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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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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
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.
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.
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.
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.
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.
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.
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.
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).