AIMC Topic: Humans

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Discriminating glaucomatous and compressive optic neuropathy on spectral-domain optical coherence tomography with deep learning classifier.

The British journal of ophthalmology
BACKGROUND/AIMS: To assess the performance of a deep learning classifier for differentiation of glaucomatous optic neuropathy (GON) from compressive optic neuropathy (CON) based on ganglion cell-inner plexiform layer (GCIPL) and retinal nerve fibre l...

Imaging research in fibrotic lung disease; applying deep learning to unsolved problems.

The Lancet. Respiratory medicine
Over the past decade, there has been a groundswell of research interest in computer-based methods for objectively quantifying fibrotic lung disease on high resolution CT of the chest. In the past 5 years, the arrival of deep learning-based image anal...

Robot-assisted arm training for treating adult patients with distal radius fracture: a proof-of-concept pilot study.

European journal of physical and rehabilitation medicine
BACKGROUND: Fracture of the distal radius is a common wrist injury. As to its management after orthopedic (conservative or surgical) treatment, there is weak evidence for conventional rehabilitation interventions. Despite the increasing interest for ...

A health informatics transformation model based on intelligent cloud computing - exemplified by type 2 diabetes mellitus with related cardiovascular diseases.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Many studies regarding health analysis request structured datasets but the legacy resources provide scattered data. This study aims to establish a health informatics transformation model (HITM) based upon intelligent cloud c...

Image quality and dose reduction opportunity of deep learning image reconstruction algorithm for CT: a phantom study.

European radiology
OBJECTIVES: To assess the impact on image quality and dose reduction of a new deep learning image reconstruction (DLIR) algorithm compared with a hybrid iterative reconstruction (IR) algorithm.

End-to-end semantic segmentation of personalized deep brain structures for non-invasive brain stimulation.

Neural networks : the official journal of the International Neural Network Society
Electro-stimulation or modulation of deep brain regions is commonly used in clinical procedures for the treatment of several nervous system disorders. In particular, transcranial direct current stimulation (tDCS) is widely used as an affordable clini...

Supervised learning in spiking neural networks: A review of algorithms and evaluations.

Neural networks : the official journal of the International Neural Network Society
As a new brain-inspired computational model of the artificial neural network, a spiking neural network encodes and processes neural information through precisely timed spike trains. Spiking neural networks are composed of biologically plausible spiki...

Harnessing Population Pedigree Data and Machine Learning Methods to Identify Patterns of Familial Bladder Cancer Risk.

Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology
BACKGROUND: Relatives of patients with bladder cancer have been shown to be at increased risk for kidney, lung, thyroid, and cervical cancer after correcting for smoking-related behaviors that may concentrate in some families. We demonstrate a novel ...