Critical Care

Minimally invasive, robot-assisted procedure for kidney transplantation among morbidly obese: Positive outcomes at 5 years post-transplant.

The pre-transplant weight loss required of end-stage renal disease patients is often unachievable. Though robot-assisted procedures among extremely obese have shown minimal complication, long-term outcomes are understudied. Previously, we reported no difference in 6-month patient and graft survival among 28 robot-assisted transplant cases (2009-2013) and 28 open controls (2004-2010). Groups were f...

Multi-Channel Convolutional Neural Networks Architecture Feeding for Effective EEG Mental Tasks Classification.

Mental tasks classification is increasingly recognized as a major challenge in the field of EEG signal processing and analysis. State-of-the-art approaches face the issue of spatially unstable structure of highly noised EEG signals. To address this problem, this paper presents a multi-channel convolutional neural network architecture with adaptively optimized parameters. Our solution outperforms a...

Analysis of platelet-activating factors in severe sepsis by flow cytometry and its correlation with clinical sepsis scoring system: A pilot study.

BACKGROUND: Sepsis is a major global healthcare concern. Platelets and leucocytes play a key role in sepsis. Whole blood flow cytometry (FCM) is a pow...

Progress in the Development and Challenges for the Use of Artificial Kidneys and Wearable Dialysis Devices.

BACKGROUND: Renal transplantation is the treatment of choice for chronic kidney disease (CKD) patients, but the shortage of kidneys and the disabling ...

Using machine learning to guide targeted and locally-tailored empiric antibiotic prescribing in a children's hospital in Cambodia.

: Early and appropriate empiric antibiotic treatment of patients suspected of having sepsis is associated with reduced mortality. The increasing preva...

Artificial Intelligence and Dialysis.

Changes of Early Sepsis Biomarker Presepsin Level during Hemodialysis: Influence of β-Microglobulin Clearance of Dialysis Membrane: A Preliminary Study.

BACKGROUND: Although presepsin (P-SEP) is an early sepsis biomarker, sepsis is often suspected after starting hemodialysis (HD). To enhance the utilit...

Machine learning based framework to predict cardiac arrests in a paediatric intensive care unit : Prediction of cardiac arrests.

A cardiac arrest is a life-threatening event, often fatal. Whilst clinicians classify some of the cardiac arrests as potentially predictable, the majo...

Creation of a Robust and Generalizable Machine Learning Classifier for Patient Ventilator Asynchrony.

BACKGROUND: As healthcare increasingly digitizes, streaming waveform data is being made available from an variety of sources, but there still remains ...

A machine learning-based model for 1-year mortality prediction in patients admitted to an Intensive Care Unit with a diagnosis of sepsis.

INTRODUCTION: Sepsis is associated to a high mortality rate, and its severity must be evaluated quickly. The severity of illness scores used are inten...

Deep learning for classifying fibrotic lung disease on high-resolution computed tomography: a case-cohort study.

BACKGROUND: Based on international diagnostic guidelines, high-resolution CT plays a central part in the diagnosis of fibrotic lung disease. In the co...

Joint Classification and Regression via Deep Multi-Task Multi-Channel Learning for Alzheimer's Disease Diagnosis.

In the field of computer-aided Alzheimer's disease (AD) diagnosis, jointly identifying brain diseases and predicting clinical scores using magnetic re...

Convolutional Neural Networks with Template-Based Data Augmentation for Functional Lung Image Quantification.

RATIONALE AND OBJECTIVES: We propose an automated segmentation pipeline based on deep learning for proton lung MRI segmentation and ventilation-based ...

An End-to-End Deep Learning Histochemical Scoring System for Breast Cancer TMA.

One of the methods for stratifying different molecular classes of breast cancer is the Nottingham prognostic index plus, which uses breast cancer rele...

Societal Issues Concerning the Application of Artificial Intelligence in Medicine.

BACKGROUND: Medicine is becoming an increasingly data-centred discipline and, beyond classical statistical approaches, artificial intelligence (AI) an...

Identification of a Novel Clinical Phenotype of Severe Malaria using a Network-Based Clustering Approach.

The parasite Plasmodium falciparum is the main cause of severe malaria (SM). Despite treatment with antimalarial drugs, more than 400,000 deaths are r...

Big data and machine learning in critical care: Opportunities for collaborative research.

The introduction of clinical information systems (CIS) in Intensive Care Units (ICUs) offers the possibility of storing a huge amount of machine-ready...

Prognostication and Risk Factors for Cystic Fibrosis via Automated Machine Learning.

Accurate prediction of survival for cystic fibrosis (CF) patients is instrumental in establishing the optimal timing for referring patients with termi...

Improved multi-view privileged support vector machine.

Multi-view learning (MVL) concentrates on the problem of learning from the data represented by multiple distinct feature sets. The consensus and compl...

Ensemble Learning Approach via Kalman Filtering for a Passive Wearable Respiratory Monitor.

OBJECTIVE: Utilizing passive radio frequency identification (RFID) tags embedded in knitted smart-garment devices, we wirelessly detect the respirator...