Center for Artificial Intelligence in Medicine

How AI is changing medicine

In an article on current implementation of artificial intelligence in healthcare today, Barbara Reye explores the disruptive potential of machine learning in medicine. Examples range from intensive care monitoring and false alarm reductions over early signs for cerebral hemorrhage, medical image analysis and diagnostic support, skin cancer, newborn health and a nutrition app developed at the University of Bern to help users stay on track with a health-promoting Mediterranean diet.

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"I believe that AI is the key to a new era of healthcare."

Song Xue is a biomedical postdoctoral researcher specialized in deep learning at the AI for Translational Theranostics (AITT) group of the Department of Nuclear Medicine, Inselspital. Applying artificial intelligence to nuclear medicine, Song aims to reduce radiation in diagnostic PET imaging and to personalize dose prediction for radionuclide therapy.

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Bern Interpretable AI Symposium

One-day meeting to bring researchers together in the medical image interpretable AI community. Our hope and objective is to attempt to “open the black box”, share insights into challenges and breakthroughs in this field and to foster better interaction with each other.

Program & registration...

"With deep learning you can explore rich patterns of neural activity."

Florence Aellen is the deep learning specialist at the Cognitive Computational Neuroscience Lab of the Institute of Computer Science, University of Bern. For her PhD she works with a very interdisciplinary research team to unravel interrelations between electrical brain activity and states of consciousness. Herself originally coming from a background in mathematics and theoretical physics, she now puts her computational expertise in the service of clinical applications, learning a lot in the process.

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AI Medtech Founders

Ready to start your own AI business? Networking and insights sharing event on Women´s Day 2023 featuring four Medtech founders and hands-on tips on how to get support and funding and how to build your network.

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AI to detect lymph node metastases in colorectal cancer

Screening of lymph node metastases in colorectal cancer (CRC) could be solved by an AI-assisted diagnostic solution. A group of pathologists and data scientists led by the Institute for Tissue Medicine and Pathology, University of Bern, has proposed a deep learning–based workflow for the evaluation of CRC lymph node metastases. The approach showed very good performance, providing the basis for a computer-assisted diagnostic tool for easy and efficient lymph node screening in CRC patients.

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Measuring blood glucose with the smartwatch

Researchers at the Inselspital, Bern University Hospital, and the University of Bern developed a method that uses machine learning and smartwatch data to detect hypoglycemia. The approach was tested in a pilot study with 31 diabetes patients and could in the future be used to non invasively measure blood glucose levels as a valuable complement to existing methods for blood glucose monitoring.

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Bridging deep learning and clinical radiotherapy

The ARTORG Medical Image Analysis group (MIA) and the Department of Radio-Oncology of the Inselspital have developed an open-source, deep learning framework-independent Python package feasible for processing DICOM RT Structure Sets, in collaboration with Varian a Siemens Healthineers Company. “PyRaDiSe” (Python (Py), radiotherapy (Ra), DICOM-based (Di), auto-segmentation (Se)) goes beyond current 2D reconstruction, potentially supporting acceptance by healthcare professionals.

View the package…

Predicting heart attack from routine hospital data?

The Department of Clinical Chemistry and the Insel Data Science Center at the Inselspital have conducted a proof-of-concept study to infer the diagnosis of myocardial ischemia from predictive analytes extracted from routine hospital lab data. Authors could demonstrate that an assembly of algorithms was able to create unbiased guidelines for laboratory diagnostics by using computational evidence in today’s era of healthcare digitalization. This is an important first step towards evidence-based laboratory diagnostics and, therefore, improved patient care.

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AI-assisted interpretation in cardiotocography

Artificial intelligence is gaining interest in the field of cardiotocography interpretation in obstetrics, since it promises to remove existing biases and improve the well-known issues of inter- and intra-observer variability. A review publication by the Department of Obstetrics and Feto-maternal Medicine, Bern University Hospital, with CSEM hints at potentials of AI to help detect complications in the unborn child earlier.

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Portrait Athina Tzovara

How can artificial intelligence help to better understand states of consciousness? Assistant Professor TT in Machine Learning in Medicine, Athina Tzovara, explores brain activity data with AI to understand how brain functions change during sleep or in coma patients. She works both at the Institute for Informatics of the University of Bern and for NeuroTec, the research platform of the Inselspital Neurology Department.

Watch the video portrait...

