AIMC Topic: Humans

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Prediction of age and brachial-ankle pulse-wave velocity using ultra-wide-field pseudo-color images by deep learning.

Scientific reports
This study examined whether age and brachial-ankle pulse-wave velocity (baPWV) can be predicted with ultra-wide-field pseudo-color (UWPC) images using deep learning (DL). We examined 170 UWPC images of both eyes of 85 participants (40 men and 45 wome...

Cross-site transportability of an explainable artificial intelligence model for acute kidney injury prediction.

Nature communications
Artificial intelligence (AI) has demonstrated promise in predicting acute kidney injury (AKI), however, clinical adoption of these models requires interpretability and transportability. Non-interoperable data across hospitals is a major barrier to mo...

SVFX: a machine learning framework to quantify the pathogenicity of structural variants.

Genome biology
There is a lack of approaches for identifying pathogenic genomic structural variants (SVs) although they play a crucial role in many diseases. We present a mechanism-agnostic machine learning-based workflow, called SVFX, to assign pathogenicity score...

Pathway information extracted from 25 years of pathway figures.

Genome biology
Thousands of pathway diagrams are published each year as static figures inaccessible to computational queries and analyses. Using a combination of machine learning, optical character recognition, and manual curation, we identified 64,643 pathway figu...

Suicide Risk Assessment Using Machine Learning and Social Networks: a Scoping Review.

Journal of medical systems
According to the World Health Organization (WHO) report in 2016, around 800,000 of individuals have committed suicide. Moreover, suicide is the second cause of unnatural death in people between 15 and 29 years. This paper reviews state of the art on ...

An Easy-to-Use Machine Learning Model to Predict the Prognosis of Patients With COVID-19: Retrospective Cohort Study.

Journal of medical Internet research
BACKGROUND: Prioritizing patients in need of intensive care is necessary to reduce the mortality rate during the COVID-19 pandemic. Although several scoring methods have been introduced, many require laboratory or radiographic findings that are not a...

Cancer classification based on chromatin accessibility profiles with deep adversarial learning model.

PLoS computational biology
Given the complexity and diversity of the cancer genomics profiles, it is challenging to identify distinct clusters from different cancer types. Numerous analyses have been conducted for this propose. Still, the methods they used always do not direct...

Circulating Neutrophil Extracellular Traps Signature for Identifying Organ Involvement and Response to Glucocorticoid in Adult-Onset Still's Disease: A Machine Learning Study.

Frontiers in immunology
Adult-onset Still's disease (AOSD) is an autoinflammatory disease with multisystem involvement. Early identification of patients with severe complications and those refractory to glucocorticoid is crucial to improve therapeutic strategy in AOSD. Exag...

CheXLocNet: Automatic localization of pneumothorax in chest radiographs using deep convolutional neural networks.

PloS one
BACKGROUND: Pneumothorax can lead to a life-threatening emergency. The experienced radiologists can offer precise diagnosis according to the chest radiographs. The localization of the pneumothorax lesions will help to quickly diagnose, which will be ...

List-wise learning to rank biomedical question-answer pairs with deep ranking recursive autoencoders.

PloS one
Biomedical question answering (QA) represents a growing concern among industry and academia due to the crucial impact of biomedical information. When mapping and ranking candidate snippet answers within relevant literature, current QA systems typical...