AIMC Topic: Humans

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Artificial Intelligence-Based Conversational Agents for Chronic Conditions: Systematic Literature Review.

Journal of medical Internet research
BACKGROUND: A rising number of conversational agents or chatbots are equipped with artificial intelligence (AI) architecture. They are increasingly prevalent in health care applications such as those providing education and support to patients with c...

Review of medical image recognition technologies to detect melanomas using neural networks.

BMC bioinformatics
BACKGROUND: Melanoma is one of the most aggressive types of cancer that has become a world-class problem. According to the World Health Organization estimates, 132,000 cases of the disease and 66,000 deaths from malignant melanoma and other forms of ...

A machine learning framework with anatomical prior for online dose verification using positron emitters and PET in proton therapy.

Physics in medicine and biology
We developed a machine learning framework in order to establish the correlation between dose and activity distributions in proton therapy. A recurrent neural network was used to predict dose distribution in three dimensions based on the information o...

NuSeT: A deep learning tool for reliably separating and analyzing crowded cells.

PLoS computational biology
Segmenting cell nuclei within microscopy images is a ubiquitous task in biological research and clinical applications. Unfortunately, segmenting low-contrast overlapping objects that may be tightly packed is a major bottleneck in standard deep learni...

Prediction of 3-month treatment outcome of IgG4-DS based on BP artificial neural network.

Oral diseases
OBJECTIVE: The study aimed to establish an effective back-Propagation artificial neural network (BP-ANN) model for automatic prediction of 3-month treatment outcome of IgG4-DS.

Multi-domain convolutional neural network (MD-CNN) for radial reconstruction of dynamic cardiac MRI.

Magnetic resonance in medicine
PURPOSE: Cardiac MR cine imaging allows accurate and reproducible assessment of cardiac function. However, its long scan time not only limits the spatial and temporal resolutions but is challenging in patients with breath-holding difficulty or non-si...

New Machine Learning Approach for Detection of Injury Risk Factors in Young Team Sport Athletes.

International journal of sports medicine
The purpose of this article is to present how predictive machine learning methods can be utilized for detecting sport injury risk factors in a data-driven manner. The approach can be used for finding new hypotheses for risk factors and confirming the...

The Brain Chart of Aging: Machine-learning analytics reveals links between brain aging, white matter disease, amyloid burden, and cognition in the iSTAGING consortium of 10,216 harmonized MR scans.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Relationships between brain atrophy patterns of typical aging and Alzheimer's disease (AD), white matter disease, cognition, and AD neuropathology were investigated via machine learning in a large harmonized magnetic resonance imaging d...

Optical Mapping-Validated Machine Learning Improves Atrial Fibrillation Driver Detection by Multi-Electrode Mapping.

Circulation. Arrhythmia and electrophysiology
BACKGROUND: Atrial fibrillation (AF) can be maintained by localized intramural reentrant drivers. However, AF driver detection by clinical surface-only multielectrode mapping (MEM) has relied on subjective interpretation of activation maps. We hypoth...