Medical Engineering

Distributed AI Transforms Operating Room Efficiency

Fraunhofer IPA’s experimental hybrid operating theatre in Mannheim is part of the DAIOR project.
(c) Fraunhofer IPA

Research project DAIOR:

A research team of scientists from the Fraunhofer IPA, the Bosch Digital Innovation Hub at Bosch Health Campus and the Institute of Image-Guided Surgery (IHU) of Strasbourg has jointly launched the DAIOR project (»Distributed Artificial Intelligence for the Operating Room«). Within the framework of the project, the project partners are working on realizing the operating room (OR) of the future with help of artificial intelligence (AI) and robot assisted telemedicine. To achieve this, the research team is pursuing two directions. The first is to develop federated learning approaches to exploit surgical data from different clinical centers and build new AI-methods to support surgeries in real time. The second is to deploy cross-site AI supported, robot assisted telesurgery, even across national borders.

A research team from Fraunhofer IPA is working with the Bosch Digital Innovation Hub at the Bosch Health Campus and the Institute of Image Guided Surgery (IHU) of Strasbourg to use data to help medical staff during a patient’s treatment or surgery. By analyzing data, optimizing workflows and using empirical values from previous surgeries, AI algorithms will be trained to support clinical staff in real time and independent of location. This ultimately aims to improve patient care.

Local knowledge as cross location training data for AI model

The use of medical data is usually limited to one site. Treatments are site dependent because there are hardly any possibilities for data exchange in the healthcare system. Another challenge is the variety of formats of the data such as images, texts, and videos. These make it difficult to recognize correlations and use them for the treatment of patients. The DAIOR project aims to change this. AI models, trained with the locally available data and data from other centers using distributed learning approaches, will be the enabling technology.

»The knowledge can thus be used elsewhere without sensitive medical data leaving the respective location,« says Johannes Horsch, one of the DAIOR scientists. In this way, distributed knowledge is bundled and made available regardless of location. »Through the methods of federated learning, training data from different locations can be used in DAIOR, even across national borders, while the data remains at the site, thus ensuring protection for patient data at the same time.«

Location independent operations with robot assisted telesurgery

The core of the collaboration between Fraunhofer IPA and IHU Strasbourg is based on the joint project »5G-OR« and the communication infrastructure that has already been successfully established and installed. The 5G infrastructure implemented will be used to realize remote surgery. An AI model for cross location robot assisted telesurgery, will compensate for delays in data communication on both sides by predicting the subsequent steps. »It works in a similar way to our brain,« explains Horsch. »Our brain is constantly calculating possible immediate future scenarios. The AI acts in exactly the same way.« This AI model will be able to predict the next steps and assist surgeons.

Fraunhofer IPA’s experimental hybrid operating theatre in Mannheim is part of the DAIOR project.
Fraunhofer IPA’s experimental hybrid operating theatre in Mannheim is part of the DAIOR project. (c) Fraunhofer IPA

With this robot assisted telesurgery, in accordance with the scientists’ goal, it will soon be possible to perform surgeries via the internet, regardless of location. This is a milestone in the care of patients, especially in emergency medicine, where seconds often matter, for example in the case of a heart attack or stroke. Surgeries can be performed faster and patients can receive better medical care, for example, if surgeons do not have to change locations for a surgery. This, in turn, should be noticeable for the patients, as clinical staff will have more time available for treatment elsewhere.

Long term Franco-German cooperation

DAIOR is already the second long term cooperation between the Fraunhofer IPA and the IHU Strasbourg and falls into a plethora of projects between the three partners. Fraunhofer IPA and IHU were, e.g. already able to realize the »5G-OR« project together, as mentioned. The DAIOR project strengthens the Franco-German cooperation once again and enables an international technology and knowledge transfer.

IHU Strasbourg is a multidisciplinary institute dedicated to innovative image guided therapies for patient care. Its research and development activities focus on minimally invasive precision interventions enhanced by virtual reality technologies, robotics and artificial intelligence, and novel »patient journeys« combining accelerated diagnosis, outpatient surgery and improved post operative rehabilitation.

With its focus on medical robotics, the Fraunhofer IPA sees AI as an opportunity to provide surgeons in particular with increasing support through intelligent assistance systems and as a way to automate substeps of surgeries. Telesurgery was identified as an important milestone here, as it already includes the infrastructure necessary for automation and offers the possibility of collecting large amounts of data from the interventions.