LUMIERE Dataset for Glioblastoma Released

The Medical Image Analysis group at the ARTORG Center of the University of Bern in collaboration with colleagues at Inselspital, Bern, has released the first publicly available single-center dataset of Glioblastoma Magnetic Resonance Imaging (MRI) with expert ratings. It comprises over 600 multi-sequence MRI acquisitions and expert readings of selected studies according to the response assessment in neuro-oncology (RANO) criteria, automated tumor segmentations, and a rich set of complementary information, such as advanced imaging biomarkers, patient demographics and pathology information.

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"I would like to convert my research into a useful tool for clinicians."

Amith Kamath wishes to facilitate faster radiotherapy treatment for patients with glioblastoma through AI-supported therapy planning. The CAIM Young Researcher Award winner is pursuing his PhD at the Medical Image Analysis group of the ARTORG Center for Biomedical Engineering Research and looks forward to translating his research into a clinical tool, also through the personalized business coaching by be-advanced he received as part of his award win for “translation”.

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CAIM supports Ukrainian scientists

The Center for AI in Medicine supports scientists from Ukraine in these difficult times. Following the measures and call from the Swiss National Science Foundation to help Ukrainian researchers as well as the University of Bern’s initiative to solidarize with Ukraine and its universities, CAIM calls its members and partners to reach out and proactively seek ways to help our colleagues.

Contact info.caim@unibe.ch with ideas or requests for support.

Deep Learning detects neurodegeneration at the micrometer scale

A research group from Inselspital and the University of Bern has developed a deep learning tool that can measure neuro-degeneration reliably and significantly faster than established methods. A scientific paper now shows that the algorithm can be trained to read different types of MRI images used in everyday clinical practice. Research at CSIRO's Australian eHealth Research Centre has furthermore shown in an independent evaluation that the open-source method can measure subtle changes in the range of up to 0.01mm (reference 0.06mm).

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Survey on artificial intelligence in medicine

The Ethics Lab of the Center for Artificial Intelligence in Medicine (CAIM) collected voices from the public to learn about their perception of opportunities or risks associated to the use of artificial intelligence in medicine. The results will flow back into the center’s research activities.

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SDiPath Annual Assembly and Industry Fair: AI in Pathology

SDiPath’s second industry fair, this time focusing on AI applications in pathology.
The event takes place on-site, from 10-17:00 at the Institute of Pathology, University of Bern on Thursday, January 19th, 2023.

More information and registration...

"I felt I was part of something much bigger than us."

CAIM Young Research Award winner Charlotte Kern and her colleague Verena Schöning use different approaches such as data mining, machine learning, and modelling and simulation studies in pharmacometrics to predict the effects of medication on diseases and thus inform clinical decision making. During the COVID-19 pandemic, their research directly contributed to improved patient care.

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Averting severe embolisms through artificial intelligence

Experts in laboratory medicine at Inselspital, Bern University Hospital, have developed a diagnostic prediction model in a long-term prospective multicenter study in collaboration with data scientists at the University of Bern, which provides treating physicians with an indicator to reliably diagnose HIT (heparin-induced thrombocytopenia) - a rare but life threatening complication for hospitalized patients after major surgery or severe inflammation. The diagnostic machine learning tool derived from this research in the field of laboratory medicine is unique in the world.

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Great Interest in the CAIM Research Symposium

The first Research Symposium of the Center for Artificial Intelligence in Medicine since its official opening in March 2021 was attended by more than 100 researchers from the Bernese ecosystem around the University and University Hospital. CAIM Director Raphael Sznitman was excited to witness the beginning of promising interdisciplinary scientific discussions in the wake of the two keynote speeches and during the networking breaks. "It is great to have such a vibrant community around AI research for healthcare here in Bern," he said.

Impressions CAIM Research Symposium 2022...

Amith Kamath and Charlotte Kern win CAIM Young Researcher Awards

The very translational research of PhD students Amith Kamath, ARTORG Center, University of Bern, and Charlotte Kern, Department of Clinical Pharmacology and Toxicology at the Inselspital, Bern University Hospital, has been recognized at the CAIM Research Symposium with one of the new CAIM Young Researcher Awards each. Awards were sponsored by the Bern Economic Development Agency with a total of CHF 1000. The research developed yet a bit further into a product (Amith Kamath) additionally received 16 hours worth of personalized entrepreneurial coaching by be-advanced.

