Located and founded in Karlsruhe, Germany, medicalvalues offers an AI-based solution that converts medical data into valuable diagnostic insights. The company aims to simplify the complex diagnostic decision-making process by gathering and interpreting vast amounts of data from various disciplines. This approach allows for a more comprehensive and holistic patient assessment, which combines real-time patient information with digitized medically validated research knowledge. By doing so, the system can provide recommendations on suspected diagnoses and the best next diagnostic steps.
In addition to clinical decision support, Medicalvalues provides several modules that aid in data and workflow management, semi-automated report generation, and a machine learning environment for data scientists. Their approach towards integrated diagnostics improves the quality of diagnostics, reduces the burden on physicians, and optimizes data utilization for early and precise diagnosis, including for rare diseases that are often overlooked.
Medicalvalues’ unique selling points include their focus on constituting the patient situation across all clinical disciplines and the integration of every piece of information that may contribute to a diagnosis. They have a hybrid approach that links research knowledge with real-time diagnostic data from various sources. Their prebuilt and medically validated diagnostic pathways are applicable in various industries, including healthcare service providers, insurance companies, medical software vendors, and pharmaceutical companies. Additionally, their approach relies on whitebox AI to ensure explainability and acceptance of their decision support, combining a centralized and decentralized architecture for knowledge management and machine learning components.
In summary, Medicalvalues’ AI-based solution offers a comprehensive and integrated approach to diagnostic decision-making, providing valuable insights to medical professionals across different disciplines. Their unique selling points and various modules make their solution scalable and productive, enabling early and precise diagnosis, particularly for rare diseases that are often challenging to identify.
Role in the project
Medicalvalues will incorporate symptoms, pre-existing conditions, laboratory parameters, imaging results, anthropometric and physical parameters, and lifestyle aspects associated with an increased CVD risk into risk determination using validated medical algorithms. This helps to detect a possible disease at an early stage or even to prevent the development of the disease. The knowledge graph prediction model acts as an “umbrella” which orchestrates the ML prediction model. A white-box evaluation of the data using artificial intelligence is intended to optimize diagnostic processes. A dashboard summarizes all input and output data for integrated diagnostics in clinics. The GDPR is at all times considered.
Carmen Diker started her education at the University of applied sciences of Worms from 2013 to 2017 on International Management with studies abroad at Cape Peninsula University of Technology in 2014 and the Emirates Academy of Hospitality Management in 2015. After her successful bachelor’s degree, she started at Roche Diagnostics until 2021 as a trainee for market development and for medical & scientific affairs. In parallel she accomplished her Master of Science degree at the Friedrich-Alexander-University of Erlangen in the field of Medical Process Management. Due to her broad knowledge based on different studies and deep experience working for Roche Diagnostics she is medicalvalues expert for medical process management and data flows in healthcare environment. She will be the support for medical data flows under consideration of a possible medical environment as well as for the medical process management and knowledge graph enrichment and validation within this project.
Maximilian Kucher studied mathematics at KIT until 2016, he studied computer science at the University of applied sciences of Karlsruhe (HKA) on bachelor and master’s degree until 2021. In 2018 he was working for ITK engineering where he optimized a computer vision algorithm in the context of functional safety and afterwards for CAS Software AG with a black-box and derivative-free optimization in a configuration system until 2021. He has full understanding of advanced mathematics, machine learning expertise and data handling in the automotive and IT industry. In this project he will be the second developer for AI and risk score handling.
Maren Klimm studied cognitive science at the Eberhard-Karl-University of Tübingen (EKUT) until 2018. After her bachelor’s degree she studied at the University of applied sciences of Reutlingen at Human Centered Computing where she got her master’s degree. Her master thesis “Human-machine interaction of autonomous driving” was done at the Bosch company in 2021. She moved on to medicalvalues where she is in lead for UI/UX design for our machine learning and knowledge graphs to create user friendly interfaces for physicians and medical staff. She will be in lead for UI/UX design, design thinking methodology and handling the user experience.