In this short survey, we want to find out how you and your peers in the healthcare and life science space are using data science and big data technologies.  The survey should take 5 to 7 minutes, and your responses are completely anonymous.
 
Complete the survey and we'll send you the survey results and a free pass to the virtual Healthcare NLP Summit (Apr 6-7, 2021.)

If you have any questions about the survey, please email us: survey@gradientflow.com. We really appreciate your input!

Note: All questions in the survey require a response

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1. Who are the intended users of the AI applications that your organization builds? (select all that apply)

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3. What is the total size of your organization, including all locations where it operates? (select one)

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4. Which of these job types most accurately describes your role? (select one)

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5. What is the stage of AI adoption in your organization? (select one)

If you have an AI system for healthcare or life science in production today, please answer all the following questions only with regard to that production system. Please do NOT include projects that are still in development or evaluation stages.

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6. On what types of data does your system apply AI models? (Select all that apply)

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7. On what types of data do you expect to train or apply models in the next 1-2 years?  (Select all that apply)

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8. How important are the following requirements when evaluating a machine learning, NLP, or computer vision solution? (1=Not Important, 5=Very Important)

  1 2 3 4 5
State-of-the-art Accuracy
Scalability to large datasets
Speed of training or inference
Production readiness
Fit with existing software stack
Healthcare-specific pre-trained models
Ability to train your own models
Open-source or open-core software
No data sharing with software vendor

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9. Which of these are you using today to build your ML / DL / NLP / AI models? (check all that apply)

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10. Which of these do you plan to use in 1-2 years to build your ML / DL / NLP / AI models? (check all that apply)

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11. How important are the following requirements, when evaluating a locally installed software library or SaaS on which your AI project depends?  (1=Not Important, 5=Very Important)

  1 2 3 4 5
Implements state-of-the-art techniques (like deep learning, transfer learning, or reinforcement learning)
Implements healthcare-specific models & algorithms
Production ready codebase
Large and active user community
Regularly updated with new and improved functionality
Optimized for modern hardware (like GPUs or TPUs)
Fits with our existing software stack

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12. If your organization uses or plans to use outside consultants, how important are the following requirements for a consulting company that will deliver part of all of your AI project? (1=Not Important, 5=Very Important)

  1 2 3 4 5 N/A
Experts in machine learning, deep learning, NLP, or computer vision
Experts in healthcare data engineering, integration, and compliance
Medical doctors or other clinicians in our project’s specialty
Experts in MLOps (model deployment, operations, and governance)
Product managers to design how the system will deliver business outcomes
Local consultants who can work on-site with our team
Education and on-the-job training to grow our in-house AI talent
Faster time-to-market, compared to building the system in-house
Cheaper than building an in-house team
No sharing or derivative rights of the data or code with the consulting company

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13. For which of these functions do you have a software package that you currently use, or expect to use before the end of 2021? (Select all that apply)

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14. How do you validate that an AI model is ready for production use? (Select all that apply)

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