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The potential for machine learning systems to improve outcomes for patients and health care systems alike is monumental. For patients, the benefit is more targeted and effective care, while health care systems can reduce costs and improve experiences for everyone.
There are hidden goldmines waiting in existing publication data and metadata. We have experience in designing and developing systems that review research and compare the occurrences of words to help uncover hidden possibilities. Some of our capabilities include:
Using natural language processing to look at drug names, especially new drug names.
Using latent knowledge to suggest new applications for existing treatments.
For the researchers and patients of tomorrow, finding new and more effective treatments is an opportunity that should not be overlooked.
Lemay.ai has had extensive and first hand experience in both clinical trial design and review, particularly in the area of data anonymization recommendations.
Medical specialists spend hours looking at graphs, images and forms to identify and assess both nascent and progressing health conditions. When you speed up that process, you make it possible to treat conditions early and reduce wait times for all patients. Lemay.ai’s solutions include the following:
Image recognition systems that catch problems busy practitioners miss.
Intake form processing to speed up risk factor identification for verification and treatment.
Patient data cleanup, for example, separating “real” data from false positives caused by unintended movement.
The end result is that more conditions are caught sooner when they are more treatable.
It is possible to both improve efficiency and patient care at the same time. Talk to our AI experts about your specific situation to begin building a better system for your stakeholders.
Our goal is to be as helpful as possible.