AIMC Topic: Artificial Intelligence

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Social Cognition in the Age of Human-Robot Interaction.

Trends in neurosciences
Artificial intelligence advances have led to robots endowed with increasingly sophisticated social abilities. These machines speak to our innate desire to perceive social cues in the environment, as well as the promise of robots enhancing our daily l...

Artificial intelligence in glioma imaging: challenges and advances.

Journal of neural engineering
Primary brain tumors including gliomas continue to pose significant management challenges to clinicians. While the presentation, the pathology, and the clinical course of these lesions are variable, the initial investigations are usually similar. Pat...

Artificial intelligence: radiologists' expectations and opinions gleaned from a nationwide online survey.

La Radiologia medica
PURPOSE: To report the results of a nationwide online survey on artificial intelligence (AI) among radiologist members of the Italian Society of Medical and Interventional Radiology (SIRM).

Use of CT and artificial intelligence in suspected or COVID-19 positive patients: statement of the Italian Society of Medical and Interventional Radiology.

La Radiologia medica
The COVID-19 pandemic started in Italy in February 2020 with an exponential growth that has exceeded the number of cases reported in China. Italian radiology departments found themselves at the forefront in the management of suspected and positive CO...

Machine Learning and Psychological Research: The Unexplored Effect of Measurement.

Perspectives on psychological science : a journal of the Association for Psychological Science
Machine learning (i.e., data mining, artificial intelligence, big data) has been increasingly applied in psychological science. Although some areas of research have benefited tremendously from a new set of statistical tools, most often in the use of ...

Artificial Intelligence-Based Differential Diagnosis: Development and Validation of a Probabilistic Model to Address Lack of Large-Scale Clinical Datasets.

Journal of medical Internet research
BACKGROUND: Machine-learning or deep-learning algorithms for clinical diagnosis are inherently dependent on the availability of large-scale clinical datasets. Lack of such datasets and inherent problems such as overfitting often necessitate the devel...

Effects of Study Population, Labeling and Training on Glaucoma Detection Using Deep Learning Algorithms.

Translational vision science & technology
PURPOSE: To compare performance of independently developed deep learning algorithms for detecting glaucoma from fundus photographs and to evaluate strategies for incorporating new data into models.