How should we make decisions in our personal and professional lives? What are winning strategies and what are the unique perspectives flying relatively under the radar?
Maybe what I do for a living is unique--or maybe it isn't. But I will argue, it is certainly dynamic. In the last several weeks I attended the International Conference on Advances in Interdisciplinary Statistics and Combinatorics, National Academy of Medicine Annual Meeting--Cancers: Can We Beat the Odds, Quality Talks, AWS transformation day, and a refresher workshop on R Programming language.
Barry D. Nussbaum, former president of American Statistical Association and Chief Statistician of the Environment Protection Agency presented one of the most relevant and interdisciplinary keynotes--It's Not What We Said, It's Not What They Heard, It's What They Say They heard.
The main objective of the conference is to promote interdisciplinary research involving statistical techniques. These techniques are becoming increasingly important in all fields of scientific discovery.
A unique feature of the proposed conference is that we plan to bring together nationally and internationally recognized researchers from many fields including anthropology, biology, economics, education, environmental science, information systems, insurance, mathematics, medicine, psychology, and public health.--International Conference on Advances in Interdisciplinary Statistics and Combinatorics 2018
A quick review of Simpson's paradox reminds us of the translation of clinical trial data into the real world application of personalized medicine. Barry Nussbaum cautions--we need to be clear communicators of the little arguments in the graphics.
This isn’t your ordinary health care discussion. Quality Talks is a series of stirring, succinct talks by current and emerging health care leaders with ideas about how we can collaboratively improve American health care.
In addition to the dynamic and thought-provoking speakers, the event features interactive dialogue among all attendees about advancing the health care system and improving patient care.--Quality Talks 2018
I absolutely enjoyed Quality Talks. Quick and clean Ted Talk style presentations followed by speaker hubs for face-to-face discussions with presenters. This should be the model of important discussions in healthcare. One of my favorite speakers was Bon Ku, MD. Looking at a system without handwringing or critical review--but looking to innovate and align new edges in healthcare.
Here is a snippet of a talk he gave although not from Quality Talks--you can see how his novel approach to medical education needs to go viral. I am patiently waiting for Continuing Medical Education (CME) to innovate but so far--status quo prevails.
Here is a snippet of a talk he gave although not from Quality Talks--you can see how his novel approach to medical education needs to go viral. I am patiently waiting for Continuing Medical Education (CME) to innovate but so far--status quo prevails.
If you think about big data--think bigger. John Halamka MD is the Chief Information Officer at Beth Israel Deaconess Medical Center. In his Quality Talk, Will Health IT Finally Be Driven by Demand, he shared that he is storing 11 petabytes of data on AWS. To grasp the magnitude, think of a peta-second. We walked back into the room following a conference break. Halamka commented that a peta-second ago, a brontosaurus would have walked the space. Mind-boggling no?
When AWS Transformation Day comes to your town, I suggest you attend if possible. If you succeed in building big data communities for your clients, there is a temptation to blur the edges of your expertise and get lost in the infrastructure. In my own experience I believe you must be fluent in the process but what you might actually need at the table is an experienced data engineer.
The lexicon appears to lump everything into broad categories such as data scientist--but that means nothing. You need someone to develop an architecture to help the process for analyses and processing as well as providing oversight to monitor systems.
The slide below shares the output from text generated machine learning using an image. Absolutely hysterical but also shows the limits of what we can glean from limited data.
The lexicon appears to lump everything into broad categories such as data scientist--but that means nothing. You need someone to develop an architecture to help the process for analyses and processing as well as providing oversight to monitor systems.
The slide below shares the output from text generated machine learning using an image. Absolutely hysterical but also shows the limits of what we can glean from limited data.
I work in a mobile environment because that is where the data lives. I wanted to share a few insights from the last round of travel. I rely on the information when building presentations, projects, or even simply engaging across social media. You need a vast toolbox to curate from the edges. The edges have the best view...
We can either remain with the status quo, distort reality with limited literacy around our data, or pivot toward doing better. Follow along for a series of data workshops to help you begin your journey...
We can either remain with the status quo, distort reality with limited literacy around our data, or pivot toward doing better. Follow along for a series of data workshops to help you begin your journey...