Current Background Reports -- MEDICA - World Forum for Medicine

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AI in the hospital – Possibilities and limits

17.01.2020

A hospital generates several thousands of gigabytes of data each day. The growing flood of data is no longer manageable for doctors. The great hope: artificial intelligence. Radiology is the main beneficiary. Dr. Felix Nensa from Essen University Hospital and Dr. Peter Langkafel from the Digital Health Factory tell us more about the possibilities and limits of learning machines.
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Image: Female physician shows a man an image of the prostate; Copyright: panthermedia.net/imagepointfr

Prostate cancer can now be diagnosed better using AI

16.01.2020

Researchers at Radboud university medical center have developed a 'deep learning' system that is better than most pathologists at determining the aggressiveness of prostate cancer. The AI system, which uses tissue samples to arrive at its diagnosis, taught itself to identify prostate cancer based on data from over 1200 patients.
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Image: new 3D technology capturing structural and energetic features of the interface of a protein docking model; Copyright: Daisuke Kihara/Purdue University

Deep learning and 3D technology to create better drugs

10.01.2020

Proteins are often called the working molecules of the human body. A typical body has more than 20,000 different types of proteins, each of which are involved in many functions essential to human life.
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Image: binary code on black ground; COLOURBOX.de

Artificial Intelligence tracks down leukemia

09.01.2020

Artificial intelligence can detect one of the most common forms of blood cancer – acute myeloid leukemia (AML) – with high reliability. Researchers at the German Center for Neurodegenerative Diseases (DZNE) and the University of Bonn have now shown this in a proof-of-concept study. Their approach is based on the analysis of the gene activity of cells found in the blood.
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Image: Robot points with his finger at CT images of the brain, in the background a CT device; Copyright: panthermedia.net/phonlamai

Smart algorithm finds possible treatment for childhood cancer

09.01.2020

Using a computer algorithm, scientists at Uppsala University have identified a promising new treatment for neuroblastoma. This form of cancer in children, which occurs in specialised nerve cells in the sympathetic nervous system, may be life-threatening.
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Image: three lemons: Drug Protein Lemon System; Copyright: Purdue University/Gaurav Chopra

AI: this lemon could help create better drugs

06.01.2020

One of the challenges in using machine learning for drug development is to create a process for the computer to extract needed information from a pool of data points. Drug scientists must pull biological data and train the software to understand how a typical human body will interact with the combinations that come together to form a medication.
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Image: AI computer; Copyright: RIKEN

AI identifies features associated with cancer recurrence

19.12.2019

Artificial intelligence (AI) technology developed by the RIKEN Center for Advanced Intelligence Project (AIP) in Japan has successfully found features in pathology images from human cancer patients, without annotation, that could be understood by human doctors. Further, the AI identified features relevant to cancer prognosis that were not previously noted by pathologists.
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Image: depiction of dementia as gears coming loose in a head; Copyright: panthermedia.net/lightwise

AI: combined with astrophysics as key to early dementia diagnosis

18.12.2019

Crucial early diagnosis of dementia in general practice could improve thanks to a computer model designed in a collaboration between Brighton and Sussex Medical School (BSMS) and astrophysicists at the University of Sussex.
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Image: elderly couple; Copyright: panthermedia.net/mykeyruna

AI: neural network for elderly care could save millions

16.12.2019

If healthcare providers could accurately predict how their services would be used, they could save large sums of money by not having to allocate funds unnecessarily. Deep learning artificial intelligence models can be good at predicting the future given previous behaviour, and researchers based in Finland have developed one that predicts when and why elderly people will use healthcare services.
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Image: woman holds her hands on breast; Copyright: panthermedia.net/Andriy Popov

Diagnostic tool: AI for breast cancer

13.12.2019

Scientists are developing a new way to identify the unique chemical 'fingerprints' for different types of breast cancers. These new chemical footprints will be used to train AI software - creating a new tool for rapid and accurate diagnosis of breast cancers.
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Image: scanning electron microscope image of NETs; Copyright: Urban, et al., Max Planck Institute

Machine learning: to measure inflammation process

13.12.2019

UNC School of Medicine researchers created an artificial intelligence tool to measure NETosis, an inflammatory process where white blood cells trap invaders; this work will help scientists find ways to stop or promote NETosis in disease states
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Image: laboratory technology; Copyright: panthermedia.net/Robert Przybysz

Analyser system: Epigenomic technology combats disease

11.12.2019

Much remains unknown about diseases and the way our bodies respond to them, in part because the human genome is the complete DNA assembly that makes each person unique. A Virginia Tech professor and his team of researchers have created new technology to help in understanding how the human body battles diseases.
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 Image: illustration of the ConvPath software workflow; Copyright: UTSW

Software tool: AI helps doctors identify cancer cells

11.12.2019

UT Southwestern researchers have developed a software tool that uses artificial intelligence to recognize cancer cells from digital pathology images - giving clinicians a powerful way of predicting patient outcomes.
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Image: PR-OCT imaging; Copyright: Zhu Lab

Machine learning: imaging boosts colon cancer diagnosis

09.12.2019

Colorectal cancer is the second most common type of cancer worldwide, with about 90% of cases occurring in people 50 or older. Arising from the inner surface, or muscosal layer, of the colon, cancerous cells can penetrate through the deeper layers of the colon and spread to other organs. Left untreated, the disease is fatal.
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Image: A drawing block with a pen on it; Copyright: RMIT University

Screening tech advances early detection of Parkinson's disease

05.12.2019

Screening technology to catch Parkinson's disease in its earliest stages could be available within three years, following an agreement between RMIT University and start-up company Jesse Medical.
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Image: A young man is lying on the floor, using his phone; Copyright: panthermedia.net/Nikoleta Vukovic

Machine learning predicts success of digital health interventions

04.12.2019

Health apps could be better tailored to the individual needs of patients. A new statistical technique from the field of machine learning is now making it possible to predict the success of smartphone-based interventions more accurately.
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Image: Monitor at an intensive care unit; Copyright: panthermedia.net/beerkoff1

Big Data makes intensive care better

02.12.2019

Patient safety in intensive care units could be significantly improved if false alarms could be greatly reduced and critical complications such as epileptic seizures could be predicted.
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Image: An artist's illustration of modern neurosurgical intensive care and the use of machine learning algorithms; Copyright: Rahul Raj, University of Helsinki

AI: algorithm for intensive care of traumatic brain injury

28.11.2019

Traumatic brain injury (TBI) is a significant global cause of mortality and morbidity with an increasing incidence, especially in low-and-middle income countries. The most severe TBIs are treated in intensive care units (ICU), but in spite of the proper and high-quality care, about one in three patients dies.
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Image: Diascopic's iON platform next to a laptop; Diascopic, LLC

AI: startup developing tool for tuberculosis detection

27.11.2019

Diascopic LLC, a Cleveland-based medical research company that develops diagnostic technology, will use a highly competitive federal grant to develop and apply new artificial intelligence (AI) and digital pathology tools for detecting tuberculosis (TB).
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