Using interpretability to improve medical AI

The Medical Image Analysis lab at the ARTORG Center has just published a study where interpretability informed sample selection from a set of radiological images. The lab, which has focused on interpretability both as a means for more transparency in medical AI workings and as a tool to improve AI itself, reports that their novel sample selection approach based on graph analysis to identify informative samples in a multi-label setting improved model performance, learning rates, and robustness when compared to state-of-the-art Active Learning methods.

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CAIM Research Symposium

On 24 November, 8.30-13.30h CAIM will be presenting updates on its funded research projects as well as two invited keynotes on AI for medicine opportunities and challenges at the University of Bern main building top floor event venue (Kuppelsaal). Meet our Executive team, our ethics specialists and the people behind our initiative DAIM and exchange ideas during coffee breaks!

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"Artificial Intelligence Advances Medicine"

Stavroula Mougiakakou, head of Artificial Intelligence in Health and Nutrition at the ARTORG Center, conducts applied fundamental research and with her team aims to close the gap between theory and practice. In the highly interdisciplinary and very competitive field of AI in medicine she sees a clear need for rigorous scientific testing that can assure approaches, tools and processes that can benefit users. At CAIM, she is Co-Responsible for Education and leads the master program "AI in Medicine".

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Less radiation with AI-enhanced PET

PET/CT can be used to clarify tumor diseases regarding their extension and therapy response, as well as to answer neurological and cardiological questions. The Bern University Hospital uses the world's most sensitive PET scanners with comparatively low radiation exposure. AI-supported image attenuation could further lower radiation and result in better imaging, as demonstrated by the Nuclear Medicine Department in Nature Communications.

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Maintaining a Mediterranean diet with your phone

Researchers at the ARTORG Center in collaboration with Oviva and with the Epidemiology, Biostatistics and Prevention Institute (EBPI), University of Zurich, have demonstrated that an AI system on a smartphone can effectively track whether a person is adhering to a Mediterranean diet (MD). MD can decrease the risk of non-communicable disease and prevent overweight and obesity. The feasibility study of the system was just published in Nature Scientific Reports.

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MADiMa 2022

The main scope of MADiMa2022 is to bring together researchers from the diverse fields of engineering, computer science and nutrition who investigate the use of information and communication technologies for better monitoring, assessment, and management of food intake.

More information and how to submit...

DAIM Lunch Talk

Dr. Lisa Koch, Institute for Ophthalmic Research, University of Tübingen, will present approaches "Towards Safe and Effective Medical Image Analysis Systems" at this lunchtime event in hybrid mode hosted by the ARTORG Center for Biomedical Engineering Research. This event runs under the umbrella of the initiative DAIM - Diversity for AI in Medicine. Participation is free. Please register.

Details and registration...

Bernese AI system receives FDA approval

An artificial intelligence system for brain tumor segmentation from multisequence MRI has received 510k clearance by the US American Food and Drug Administration on 29 September 2022. The system was developed by Prof. Dr. Mauricio Reyes and his team from the Medical Image Analysis lab, at the ARTORG Center and the Center of AI in Medicine, Univ. of Bern. Work on this important milestone by many talented PhD and Master students has started at the @MICCAI 2011 conference, receiving the 2016 MICCAI Young Scientist Publication Impact Award as well as the 2016 Ypsomed Innovation Award. It underlines the importance of Bernese research on a global scale.

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AI: Friend and helper of medical professionals?

AI is profoundly changing the healthcare system. This process poses various challenges for the medical profession. With the brochure "Artificial intelligence in everyday medical practice", the Swiss Medical Association FMH offers the medical profession an overview of AI in the medical environment. Ten demands raise awareness for the essential aspects of AI in medicine.

Read the FMH media release (German & French)...

Research Awards

CAIM launches its student research award! Apply from 6 September for best student project CAIM. Two winning projects will be announced at the CAIM Research Symposium on 24 November and will receive CHF 500 each.

Learn how to apply...

Smart Tools for Dexterity Home Training in Parkinson’s

Limited hand and finger movement due to Parkinson's disease can be counteracted to some degree with targeted physical therapy. To provide patients with individual training options at home, the Gerontechnology and Rehabilitation group at ARTORG Center has now evaluated the usability of two new interactive game sensor-based hand devices.

More about the study…

Making the most out of lab data

Every large hospital produces a wealth of data each day, holding the key to new insights into diseases and improved patient care. For machine learning and Big Data approaches to be utilized on this data, lab data needs to be FAIR: findable, accessible, interoperable, and reusable, propose a team of researchers from the Department of Clinical Chemistry at the Inselspital.

