Advancing life sciences and healthcare data management

Rulex empowers healthcare and life science organizations to leverage sensitive data while maintaining high standards of data governance and privacy.

Rulex Platform can overcome the retrieval, integration, and accuracy challenges of vast medical datasets, by creating a unified view and efficiently detecting and correcting administrative errors in electronic health care records.

Thanks to Rulex’s eXplainable AI capabilities, researchers can find innovative patterns in medical data, enabling doctors to provide personalized diagnoses and treatment plans.

Life Sciences & Healthcare Case Studies E-book

Improving lives with next-gen technology

Powered by Rulex Platform, healthcare professionals have enhanced patient care and accelerated medical research by implementing solutions ranging from detecting errors in medical records to tailoring diagnostic predictions, analyzing gene expression, and more.

Download our use case e-book to explore some of these success stories.

WHY RULEX

SOLUTIONS

USE CASES

FREE RESOURCES

WHY RULEX
SOLUTIONS
Use Cases
Free Resources

Rulex Platform

Why Rulex is different

Transparent technology

Transparent technology

Rulex’s native eXplainable AI provides transparent explanations for every prediction, which are indispensable for healthcare professionals seeking to adopt AI for critical tasks such as personalized diagnostics and treatment planning.

Compliant processes

Advanced data governance

With its advanced data authentication, authorization and encryption capabilities, Rulex ensures data integrity, safety, and compliance, enabling life science organisations to guarantee privacy and protection of sensitive data.

Intuitive software

Intuitive software

With a WYSIWYG drag-and-drop interface, Rulex Platform enables researchers to work independently on their specialized data, finding patterns, testing hypotheses, and securely sharing results with healthcare and pharmaceutical professionals.

Solutions

What we do for healthcare and life sciences

DATA SOURCES

DATA AGILITY

Collecting and integrating data from diverse sources and formats, facilitating analysis.

DATA QUALITY

Correcting errors in medical data through a multi-faceted data quality solution.

EXPLAINABLE AI

Deploying native XAI to support clinical and operational decision-making.

OUTPUT

Streamlining data orchestration

Healthcare organizations deal with vast amounts of biological and clinical data from different sources, which is challenging to efficiently collect, integrate, and analyze.

Rulex Platform enables organizations to swiftly orchestrate data, incorporating robust security measures to protect sensitive information, such as patient records and genomic data.

After aggregation and analysis, results can be safely shared with multidisciplinary teams and organizations in any format, from attachments in triggered emails, to files in cloud storage, facilitating collaboration and communication.

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Correcting errors in medical records

Errors in medical data can have serious consequences, from jeopardizing patient safety to causing delays in treatment and surgical interventions, not to mention the far-reaching risks resulting from inaccurate research.

Rulex provides a multi-faceted data quality solution tailored to specific needs. The solution encompasses conventional data cleansing, streamlined rule-based validation, and augmented data quality driven by our proprietary eXplainable AI algorithm.

Working with complete and correct data enables healthcare professionals and researchers to make informed decisions, ultimately leading to improved health outcomes.

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Leveraging explainable AI for medical research

AI analytics holds tremendous potential for advancing medical research, assisting clinical experts in identifying intricate correlations within extensive datasets that may pose challenges for conventional analysis.

Rulex’s native eXplainable AI algorithm, the Logic Learning Machine (LLM), produces fast and accurate predictions, generated as understandable if-then rules. This transparency can guarantee the absence of bias in any analysis, upholding essential ethical AI standards.

For its accuracy and transparency, Rulex’s LLM has supported numerous medical research projects, ranging from extracting rules for diagnosing pleural mesothelioma to predicting obstructive sleep apnea in people with Down Syndrome.

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USE CASES

Rulex for healthcare and life sciences

Improving hospital medical records accuracy

Errors in medical records can have important consequences, from minor billing or admin blips to major errors, such as delays in scheduling surgical interventions.

In collaboration with Deimos, Rulex employed its eXplainable AI to identify inconsistencies between diagnosis, surgery, and medical procedures in the Alto Adige Health Authority’s hospital discharge forms.

Rulex’s XAI generated if-then rules to automatically check hospital records, enabling the identification of probable error locations.

This resulted in time savings for personnel and enhanced data accuracy.

Establishing effective metabolic control

One of the primary goals of diabetologists is to establish effective metabolic control in type 2 diabetes patients, measured through hematic levels of HbA1c, without causing weight gain.

In collaboration with Deimos, Rulex empowered the Italian diabetology association with its XAI technology to extract and rank the factors most strictly associated with reducing HbA1c levels. The study involved vast amounts of raw data, including the medical records of 2 million diabetic patients and the data collected from medical visits over a 10-year period, with over 137 variables per patient.

Innovative correlations were identified, leading to more efficient care for diabetic patients.

Tailoring diagnostic predictions

Precision medicine aims to tailor the diagnosis, follow-up, and management of individuals based on their genetic and environmental background. The process is challenging due to complex medical traits and multiple variants, and becomes increasingly more complex for rare diseases, which have reduced historical data.

Collaborating with the medical departments of Milano-Bicocca and Humanitas Universities, Rulex tested the feasibility and accuracy of predicting the risk of primary biliary cholangitis using its eXplainable AI.

The analysis of high-dimensional genomic data revealed new patient clusters and correlations, resulting in a the formulation of targeted treatment plans.

FREE RESOURCES

Free resources to dive into clinical data management

Drive medical research further with Rulex Platform

Rulex Platform