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ISR Radiology (@ISR_Radiology)

#artificialintelligence

Set your alarms Today at 17:00, Prof. Josef Penninger will be giving his exclusive lecture on ACE2 and its potential as a rational frontline therapy for #COVID-19. The lecture will be streamed live and free of charge on ESR Connect.


RSNA2019

#artificialintelligence

We understand patient care comes first and our solutions will look at the full picture including prior images*, DBT detection and short-term individual risk* creating a patient journey that is personalized. The results are truly ProFound. We will be showcasing the Breast Health Solutions suite, which delivers powerful software solutions for breast tomosynthesis, breast density and 2D mammography. Please visit us in our main booth in the South Hall, booth #3929 or in the AI Showcase located in the North Hall, booth #10716, to experience our innovative technology live on the show floor.


Study: Dogs Have Some Understanding of Language

U.S. News

Researchers then conducted functional Magnetic Resonance Imaging scans on the dogs while their owners stood in front of the machine calling out the name of each object while showing the corresponding toy. The owners also called out meaningless words while displaying random objects. The fMRI results showed increased activation in auditory regions of the dogs' brains to the unassigned words compared to the trained words.


[Policy Forum] How economics can shape precision medicines

Science

Many public and private efforts in coming years will focus on research in precision medicine, developing biomarkers to indicate which patients are likely to benefit from a certain treatment so that others can be spared the cost--financial and physical--of being treated with unproductive therapies and therapeutic signals can be more easily uncovered. However, such research initiatives alone will not deliver new medicines to patients in the absence of strong incentives to bring new products to market. We examine the unique economics of precision medicines and associated biomarkers, with an emphasis on the factors affecting their development, pricing, and access.


Machine Learning and Evidence-Based Medicine Annals of Internal Medicine

#artificialintelligence

Inferences were made using traditional biostatistics. In the early 1990s, ML emerged, whereby advanced computing programs (machines) processed huge data sets (big data) from many sources and discerned patterns among multiple unselected variables. Such patterns were undiscoverable using traditional biostatistics (1) and were used to iteratively refine (learn) layered mathematical models (algorithms). The Table lists key differences between EBM and ML.