The Bosch Digital Innovation Hub formerly known as KTBW is an agile innovation and implementation unit at the Bosch Health Campus (Stuttgart) with close, long term and successful cooperations with the two aforementioned institutions and long-standing networks in the Mannheim and Strasbourg ecosystems. It aims to increase the implementation rate of research projects, especially in the field of digital innovations and AI applications in healthcare, and acts as a catalyst for AI and digital healthcare innovations and innovative care concepts.

Fact sheet

Project: »DAIOR – Distributed Artificial Intelligence for the Operating Room«

Project duration: 01.07.2023 to 30.06.2027

Project partners: Fraunhofer Institute for Manufacturing Engineering and Automation IPA, Bosch Digital Innovation Hub (KTBW), Institute of Image-Guided Surgery (IHU) of Strasbourg

Funding volume: €1.284.017

Funding: Federal Ministry of Education and Research (BMBF)

https://www.ipa.fraunhofer.de/en/press-media/press_releases/distributed-artificial-intelligence-to-improve-patient-care-in-the-operating-room.html

Comments (0)

Write a comment

Related Posts

High-resolution mapping of enzyme activity in tissues. Credit: Angewandte Chemie
Medical Engineering

Fluorescent Probes Reveal Enzyme Activity in 3D Organs

It is now possible to obtain three-dimensional, high-resolution images of enzyme activity in tissue samples or whole organs—thanks to probe molecules that anchor fluorescent dyes within tissue as they are activated by enzymes. The organ being mapped is made transparent by a clearing process. As a Japanese team reported in the journal Angewandte Chemie, this allowed for visualization of differences in aminopeptidase N activity and the effects of inhibitors in mouse kidneys. Enzymes play a crucial role in regulating physiological…

By using their high-precision, high-efficiency gene editing technique, NISHIDA Keiji and his Kobe University team engineered aLactobacillusstrain that could produce yogurt with less than a tenth of a chemical that is associated with aggravating type 2 diabetes, making it safer to consume for people with the condition. Nishida says: “The bacteria we produced are not subject to regulations concerning genetically modified organisms when used as foods, supplements or medicines. We thus expect that they can be readily commercialized after appropriate safety confirmation.” Credit: NISHIDA Keiji
Medical Engineering

DNA Base Editing Advances Lactobacillus Strain Development

A Kobe University team was able to edit the DNA of Lactobacillus strains directly without a template from other organisms. This technique is indistinguishable from natural variation and enabled the researchers to create a strain that doesn’t produce diabetes-aggravating chemicals. Humans have improved the microorganisms we rely on for millennia, selecting variants that are better able to produce wine, yogurt, natto and many other products. More recently, direct genetic modification has emerged as a tool to exert more precise and…

mHealth radionomic analysis of grayscale photos of the eye’s conjunctiva help predict anemia prediction in school-age children. Each analysis focuses on extracting predefined mathematical characterizations of spatial and textural patterns associated with anemia. Credit: S. S. Hong et al., 10.1117/1.BIOS.2.2.022303.
Medical Engineering

Smartphone Eye Photos Could Help Detect Anemia in Kids

Noninvasive method detects anemia in children by analyzing smartphone photos of the eye’s conjunctiva Anemia, a condition marked by low levels of hemoglobin in the blood, affects nearly 2 billion people worldwide. Among them, school-age children in low- and middle-income countries are particularly vulnerable. Left untreated, anemia in children can interfere with growth, learning, and overall development. Detecting the condition early is essential, but standard diagnostic methods require blood samples and lab equipment—resources that are often unavailable in low-income areas….

A graphic representation of the starfish-inspired wearable device alongside biological starfish. Credit: Courtesy of Zheng Yan
Medical Engineering

Starfish-Inspired Wearable Tech Innovates Heart Monitoring

Designed by University of Missouri researchers, the device includes AI technology to detect potential heart problems with over 90% accuracy, making it a promising tool for at-home monitoring When we move, it’s harder for existing wearable devices to accurately track our heart activity. But University of Missouri researchers found that a starfish’s five-arm shape helps solve this problem. Inspired by how a starfish flips itself over — shrinking one of its arms and using the others in a coordinated motion…

Feedback