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CAIM at Uni Bern Researchers’ Night

Save the Date!
Our Center will present itself to the broader public with an interactive discovery trip of what Artificial Intelligence means and does and how it is applied today (and tomorrow) in healthcare.

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Sensor-based early detection of age-related diseases from home

Researchers at the University of Bern and Inselspital, Bern University Hospital have demonstrated how sensors that record movement patterns could help detect health problems in the elderly, including old-age depression, risk of falls or cognitive impairment, at an early stage. In the future, this could help seniors to live a self-determined life at home for longer and relieve increasing pressure on the healthcare system.

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Interview with neurosurgeon Andreas Raabe

In his career, neurosurgeon and clinic director Andreas Raabe has seen major developments in medical technology that open unprecedented possibilities for interventions on the brain and spine. With a keen interest in physics, he develops new technologies for the operating room emerging from practice at Inselspital together with the ARTORG Center.

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Hypo- and Hyperglycemia Prediction

Blood glucose decompensations of hospitalized patients poses a frequent and significant risk for patient outcomes and safety. A team of data scientists and doctors from the University of Bern and Bern University Hospital have generated a broadly applicable multiclass classification model for predicting decompensation events from patients’ electronic health records to indicate necessary adjustments in monitoring or therapy.

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Esther Brill

Esther Brill is a PhD student in cognitive neuroscience at the University Hospital of Old Age Psychiatry and Psychotherapy Bern. As a digital native she considers connecting technology and clinical work essential to fight ever more prevalent neurodegenerative diseases such as dementia through computerized cognition games.

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ARTORG Center to develop digital care assistant with QUMEA

Together with digital health startup QUMEA, the ARTORG Center for Biomedical Engineering Research, University of Bern and the Bern University of Applied Sciences (BFH) have started a project to enable hospital care teams and doctors to adapt and improve care via sensor-based technology. The project is funded by an Innosuisse grant of CHF 1.2 million under the impulse program Swiss Innovation Power.

Read the QUMEA media release...

The virtual microphone

Scientists from Bern have shown in a feasibility study that artificial intelligence can help improve understanding in noisy environments. PD Wilhelm Wimmer explains in an interview with dezibel, pro audito, how exactly this works.

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Workshop Medical Decision Support

Interdisciplinary workshop by the Technical University of Munich (TUM) tailored specifically to the needs of medical professionals and part of the TUM working group "AI for Doctors". The hybrid workshop features examples from dermatology, neuroradiology, opthalmology and pathology, a keynote by Ben Glocker (Imperial College London) and a presentation on Explainable AI by Mauricio Reyes (CAIM).

More information and registration...

AI for diabetes project MELISSA launched

The EU Research Project “MELISSA: Mobile Artificial Intelligence Solution for Diabetes Adapted Care” was launched today by a consortium of 12 partners, comprising the ARTORG Center Artificial Intelligence in Health and Nutrition (AIHN) lab, University of Bern. AIHN is the artificial intelligence expert in the project and initiated it in collaboration with Debiotech.

More about MELISSA…

Ana Leni Frei

Ana Leni Frei does her PhD in computational pathology on cell interactions in rectal cancer. She hopes to help build AI tools that can assist pathologists to understand changes that occur in the tumor microenvironments of patients receiving neoadjuvant chemoradiotherapy and hopefully understand why 20% of them do not respond to the therapy.

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CAIM participates in AI Med Summit

Just a year old, CAIM was nominated as 'Best Hospital/Institution of the Year' at the Ai Med Summit 2022. Our center was honored to present our activities to renowned AI research institutions and industry from around the world in San Francisco, USA on 25 May 2022. Although we did not bag the win this time, we take the nomination as an incentive for excellence in research and translation for next year.

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CAIM first year recap

CAIM celebrates its first anniversary with this retrospective from Director Raphael Sznitman on the milestones achieved so far.

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Using AI for patient well-being

In a recent interview with Netzwoche, CAIM Director Raphael Sznitman has emphasized the importance of real-world AI solutions to make a real difference to patient care. Referring to the first round of CAIM funded projects, he said: "All the projects aim for a tangible patient benefit – which is important to us at CAIM, as we do not want to develop technology without real added value."

Read the entire interview (in German)...

Strange dreams help your brain learn better

A study by the University of Bern Department of Physiology suggests that dreams—especially those that simultaneously appear realistic, but, upon a closer look, bizarre—help our brain learn and extract generic concepts from previous experiences. The study, carried out within the Human Brain Project and published in eLife, offers a new theory on the significance of dreams using machine learning inspired methodology and brain simulation.

