Machine Learning Project Roadmap

Before you begin, get an actionable roadmap outlining the components you’ll need to make your ML project for pathology a success.

In 3-4 weeks, you’ll have a clear plan for your project.

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Afraid your machine learning project will turn into an endless stream of failed experiments?

Machine learning projects are complex and iterative with uncertain outcomes. It’s not simply software but the intersection of software, engineering, and science. And this field moves fast. Deep learning barely existed a decade ago, and the tools and research are constantly evolving.

The decisions you make at the very beginning of the project are going to affect everything from here on out. You don't want to start out on the wrong foot because that could jeopardize the success of the project or make it really expensive and time-consuming. You know that this ML product or service can play a critical role in the success of your business, but is your team up to the challenge?

You’ve tried to hire the best talent, but ML experts are hard to find – and expertise in your domain is even more elusive. How will you know if the direction you’re going aligns with current or emerging best practices? Is there a more recent advancement that can tackle your challenge more efficiently or with superior results?

Clear strategy for implementation

Imagine your ML product or service setting the standard for the industry. As you start down this road, envision having a clear strategy for your project. A plan for data, modeling, and validation based on expectations from prior research.

Before you implement anything, you’ll understand the possible outcomes from your project and what it’ll take to achieve your desired results. Your project will progress smoother and with confidence.

You'll have a recognized expert in ML only a phone call away. Your team wouldn't get stuck debating approaches or going down rabbit holes while evaluating a method.

The impact on your business of a successful ML implementation is immense. Set your project on the right path from the start.

Get a customized Machine Learning Roadmap incorporating best practices for pathology

Using our proven process, we'll assess your planned project. We’ll focus on your current datasets, target task, and desired outcomes. We’ll outline our findings in a report that will provide a strategic plan for advancing your ML project and ensuring that it can support your goals.

Results:

  • Increased clarity on the scope of work
  • Decreased uncertainty for the implementation phase that follows
  • Decreased likelihood of going in circles or wasting time on unsuccessful approaches
  • Confidence that you're incorporating the latest and greatest tools and techniques
  • Save time and money by identifying existing toolkits instead of implementing from scratch
  • Increased likelihood of success

Here’s how it works:

Our meetings will take place over Zoom over the course of 3 to 4 weeks. You’ll start by filling out a questionnaire with some background information about your project. We’ll dive deeper into this in our kickoff meeting, examining the desired outcomes for your project and what you’ve tried so far.

By our second meeting, we’ll have some possible solutions to present to you. We’ll talk through which will be most suitable for your application. Subsequent meetings will refine our strategy for data and annotation requirements, model development, and validation until we’ve settled on the best option for you. We’ll review the roadmap in our final session.

A six week check-in is also included in case you have any follow up questions as your team begins implementing the roadmap.

Deliverables:

You will receive a strategic roadmap detailing each of the components below:

  • Images and annotations: challenges, preprocessing, and cleaning requirements
  • Expectations from existing tools and research: software and research literature review
  • Modeling: architecture and training
  • Validation: metrics, generalizability, and error analysis

100% money-back guarantee!

If you don’t feel the ML Roadmap is the right fit for you, just let us know at the end of our kickoff meeting and we’ll refund your payment in full.

Don’t just take our word for it…

Pixel Scientia provides valuable insights for Gestalt's image analysis product development. Heather has deep understanding of digital pathology and machine learning and their application to whole slide images. Her in-depth review of the current state of the art research has enabled Gestalt to rapidly focus our machine learning efforts on approaches that are yielding value for our pathologists and their patients.

Brian Napora, Gestalt Diagnostics, VP of Sales & Product Management

Heather's knowledge of the current state of the art within the digital pathology field is second to none. Consultation on best practice approaches for deep learning model classification performance and insight into digital research perspectives were very beneficial. Discussions of prior art enabled our team to focus on novel research and refine our current AI methodologies for clinical research.

Jenny Fitzgerald, Deciphex, Director of Clinical Research & Operations

Still have questions?

What happens after I apply?

We’ll schedule a short call to confirm that this package is suitable for your project. Then we’ll send over a short contract. Once you submit your payment, you’ll receive an email with a link to a questionnaire. At the end of the questionnaire you’ll be able to schedule our kickoff call.

Will you sign an NDA before we start?

The contract for this ML Roadmap will include confidentiality and non-disclosure provisions.

We already have a great ML team. Why do we need you?

Maybe you don't need me. If your team is spending most of their time keeping up with the state-of-the-art and can outline a clear roadmap, you might not.

But if your team is spending most of their time training algorithms, that's where we come in. It is our job to stay at the forefront of the field, specifically at the intersection of machine learning, computer vision, and pathology. Through literature reviews and observations across multiple projects, we develop best practices for applying ML to pathology images and tactics for adapting new advances.

You and your team know your data and specific application better than we ever will. In developing the ML Roadmap, we build upon your team’s expertise and combine it with our knowledge of the field to get you on the path to a successful ML solution.

Our project is different from other applications. Is this a problem?

No. All projects in this space are different. This is why we focus specifically on pathology so that we can dig into research that's relevant to the field. We will be sure to assess the closest related publications. There may be some differences between these and your application, but it is essential for setting expectations for your project.

We’ve already started implementing a solution, do we still need a roadmap?

A roadmap likely isn't the best choice since you've already started your project. But if you find yourself in a jam, you might look into our other ML Services.

Some challenges don't arise until later on in a project. Like discovering that your model doesn't generalize to images from a different scanner or lab. Or analyzing your results for potential biases. These are great reasons to seek advice on a project that's already in progress but are best-suited to a different offering.

What’s next after the roadmap? Can you help us with implementation?

After completing this roadmap, we have a few options. Your team could go off and implement the algorithms outlined independently. However, our clients have found that their projects are completed more efficiently with continuous guidance. You can sign up for our Accelerator monthly service and receive advice as your team handles the implementation. For teams requiring additional support, we can assist with the implementation

Still not sure if this is the right package for you?

Schedule a free Strategy Session, and we’ll help you determine if this is a good fit.

Who are you, anyway?

Pixel Scientia Labs is led by Heather Couture. I have 16 years of experience in machine learning, 10 of those with applications to pathology. While I have no medical training, I do have a PhD in Computer Science and have published in top-tier computer vision and medical imaging venues. I write regularly on LinkedIn, for my newsletter Pathology ML Insights, and for a variety of trade publications. You may have heard me on podcasts or at conferences.

My team and I help our clients accelerate their machine learning projects with best practices for pathology and remote sensing images. We make use of the latest ML research to amplify their results and support their in-house team for the long term. Our mission is to fight cancer and climate change with AI – and we do that by strengthening the ML component of our clients’ most impactful projects.

Availability is limited

We only take on one new client a month with this ML Roadmap offer. Scheduling is first come, first served. The sooner you apply, the sooner you will get a clear path for your ML project.

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