Medical platform for disease and pathology prevention
For the last decade or so, there have been comprehensive platforms that facilitate medical or hospital management between doctor and patient, commonly referred to as HIS. The acquisition of this tool has greatly facilitated medical centers, since these platforms improve the relationship in different aspects. Despite all these improvements between doctor-patient, these tools do not have predictive or preventive functions, so they still have technical limitations, as well as a wide range of possibilities that, through new developments and functionalities, could drastically increase the performance of HIS platforms.
To address this, we have developed a unique solution that, to date, cannot be compared to any similar tool in medicine. We have drawn on the latest advances in artificial intelligence, Big Data and IoT Full project title: Intelligent data mining and pattern recommendation system capable of automatically producing engineering project documentation .
-Full project title: New AI-enabled integrated medicine management platform with preventive capabilities against the onset of diseases and pathologies.
– Project Dossier Code: 2021/C005/00148993
The complexity related to the modeling of data extracted from physical or bodily symptoms, together with the biodata of each patient, represents an important technological challenge for today’s society, since it is a problem that directly affects the entire population and that, at present, there is no technological solution on the market. Thus, we propose the acquisition of data through different channels. Physical and body data would be collected by wearable devices and by pattern recognition from video. On the other hand, biodata related to medical history and other measures such as age or population would be collected through NPL or the user’s own platform records.
The process
For integration, two platforms were proposed: Upmedica and Binah.AI. The former, while providing a solution to a myriad of problems, did not have AI systems. The second is a video and AI-based software solution that allows the extraction, in real time, of a wide range of health parameters provided by the end user in a simple and easily accessible digital format.
To be able to do this, we have converted the influx of data into a Data Lake of knowledge that allows us to feed different AI models, as well as to train anomaly detectors. Thanks to the study of data variability, models have been trained to detect possible medical alerts before they happen and thus monitor the patients who need it most.
Combining both, we have obtained a platform that integrates a wide range of functionalities, where we have also used Beat One devices for data collection. For data management, we have created a monitoring center, which is fed back to ML. To reduce and simplify the analysis, a triage system has been created using advanced algorithms that interpret the data captured by different sources.
The solution is based on an artificial intelligence, IoT and data approach.
Development with Machine Learning and Data Lake.
Unique solution for medicine with the latest technologies
Results
- The inclusion of AI-powered patient analytics within remote monitoring systems will enable the stratification of continuous patient data to make it actionable.
- Medical teams will be able to monitor thousands of patients at a time, and rely on advanced systems to triage and direct care to those patients who need it most, maximizing hospital resources.
- Each physician will only have access to their patients’ data, but the platform will analyze and learn from the data as a whole, creating a large mass of information from which valuable insights are gained.
- Human effort is reduced to a minimum and work efficiency is increased.
- AI-driven functions, such as early warning scoring systems, will help to detect potential deterioration early, giving an advantage to take preventive measures and improve patient care.
We are ready for new challenges
