Mosaic Factor’s higher priority in Healthcare is making use of data to improve patient care and monitoring in a safe manner to optimise healthcare systems resources and assisting healthcare professionals.
We use Big Data analysis enriched with AI algorithms that lead to breakthroughs in healthcare, from predictive analytics to personalised treatments to improve healthcare systems.
TYPICAL USE CASES WE TACKLE FOR HEALTHCARE ARE:
Treatment personalisation
AI-enhanced clinical documentation for pattern retrieval of potential disease.
Enhanced patient communication
Automated reports from multiple exams, Decision Support Systems, remote consultations, real-time health monitoring, improving treatment adherence.
For healthcare structures and Public Bodies: forecast disease outbreaks, patterns, patient admission rates, and medication needs for healthcare organisations.
Dashboarding and Predictive analysis
Resource allocation
We analyse patient data to run AI optimisations of resources and predicting demand. Ie. patient admission rates, equipment usage, medication needs, aiding in efficient staff scheduling and inventory management.
Collaboration with big data projects to generate new data models to improve health conditions amongst different population segments, especially when it comes to treatment of chronic disease.
New data Models
Identification of drug & therapy
Automatic prediction of novel drugs performance being able to test new drug formulations on synthetic data patients.
Explaining AI models in healthcare for digital identity and data governance purposes. We help healthcare organisation which already run big data analysis and ML models to explain and assess their accordance to GDPR and data compliance.
TRUSTWORTHY AI
The enhanced capabilities of AI within the healthcare sector are major. Notwithstanding, there is highly confidential and sensitive data in health datasets and its inappropriate use or disclosure can have serious consequences for an individual’s privacy and security.
The processing of health data is carried out always in accordance with ethical and legal principles related to the privacy and confidentiality of users, in this case patients.
Our partners
