Will artificial intelligence be the enabler for better diagnoses and therapies in future?
Whether you a medical doctor or a citizens and want to know how Artificial Intelligence (AI) can support you in your daily routine: you are definitely right here. Learn more about it in the real-world use case oncology just published in the German article “Für bessere Diagnosen und Therapien: Wie Ärzte und KI in der Krebsbehandlung zusammenarbeiten”. It outlines very specific examples where medical professionals and patients either already benefit or will benefit in near future from the adoption of optimized software tools incorporating AI technology for better outcomes.
Today, treatment alternatives for every oncology patient are individually discussed by medical
experts in so-called tumor boards. However, the molecular analysis of each tumors is very complex and the assessment of individual tumor variants time-consuming. Therefore, specialized molecular tumor boards focus also on the analysis and therapy assessment incorporating fine-grained molecular data.
We worked together with subject-matter experts to defined and evaluate a standardized clinical process, designed adequate tool support, and integrated relevant data source for an improved tumor board experience in molecular tumor boards. For example, we applied the scrum board approach, which is well-known from software engineering, to the clinical challenge.
Background
Molecular analysis of tumors is the key driver of precision medicine in oncology. It enables the matching of mutations to targeted drugs and hence more personalized treatments. With its steady advances and ever decreasing costs, it is likely to become a standard procedure for diagnosis and treatment. In molecular tumor boards, regular meetings among medical experts, treatment options are discussed and suggested for each patient based on the tumor’s genetic markup. A molecular tumor board (MTB) consists of 4 major phases: preparation, meeting, treatment suggestion documentation and follow-up. Our MTB Support Engine aims to streamline the entire process in order to tackle the key challenges of molecular tumor boards. The tool lends the Scrum methodology that has already proven itself in software development.
The most critical part of a MTB is the preparation. Genetic variants need to be researched upon available medication. For this purpose, oncologists query various databases and search engines. This is time-consuming and therefore constitutes a key bottleneck for a comprehensive rollout. The MTB support engine accelerates the preparatory research work by
Showing available information resources for a given variant
Ranking and visualizing variants by various criteria and displaying most important ones first.
Simplifying the saving of reviewed information in a click-and-collect fashion
The MTB Support Engine furthermore lets doctors generate a presentation view of relevant information with a single click. In addition, an emphasis it put on collaborative work. Every participant has access to the system allowing preparing themselves. During the meeting, decided upon treatment suggestions can be documented for inspection by the treating physician and allows a structured follow-up.
Most importantly, all information including researched annotations are saved. This allows the rapid retrieval of historic cases with genetically similar patients. Leveraging data integrated from multiple hospitals, even the discovery of novel correlations between variants and diseases is made possible in the long run.
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