AIMC Topic: Humans

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Violence detection explanation via semantic roles embeddings.

BMC medical informatics and decision making
BACKGROUND: Emergency room reports pose specific challenges to natural language processing techniques. In this setting, violence episodes on women, elderly and children are often under-reported. Categorizing textual descriptions as containing violenc...

Dyspnea, effort and muscle pain during exercise in lung transplant recipients: an analysis of their association with cardiopulmonary function parameters using machine learning.

Respiratory research
BACKGROUND: Despite improvement in lung function, most lung transplant (LTx) recipients show an unexpectedly reduced exercise capacity that could be explained by persisting peripheral muscle dysfunction of multifactorial origin. We analyzed the cours...

An evaluation of DistillerSR's machine learning-based prioritization tool for title/abstract screening - impact on reviewer-relevant outcomes.

BMC medical research methodology
BACKGROUND: Systematic reviews often require substantial resources, partially due to the large number of records identified during searching. Although artificial intelligence may not be ready to fully replace human reviewers, it may accelerate and re...

Extracting medication information from unstructured public health data: a demonstration on data from population-based and tertiary-based samples.

BMC medical research methodology
BACKGROUND: Unstructured data from clinical epidemiological studies can be valuable and easy to obtain. However, it requires further extraction and processing for data analysis. Doing this manually is labor-intensive, slow and subject to error. In th...

A Correlation-Driven Mapping For Deep Learning application in detecting artifacts within the EEG.

Journal of neural engineering
OBJECTIVE: When developing approaches for automatic preprocessing of electroencephalogram (EEG) signals in non-isolated demanding environment such as intensive care unit (ICU) or even outdoor environment, one of the major concerns is varying nature o...

Artificial Intelligence Algorithms to Diagnose Glaucoma and Detect Glaucoma Progression: Translation to Clinical Practice.

Translational vision science & technology
PURPOSE: This concise review aims to explore the potential for the clinical implementation of artificial intelligence (AI) strategies for detecting glaucoma and monitoring glaucoma progression.

Optimal forgetting: Semantic compression of episodic memories.

PLoS computational biology
It has extensively been documented that human memory exhibits a wide range of systematic distortions, which have been associated with resource constraints. Resource constraints on memory can be formalised in the normative framework of lossy compressi...

Finding, visualizing, and quantifying latent structure across diverse animal vocal repertoires.

PLoS computational biology
Animals produce vocalizations that range in complexity from a single repeated call to hundreds of unique vocal elements patterned in sequences unfolding over hours. Characterizing complex vocalizations can require considerable effort and a deep intui...

Reward-predictive representations generalize across tasks in reinforcement learning.

PLoS computational biology
In computer science, reinforcement learning is a powerful framework with which artificial agents can learn to maximize their performance for any given Markov decision process (MDP). Advances over the last decade, in combination with deep neural netwo...

Online Doctor Recommendation with Convolutional Neural Network and Sparse Inputs.

Computational intelligence and neuroscience
The recommendation system in the online medical consultation website is a system to assist patients to find appropriate doctors. Based on the analysis of the current situation of the development of an online medical community (Haodf.com) in China, th...