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Lunch Talk on Medical Robotics & AI

Keynote on "Cognition-guided Robotics and Embedded AI for Surgeons" by Prof. Dr. Franziska Mathis-Ullrich, Health Robotics & Automation Laboratory, Karlsruhe Institute of Technology. This brown bag lunch talk is held at the ARTORG Center for Biomedical Engineering Research and marks the start of a the DAIM initiative to foster diversity and inclusion for AI in medicine research.

Program & registration...

2nd Bern Data Science Day

Second Event on data science research at the University of Bern, including artificial intelligence applications for healthcare. CAIM acts as co-sponsor of the Bern Data Science Day and presents its research in poster sessions.

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Predicting Urinary Infection with AI

In a special Issue on Urinary Stones and Infections of Diagnostics, the Inselspital, the University of Cologne and the University of Bern have published a recent AI-guided analysis of urine samples from emergency patients. The assessment of 3835 samples revealed that AI can safely rule out urinary infections in 96 percent of cases. However, for a high-confidence AI prediction of positive infections and infection types, using UFC parameters alone is not sufficient.

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Launch of DAIM - Diversity for AI in Medicine

The Center for Artificial Intelligence in Medicine (CAIM) launches an initiative for diversity and inclusion in AI research for healthcare with a keynote lecture by the renowned robotics specialist Prof. Franziska Mathis-Ullrich.

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Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer

Hybrid seminar of the Institute for Informatics as part of the Computer Vision Group Open Seminars series. Greg Yang from Microsoft Research gives a two-part talk: The first half will target general practitioners or empirical researchers in machine learning, while the second half targets those who are more theoretically curious.

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Cortical oscillations in neural networks

Dealing with uncertainty is a big challenge for our brain. Led by the University of Bern, researchers from Heidelberg University, the Jülich Research Centre and Graz University of Technology have identified a new computation role for cortical oscillations that support sampling-based computations in spiking neural networks.

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Inti Zlobec elected Digital Pathology Professor

The University of Bern has elected Inti Zlobec as Professor of Digital Pathology as of April 2022. The position is one of several new professorships in the field of artificial intelligence and digitalization in medicine that have been created as part of a new research focus in this area.

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3rd Swiss Emergency Telemedicine Congress

Virtual Congress on eEmergency Medicine and Digital Health featuring presentations on mixed-reality team training for medical first responders, social humanoid robots, Ethics and AI, the digital hospital of the future, VR in acute care, and a Canadian perspective on digital emergency medicine.

Program...

Bernese Covid-19 project featured on Swedish television

Alexander Norén, technical correspondent at the Swedish television has visited Bern to realize a report on a joint project of the Inselspital, Bern University Hospital and the University of Bern for AI-assisted prediction of the severity of a Covid-19 infection progression. The research evaluates extensive clinical, image-morphological and laboratory data with machine learning.

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AI enables personalized treatment of myocarditis

A research team from the University of Bern and Inselspital, University Hospital Bern is investigating and developing innovative approaches that will enable personalized diagnosis and treatment of myocarditis. Artificial intelligence will allow individual risk assessment and progression prognosis in the future. The project has received funding from the CAIM Research Project Fund for 2022/23.

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Training emergency teams in virtual reality

In emergency medicine, all members of the treatment team are crucial to the health and survival of patients. Training routines ensure that the decisive moves are made correctly – and virtual reality is a great tool for this. Tanja Birrenbach explains in an interview how she plans and researches VR trainings for emergency teams and which developments in this area will be topic of the Emergency Telemedicine Congress she co-hosts on 30 March.

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AI helps to dose Parkinson's medication

For people suffering from Parkinson's disease, the correct adjustment of medication is crucial. Too little doesn't help, too much is counterproductive. But how much is right? Together with the Gerontechnology and Rehabilitation group at the ARTORG Center the iHomeLab of the Lucerne University of Applied Sciences and Arts have developed a sensor system and a modified smartwatch that help to find the right dosage.

Read the media release of the HS Lucerne (in German)...

AI is a valuable tool for the medical community

Report by the Schweizerische Ärztezeitung on the one-year anniversary of CAIM. Julia Rippstein describes how CAIM targets challenges arising from the introduction of digital technologies into the medical sector. In this effort, CAIM aims to bring together physicians and engineers to put new technologies at the service of patients.

Read the report (French or German)...