Diagnostic system
from medical imaging
To meet the growing demand for care, medical technology leaders are turning to AI tools that can help radiation oncologists provide high-quality, individualized treatment faster.
- Augmenting Radiation Therapy Workflows
- Tapping into Software to Write Software
- Simple and Scalable Infrastructure
Trusted by more than 800 growing companies
What AI can do with
unstructured data in healthcare
Improve data protection and minimize paperwork
Most security disasters in the healthcare industry are caused first by human error and misuse and physical theft and hacking second. Electronic Health Records or EHRs not only structure patient information but also allow for safe access and more personalized care.
Increase diagnostics accuracy
In the US alone, over 12 million patients are misdiagnosed annually. Deep learning applied to healthcare can radically improve that statistic: Instead of following a routine checklist, healthcare professionals can benefit from the informative by-product of algorithms that can read data using computer vision,
Boost clinical performance
Running any medical facility is a complex, multi-faceted undertaking rife with the possibility of making unfortunate decisions. The obvious, well-documented risk level is high. Data-driven software provides clinicians with the opportunity to make better sense of their data – schedule more efficiently, create
Forecasting system
on pharmacological reactions
Adverse drug reactions (ADRs) are an important concern in the
medication process and can pose a substantial economic burden for
patients and hospitals. Because of the limitations of clinical trials, it is
difficult to identify all possible ADRs of a drug before it is marketed. We developed a new model based on data mining technology to predict
potential ADRs based on available drug data.
- Databases and KG construction
- Prediction model
- KG embedding
- Model evaluation
“I knew that if I failed I wouldn’t regret that, but I knew the one thing I might regret is not trying.”
Jeff Homann
AI Lab Founder and CEO
Story from our clients
Showcase of awesome works we have done for our clients
Why AI lab?
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%
Reduction in healthcare costs due to optimized clinical processes and remote care
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Reduction in time spent on routine administrative tasks
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work time savings for nurses due to the elimination of unnecessary visits
Optimization for Healthcare
Insurance companies
Insurers are using artificial intelligence and machine
learning to review medical records, optimize care for chronic conditions, identify risk.
Payers manage risk
Insurers are using artificial intelligence and
machine learning to review medical records, optimize care for chronic conditions, identify risk.
AI to optimize health
AI and machine learning move from a custom and
reactive approach to more standardized and proactive management of patient care.
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