Hey everyone, this is kinda OT, but it’s such an incredible story and something I’m very proud of. Slalom, and specifically the Atlanta office where I work was the consulting firm featured here that partnered with the American Cancer Society and Google Cloud Platform for this project.
It does prove something about the companies and technologies we are investing in on this board. Some of them are literally changing the world and saving lives. That is a very real impact and very, very different than almost all of the super-hyped 99-2000 .coms
The best thing you can do is take 5-10 minutes and read these articles. But I’ll also provide some quotes below.
https://www.slalom.com/case-studies/american-cancer-society-…
https://cloud.google.com/customers/american-cancer-society/
Here’s how/why the project got started…
" Last year, one of Slalom’s consultants—someone who was passionate about technology and helping others—passed away from cancer. To honor him, Slalom reached out to the American Cancer Society (ACS) to see if, and how, a team of Slalom consultants could help further ACS’s mission of freeing the world from cancer."
The ACS process for cancer research…
"Every two years, ACS sent participants a follow-up questionnaire, and if someone reported that they had breast cancer, their hospital would send tumor samples to ACS. The samples were made by soaking the removed tumor in a solution that stops cellular activity, putting it in a block of wax, taking a very thin slice out of the block, staining the slice to show the different parts of the cells, and then putting the slice in a glass slide.
Since the study began, ACS has collected over 1,700 slides from women diagnosed with breast cancer. These slides can provide critical clues to help prevent and treat breast cancer—but identifying those clues was a challenge."
So…1,700 slides to review
"Most pathologists—doctors who specialize in identifying abnormalities in tissues—work in clinical care, so they’re in high demand in the research world. At ACS, there’s only one pathologist on the breast cancer research team, part-time. He spends the rest of his time with other duties at ACS.
“Imagine how long it takes someone to look at those 1,700 images one by one,” says Michelle Yi, Slalom solution principal. “We wanted to be able to scale that work with machine learning.”
What the new process looks like…
"First, we converted all the tissue images from their proprietary format into a standard TIFF format and saved them on Google Cloud. Now, the images can be analyzed by a machine, and if anything ever happens to the physical slides, the data won’t be lost.
The next step was to scrub the tissue slides of any inconsistencies that could skew the analysis. A lot has changed since 1992 in terms of how pathologists treat the slides. In the 90s, pathologists mixed the tissue dye by hand, which means there’s been a lot of color variations in the slides over the years. “We had some slides that were a light pink and some that were a dark purple,” says Gaudet. Also, some pathologists would write directly on the slides with Sharpies, circling a tumor or making notes."
Once we flagged and filtered out any irrelevant markings or coloring, we were able to set up unsupervised machine learning. We told the machine to identify patterns in the tiles and create 10 clusters. Clustering is when the machine groups similar patterns, like your phone automatically searching through your photos and creating a photo album of your daughter.
“We fed the computer no information about what it was going to find,” says Gaudet. “We wanted to let it tell us where to go.”
"The machine created some clusters that the team understood, like identifying the grade of cancer, which validated that the machines were on track. “But there are also new patterns that we’re not yet unable to understand why they were clustered, which was the goal,” says Gaudet. “For example, clusters two and three—well, to my eye they look exactly the same but that’s the whole premise of the project, for the machine to identify differences that the human eye can’t.”
And the time saved is invaluable. “It could have taken a pathologist three years to do what Slalom helped us do in three months,” says Gaudet.
ACS is now analyzing these clusters to discover what the patterns are. Why did the machine group these together? What do they have in common? Are there lifestyle, diet, reproductive factors that are connected to that pattern?
“We’re looking at the clusters that the Slalom team provided us and relating them back to breast cancer survival,” says Gaudet."
- Austin
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