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Microaneurysm detection using fully convolutional neural networks.

Computer methods and programs in biomedicine
BACKROUND AND OBJECTIVES: Diabetic retinopathy is a microvascular complication of diabetes that can lead to sight loss if treated not early enough. Microaneurysms are the earliest clinical signs of diabetic retinopathy. This paper presents an automat...

Automated Interpretation of Blood Culture Gram Stains by Use of a Deep Convolutional Neural Network.

Journal of clinical microbiology
Microscopic interpretation of stained smears is one of the most operator-dependent and time-intensive activities in the clinical microbiology laboratory. Here, we investigated application of an automated image acquisition and convolutional neural net...

The Role of Artificial Intelligence in Diagnostic Radiology: A Survey at a Single Radiology Residency Training Program.

Journal of the American College of Radiology : JACR
PURPOSE: Advances in artificial intelligence applied to diagnostic radiology are predicted to have a major impact on this medical specialty. With the goal of establishing a baseline upon which to build educational activities on this topic, a survey w...

Friendship with a robot: Children's perception of similarity between a robot's physical and virtual embodiment that supports diabetes self-management.

Patient education and counseling
OBJECTIVE: The PAL project develops a conversational agent with a physical (robot) and virtual (avatar) embodiment to support diabetes self-management of children ubiquitously. This paper assesses 1) the effect of perceived similarity between robot a...

Multiscale deep neural network based analysis of FDG-PET images for the early diagnosis of Alzheimer's disease.

Medical image analysis
Alzheimer's disease (AD) is one of the most common neurodegenerative diseases with a commonly seen prodromal mild cognitive impairment (MCI) phase where memory loss is the main complaint progressively worsening with behavior issues and poor self-care...

Fully-automated alignment of 3D fetal brain ultrasound to a canonical reference space using multi-task learning.

Medical image analysis
Methods for aligning 3D fetal neurosonography images must be robust to (i) intensity variations, (ii) anatomical and age-specific differences within the fetal population, and (iii) the variations in fetal position. To this end, we propose a multi-tas...

Ensemble of shape functions and support vector machines for the estimation of discrete arm muscle activation from external biceps 3D point clouds.

Computers in biology and medicine
BACKGROUND: Muscle activation level is currently being captured using impractical and expensive devices which make their use in telemedicine settings extremely difficult. To address this issue, a prototype is presented of a non-invasive, easy-to-inst...
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Representing and querying now-relative relational medical data.

Artificial intelligence in medicine
Temporal information plays a crucial role in medicine. Patients' clinical records are intrinsically temporal. Thus, in Medical Informatics there is an increasing need to store, support and query temporal data (particularly in relational databases), i...