As I read this person's quote at the start of the article, my thought was that the only thing lacking to achieve success was modesty:
“We’re pursuing problems that are computationally and intellectually exciting, and where there is the potential to change how doctors treat patients in two or three years,” Mr. Hammerbacher said.
The line shows up in a Steve Lohr New York Times story about Mt. Sinai hospital where:
[T]he goal is to transform medicine into an information science, where data and computing are marshaled to deliver breakthroughs in the treatment of cancer, Alzheimer’s, diabetes and other chronic diseases. Mount Sinai is only one of several major medical schools turning to data science as a big part of the future of medicine and health care. They are reaching out to people like Mr. Hammerbacher, whose career arc traces the evolution of data science as it has spread across the economy.
The impetus comes from other fields:
Chronic diseases, Dr. Schadt explained, are not caused by single genes, but are “complex networked disorders” involving genetics, but also patient characteristics such as weight, age, gender, vital signs, tobacco use, toxic exposure and exercise routines — all of which can be captured as data and modeled.
Don't get me wrong. I love that they are trying. But, please let's be realistic about both the development of the science and the speed with which diffusion of new diagnostic and therapeutic regimes infuse the health care system.
As I came to the end of the article, I found myself hoping that there might be a touch of that modesty after all:
“We’re pursuing problems that are computationally and intellectually exciting, and where there is the potential to change how doctors treat patients in two or three years,” Mr. Hammerbacher said.
The line shows up in a Steve Lohr New York Times story about Mt. Sinai hospital where:
[T]he goal is to transform medicine into an information science, where data and computing are marshaled to deliver breakthroughs in the treatment of cancer, Alzheimer’s, diabetes and other chronic diseases. Mount Sinai is only one of several major medical schools turning to data science as a big part of the future of medicine and health care. They are reaching out to people like Mr. Hammerbacher, whose career arc traces the evolution of data science as it has spread across the economy.
The impetus comes from other fields:
Chronic diseases, Dr. Schadt explained, are not caused by single genes, but are “complex networked disorders” involving genetics, but also patient characteristics such as weight, age, gender, vital signs, tobacco use, toxic exposure and exercise routines — all of which can be captured as data and modeled.
“We are trying to move medicine in the direction of climatology and physics; disciplines that are far more advanced and mature quantitatively,” he said.
Oh, climatology, where models remain in formative stages after years of research. Or, physics, where the hoped-for general laws that describe the universe or quanta or both are in constant flux.
Don't get me wrong. I love that they are trying. But, please let's be realistic about both the development of the science and the speed with which diffusion of new diagnostic and therapeutic regimes infuse the health care system.
As I came to the end of the article, I found myself hoping that there might be a touch of that modesty after all:
[Mr. Hammerbacher] is optimistic about his initiative’s prospects, but has come to appreciate that the mysteries of the human body may be more resistant to math than finance or social networks are. Today he speaks less about quants taking over than about their lending a hand. “We’re not the most important people,” he said, “but we can help.”