AIMC Topic: Deep Learning

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Outcomes of Adversarial Attacks on Deep Learning Models for Ophthalmology Imaging Domains.

JAMA ophthalmology
This study investigates whether adversarial attacks can confuse deep learning systems based on imaging domains.

Applications of neural networks in urology: a systematic review.

Current opinion in urology
PURPOSE OF REVIEW: Over the last decade, major advancements in artificial intelligence technology have emerged and revolutionized the extent to which physicians are able to personalize treatment modalities and care for their patients. Artificial inte...

Pathomics in urology.

Current opinion in urology
PURPOSE OF REVIEW: Pathomics, the fusion of digitalized pathology and artificial intelligence, is currently changing the landscape of medical pathology and biologic disease classification. In this review, we give an overview of Pathomics and summariz...

On Artificial Intelligence and Deep Learning Within Medical Education.

Academic medicine : journal of the Association of American Medical Colleges
The methodology of deep learning, a component of machine learning and artificial intelligence, is introduced. The opportunity for this technology to automate some aspects of medical practice is reviewed. Finally, a discussion is provided on the integ...

BeadNet: deep learning-based bead detection and counting in low-resolution microscopy images.

Bioinformatics (Oxford, England)
MOTIVATION: An automated counting of beads is required for many high-throughput experiments such as studying mimicked bacterial invasion processes. However, state-of-the-art algorithms under- or overestimate the number of beads in low-resolution imag...

Is Deep Learning On Par with Human Observers for Detection of Radiographically Visible and Occult Fractures of the Scaphoid?

Clinical orthopaedics and related research
BACKGROUND: Preliminary experience suggests that deep learning algorithms are nearly as good as humans in detecting common, displaced, and relatively obvious fractures (such as, distal radius or hip fractures). However, it is not known whether this a...

SAINT: self-attention augmented inception-inside-inception network improves protein secondary structure prediction.

Bioinformatics (Oxford, England)
MOTIVATION: Protein structures provide basic insight into how they can interact with other proteins, their functions and biological roles in an organism. Experimental methods (e.g. X-ray crystallography and nuclear magnetic resonance spectroscopy) fo...

Forty-two Million Ways to Describe Pain: Topic Modeling of 200,000 PubMed Pain-Related Abstracts Using Natural Language Processing and Deep Learning-Based Text Generation.

Pain medicine (Malden, Mass.)
OBJECTIVE: Recent efforts to update the definitions and taxonomic structure of concepts related to pain have revealed opportunities to better quantify topics of existing pain research subject areas.