AIMC Topic: Artificial Intelligence

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Development and validation pathways of artificial intelligence tools evaluated in randomised clinical trials.

BMJ health & care informatics
OBJECTIVE: Given the complexities of testing the translational capability of new artificial intelligence (AI) tools, we aimed to map the pathways of training/validation/testing in development process and external validation of AI tools evaluated in d...

[Not Available].

Bulletin du cancer
HER2 is an important prognostic and predictive biomarker in breast cancer. Its detection makes it possible to define which patients will benefit from a targeted treatment. While assessment of HER2 status by immunohistochemistry in positive vs negativ...

Contribution of artificial intelligence applications developed with the deep learning method to the diagnosis of COVID-19 pneumonia on computed tomography.

Tuberkuloz ve toraks
INTRODUCTION: Computed tomography (CT) is an auxiliary modality in the diagnosis of the novel Coronavirus (COVID-19) disease and can guide physicians in the presence of lung involvement. In this study, we aimed to investigate the contribution of deep...

Emerging technologies and their potential for generating new assistive technologies.

Assistive technology : the official journal of RESNA
Limited access to assistive technology (AT) is a well-recognized global challenge. Emerging technologies have potential to develop new assistive products and bridge some of the gaps in access to AT. However, limited analyses exist on the potential of...

AI and the cardiologist: when mind, heart and machine unite.

Open heart
Artificial intelligence (AI) and deep learning has made much headway in the consumer and advertising sector, not only affecting how and what people purchase these days, but also affecting behaviour and cultural attitudes. It is poised to influence ne...

[Artificial intelligence and big data in healthcare: Cineca's experience.].

Recenti progressi in medicina
Big data and artificial intelligence are extremely useful tools for improving care pathways and for designing and evaluating preventive medicine and health promotion strategies. The paper describes Cineca's projects that use artificial intelligence t...

Applications of Artificial Intelligence in Pediatric Oncology: A Systematic Review.

JCO clinical cancer informatics
PURPOSE: There is a need for an improved understanding of clinical and biologic risk factors in pediatric cancer to improve patient outcomes. Machine learning (ML) represents the application of computational inference from advanced statistical method...