Intensivists

Automatic Detection of Arrhythmia Based on Multi-Resolution Representation of ECG Signal.

Automatic detection of arrhythmia is of great significance for early prevention and diagnosis of car...

An integrated deep learning framework for joint segmentation of blood pool and myocardium.

Simultaneous and automatic segmentation of the blood pool and myocardium is an important preconditio...

CFD-based multi-objective controller optimization for soft robotic fish with muscle-like actuation.

Soft robots take advantage of rich nonlinear dynamics and large degrees of freedom to perform action...

A generalizable 29-mRNA neural-network classifier for acute bacterial and viral infections.

Improved identification of bacterial and viral infections would reduce morbidity from sepsis, reduce...

Deep Learning from Incomplete Data: Detecting Imminent Risk of Hospital-acquired Pneumonia in ICU Patients.

Hospital acquired pneumonia (HAP) is the second most common nosocomial infection in the ICU and cost...

Towards Reliable ARDS Clinical Decision Support: ARDS Patient Analytics with Free-text and Structured EMR Data.

In this work, we utilize a combination of free-text and structured data to build Acute Respiratory D...

Artificial intelligence in health care: accountability and safety.

The prospect of patient harm caused by the decisions made by an artificial intelligence-based clinic...

Using Domain Knowledge for Interpretable and Competitive Multi-Class Human Activity Recognition.

Human activity recognition (HAR) has become an increasingly popular application of machine learning ...

Pseudo-CT generation from multi-parametric MRI using a novel multi-channel multi-path conditional generative adversarial network for nasopharyngeal carcinoma patients.

PURPOSE: To develop and evaluate a novel method for pseudo-CT generation from multi-parametric MR im...

A comprehensive study on the multi-class cervical cancer diagnostic prediction on pap smear images using a fusion-based decision from ensemble deep convolutional neural network.

The diagnosis of cervical dysplasia, carcinoma in situ and confirmed carcinoma cases is more easily ...

Early detection of sepsis utilizing deep learning on electronic health record event sequences.

BACKGROUND: The timeliness of detection of a sepsis incidence in progress is a crucial factor in the...

Multi-Contrast Super-Resolution MRI Through a Progressive Network.

Magnetic resonance imaging (MRI) is widely used for screening, diagnosis, image-guided therapy, and ...

Intravenous Lignocaine-Fentanyl Versus Epidural Ropivacaine-Fentanyl for Postoperative Analgesia After Major Abdominal Oncosurgery: A Pilot Prospective Randomised Study.

OBJECTIVE: Epidural injection of local anaesthetics and intravenous opioid injection are two common ...

MS-Net: Multi-Site Network for Improving Prostate Segmentation With Heterogeneous MRI Data.

Automated prostate segmentation in MRI is highly demanded for computer-assisted diagnosis. Recently,...

Grasping Force Control of Multi-Fingered Robotic Hands through Tactile Sensing for Object Stabilization.

Grasping force control is important for multi-fingered robotic hands to stabilize the grasped object...

Combined Use of Three Machine Learning Modeling Methods to Develop a Ten-Gene Signature for the Diagnosis of Ventilator-Associated Pneumonia.

BACKGROUND This study aimed to use three modeling methods, logistic regression analysis, random fore...

An Artificial Neural Network-based Predictive Model to Support Optimization of Inpatient Glycemic Control.

Achieving glycemic control in critical care patients is of paramount importance, and has been linke...

A Translational Pipeline for Overall Survival Prediction of Breast Cancer Patients by Decision-Level Integration of Multi-Omics Data.

Breast cancer is the most prevalent and among the most deadly cancers in females. Patients with brea...

Clinical management of sepsis can be improved by artificial intelligence: no.

Mixed-integer optimization approach to learning association rules for unplanned ICU transfer.

After admission to emergency department (ED), patients with critical illnesses are transferred to in...

Overlooked pitfalls in multi-class machine learning classification in radiation oncology and how to avoid them.

In radiation oncology, Machine Learning classification publications are typically related to two out...