Critical Care

Myoelectric digit action decoding with multi-output, multi-class classification: an offline analysis.

The ultimate goal of machine learning-based myoelectric control is simultaneous and independent cont...

Automatic multi-needle localization in ultrasound images using large margin mask RCNN for ultrasound-guided prostate brachytherapy.

Multi-needle localization in ultrasound (US) images is a crucial step of treatment planning for US-g...

Gut microbiome-mediated epigenetic regulation of brain disorder and application of machine learning for multi-omics data analysis.

The gut-brain axis (GBA) is a biochemical link that connects the central nervous system (CNS) and en...

Not All Sepsis-Associated Acute Kidney Injury Is the Same: There May Be an App for That.

Utilization of Deep Learning for Subphenotype Identification in Sepsis-Associated Acute Kidney Injury.

BACKGROUND AND OBJECTIVES: Sepsis-associated AKI is a heterogeneous clinical entity. We aimed to agn...

Clinical Predictive Models for COVID-19: Systematic Study.

BACKGROUND: COVID-19 is a rapidly emerging respiratory disease caused by SARS-CoV-2. Due to the rapi...

A Novel Strategy for the Development of Vaccines for SARS-CoV-2 (COVID-19) and Other Viruses Using AI and Viral Shell Disorder.

A model that predicts levels of coronavirus (CoV) respiratory and fecal-oral transmission potentials...

Using machine learning methods to predict in-hospital mortality of sepsis patients in the ICU.

BACKGROUND: Early and accurate identification of sepsis patients with high risk of in-hospital death...

Multi-Ontology Refined Embeddings (MORE): A hybrid multi-ontology and corpus-based semantic representation model for biomedical concepts.

OBJECTIVE: Currently, a major limitation for natural language processing (NLP) analyses in clinical ...

LncLocation: Efficient Subcellular Location Prediction of Long Non-Coding RNA-Based Multi-Source Heterogeneous Feature Fusion.

Recent studies uncover that subcellular location of long non-coding RNAs (lncRNAs) can provide signi...

Metabolic pathway inference using multi-label classification with rich pathway features.

Metabolic inference from genomic sequence information is a necessary step in determining the capacit...

Predicting acute kidney injury in critically ill patients using comorbid conditions utilizing machine learning.

BACKGROUND: Acute kidney injury (AKI) carries a poor prognosis. Its incidence is increasing in the i...

Machine learning-based data analytic approaches for evaluating post-natal mouse respiratory physiological evolution.

Respiratory parameters change during post-natal development, but the nature of their changes have no...

AI in the Intensive Care Unit: Up-to-Date Review.

AI is the latest technologic trend that likely will have a huge impact in medicine. AI's potential l...

Multi-view radiomics and dosiomics analysis with machine learning for predicting acute-phase weight loss in lung cancer patients treated with radiotherapy.

We propose a multi-view data analysis approach using radiomics and dosiomics (R&D) texture features ...

Acute kidney disease and long-term outcomes in critically ill acute kidney injury patients with sepsis: a cohort analysis.

BACKGROUND: Acute kidney injury (AKI) is frequent during hospitalization and may contribute to adver...

Federated Gradient Averaging for Multi-Site Training with Momentum-Based Optimizers.

Multi-site training methods for artificial neural networks are of particular interest to the medical...

Millimeter-Wave Array Radar-Based Human Gait Recognition Using Multi-Channel Three-Dimensional Convolutional Neural Network.

At present, there are two obvious problems in radar-based gait recognition. First, the traditional r...

A deep learning solution to recommend laboratory reduction strategies in ICU.

OBJECTIVE: To build a machine-learning model that predicts laboratory test results and provides a pr...

Multi-label zero-shot learning with graph convolutional networks.

The goal of zero-shot learning (ZSL) is to build a classifier that recognizes novel categories with ...

Development of a Robust Multi-Scale Featured Local Binary Pattern for Improved Facial Expression Recognition.

Compelling facial expression recognition (FER) processes have been utilized in very successful field...