MEDICAL AL CLOUD
Support your doctors and your patients
Information is key in the healthcare sector. Nowadays, the unprecedented amount of medical data is overwhelming and impossible to process without technical help. This is why all Health products are supported by our Medical AI Cloud – AI cluster leveraging Machine Learning and structured medical knowledge in order to automate medical data analysis, lower the overall costs of healthcare and streamline treatment processes by taking over some of the doctors’ responsibilities.
Thanks to AI and ML we can analyze even large amounts of data almost instantaneously. This allows for the automation of processes, quicker diagnostics, and more efficient treatment, saving both patients and doctors time.
Organizing data and medical knowledge
Creating connections in the immense amount of medical data without the help of AI would be impossible. These correlations are the key for monitoring individual and population health. Linking and ordering the data allows healthcare to be more patient-oriented and personalized.
Simplification of the treatment process
Automation and streamlining of the information exchange process take a load off the patients and doctors. AI supports the communication between devices, patients and medical facilities, and ensures that all the needed data is in the right place, easily accessible and secure at the same time.
Increased efficiency and quality of medical care
Utilizing AI in healthcare means that medical personnel can actually do the most important part of their job - treat and take care of the patients. They have more time for in-person contact, supporting and educating patients. It can help with their work satisfaction, improve workforce retention, and obviously, deliver better-quality care for patients.
All Medical AI Cloud use cases ultimately lead to cost reduction. Organizing of the data, quicker and effective information analysis, and automation of processes mean more efficient healthcare. Doctors have more time to treat and patients have more tools helping them to stay healthy. What else does it mean? Early diagnoses, fewer readmissions, better outcomes.
The Science Behind the Solution
The Medical AI Cloud algorithms are adapted depending on the problem that needs to be solved. Their main task right now is the ECG analysis, which involves Digital Signal Processing, Machine Learning, and Statistical Analysis. Combination of these algorithms is set as a pipeline in which several stages are specified, such as heartbeat detector, signal quality assessment, and disorder detection. To ensure maximum detection accuracy different Deep Neural Architectures are used, e.g. Convolutional Nets for local patterns detection, Recurrent Nets for time series dependencies, Autoencoders for learning on non-annotated data.
Another task for Medical AI Cloud is a semantic text analysis, which is used for Document Classifier and Medical Knowledge Base analysis. Based on Decision Trees, after basic text manipulation, the algorithm is able to detect the type of medical document as well as interpret basic information on it.
The algorithms of statistical data analysis are used to support Medical e-Interview and for Patient Health Metamodel analysis. Together with Machine Learning models, they support Medical e-Interview and make medical treatment recommendations.
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