AIMC Topic: Humans

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Application of artificial intelligence using a convolutional neural network for detecting cholesteatoma in endoscopic enhanced images.

Auris, nasus, larynx
OBJECTIVE: We examined whether artificial intelligence (AI) used with the novel digital image enhancement system modalities (CLARA+CHROMA, SPECTRA A, and SPECTRA B) could distinguish the cholesteatoma matrix, cholesteatoma debris, and normal middle e...

Longitudinal self-supervised learning.

Medical image analysis
Machine learning analysis of longitudinal neuroimaging data is typically based on supervised learning, which requires large number of ground-truth labels to be informative. As ground-truth labels are often missing or expensive to obtain in neuroscien...

Diagnostic Accuracy and Failure Mode Analysis of a Deep Learning Algorithm for the Detection of Intracranial Hemorrhage.

Journal of the American College of Radiology : JACR
OBJECTIVE: To determine the institutional diagnostic accuracy of an artificial intelligence (AI) decision support systems (DSS), Aidoc, in diagnosing intracranial hemorrhage (ICH) on noncontrast head CTs and to assess the potential generalizability o...

Applying deep learning in digital breast tomosynthesis for automatic breast cancer detection: A review.

Medical image analysis
The relatively recent reintroduction of deep learning has been a revolutionary force in the interpretation of diagnostic imaging studies. However, the technology used to acquire those images is undergoing a revolution itself at the very same time. Di...

The effect of facial features on facial anthropomorphic trustworthiness in social robots.

Applied ergonomics
As the nature of human-robot relationships have become increasingly bound to shift from supervisor-machine to friend-companion, people have exhibited an increasing interest in making social judgments toward such anthropomorphic objects, such as trust...

Review of computer vision application in in vitro fertilization: the application of deep learning-based computer vision technology in the world of IVF.

Journal of assisted reproduction and genetics
In vitro fertilization has been regarded as a forefront solution in treating infertility for over four decades, yet its effectiveness has remained relatively low. This could be attributed to the lack of advancements for the method of observing and se...

Adopting low-shot deep learning for the detection of conjunctival melanoma using ocular surface images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The purpose of the present study was to investigate low-shot deep learning models applied to conjunctival melanoma detection using a small dataset with ocular surface images.