal so healthcare providers can intervene.
Also, with the timely arrival of Internet of Things (IoT), wearable, and big data, can you imagine the impact of giving patients an accurate 5-minute warning every time a seizure is about to start? Continue reading
If you have taken overnight call, you quickly develop a sense for the emergency department and the inpatient floors. In my institution, radiologists develop hypotheses on how inpatient orders are placed.
For instance, sometimes it might seem as if inpatient radiology exams follow some sort of circadian rhythm. The data look to confirm it: we see the infamous “x-ray bump” in the early morning, with the increase in CT start more gradually but last later into the day.
Also, are weekdays and weekends any different? If so, how?
Going on a Quest
With a little coding in Python or R, one can gain a lot of insight into how our referring providers’ lives intertwine with our own. Read the full story in my new post on Radiology Data Quest.
From the Open Data Network I stumbled upon the CMS outpatient imaging data organized by state and decided to peek into the dataset and stick the data onto a US map for fun. Geek out with Joe and me in this new blog Radiology Data Quest.
They are taking medical data science rather seriously. The folks at Stanford Medicine are onto something.
Source: Biomedical Data Science Initiative @ Stanford Medicine
Don’t Start with the Data
Do Start with a Good Question
Don’t think one person can do it all
Do build a well-rounded team
Don’t only use one tool
Do use the best tool for the job
Don’t brag about the size of your data
Do collect relevant data
Dr. Keith Dreyer opens with a keynote during the Intersociety Summer Conference (ISC) with description of data science and overview of how machine learning have evolved over time.
He describes that machines and humans inherently see things differently. Humans are excellent at object classification, recognition of faces, understanding language, driving, and imaging diagnostics. Continue reading