KNIME Powers Healthcare with Data Science
Combine clinical and patient data and protect patient health with more accurate diagnoses
Improve the quality of patient care through faster insights into patient health
Ensure patient health data privacy with auditable processes, automation, and on-time reporting
Why KNIME for Healthcare
Sophisticated Analytics, Intuitive Interface
Healthcare professionals need a tool that can perform complex operations while being simple to use for all stakeholders. KNIME’s intuitive interface enables medical practitioners through to healthcare administrators to make sense of their data without needing to code. At the same time, ease of use does not compromise functionality. Data scientists and more advanced technical users can model in the environment or tool of their choice through integrations with AI/ ML libraries, and scripting languages like Python, R and more.
Enterprise-scale Data Privacy and Security
KNIME’s secure, consistent environment respects patient health data privacy while making the data accessible enough to give professionals what they need. Security and control is addressed by native KNIME functions such as versioning, tracking, and mapping metadata, while data privacy and security can be controlled through a centralized administration. Healthcare professionals can collaborate and share work and expand the use of analytics across teams within a secure platform.
A Complete Data Science Platform
When healthcare data is not easily collected and merged this can result in missing data. Missing data can lead to incorrect treatment decisions compromising the patient’s condition. In KNIME, everything from collecting data, through to applying novel and highly advanced AI-based algorithms on big datasets and production can be handled with the most complete analytical platform possible. Healthcare organizations can design models, test, validate, and automatically deploy them continuously for end-to-end data science life cycle support.
In research, to discover and develop medical solutions, labs need a software platform flexible enough to enable innovation by seamlessly integrating new or improved algorithms. KNIME’s open-source approach keeps teams on the bleeding edge of modern data science. No vendor-developed tool can keep pace with the innovation driven by an active open-source user community.