Medical algorithms
Develop medical algorithms with us. Save time and scale your business.
Our team includes following experts: scientists, business analysts, bioengineers, annotators, software engineers, and also machine learning/deep learning specialists. Moreover, with our competencies, we successfully undertake projects of diverse complexities, leveraging various types of medical data.
Medical algorithms development in detail
Machine Learning
Graylight Imaging experts worked out a Machine Learning pipeline to ensure efficient and fast development of AI algorithms – both machine and Deep Learning.
Deep Learning
We are experienced in applying deep learning techniques to various tasks, including medical imaging analysis, clinical decision support, and also drug discovery.
Ground-truth preparation
Our specialists developed a ground-truth preparation process. Additionally, we can support you with an annotating team as well as cohort data optimisation.
Performance
We carefully listen to our clients and jointly determine the method for measuring algorithm performance, aiming for generalization and bias-free models.
Full pipeline for ML processing
Benefit from our complete pipeline for Machine Learning data processing, enabling both rapid and efficient creation of customized solutions for our partners.
Expertise in diverse data
Although our primary area of interest is medical image analysis, in our success stories we have projects based on other data as well as vision analysis.
Our medical algorithms development pipelines get your project covered
Machine Learning medical project lifecycle
How we work on medical algorithm development
Shape. Firstly, we will make sure we fully understand your requirements. Secondly, it will be determined what the collaboration will look like. Our experts will also identify the key elements of the solution and deliverables needed for certification.
Integrate and verify. Once the various elements of the solution have been made ready and tested in isolation, they are assembled and then comprehensive verification takes place through formal tests.
Create. In the first place, we consider several network types to establish algorithms. Data will be used to train the model, at first. Then, we’ll test and improve this one using more data.
Implement. Afterward implementation, algorithms can still be tested and refined based on actual data. Moreover, if needed, your model can be refined in the future.
Proven experience in Machine Learning medical algorithms development
Let’s work on your challenges together!
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