Hospitalists

Assistive Framework for Automatic Detection of All the Zones in Retinopathy of Prematurity Using Deep Learning.

Retinopathy of prematurity (ROP) is a potentially blinding disorder seen in low birth weight preterm...

A machine learning based exploration of COVID-19 mortality risk.

Early prediction of patient mortality risks during a pandemic can decrease mortality by assuring eff...

Comparison of deep learning, radiomics and subjective assessment of chest CT findings in SARS-CoV-2 pneumonia.

PURPOSE: Comparison of deep learning algorithm, radiomics and subjective assessment of chest CT for ...

Predictive modelling of piezometric head and seepage discharge in earth dam using soft computational models.

Predictions of pore pressure and seepage discharge are the most important parameters in the design o...

Contrasting factors associated with COVID-19-related ICU admission and death outcomes in hospitalised patients by means of Shapley values.

Identification of those at greatest risk of death due to the substantial threat of COVID-19 can bene...

Video-Sensing Characterization for Hydrodynamic Features: Particle Tracking-Based Algorithm Supported by a Machine Learning Approach.

The efficient and reliable monitoring of the flow of water in open channels provides useful informat...

Hybridized neural networks for non-invasive and continuous mortality risk assessment in neonates.

Premature birth is the primary risk factor in neonatal deaths, with the majority of extremely premat...

Minimizing Selection and Classification Biases. Comment on "Clinical Characteristics and Prognostic Factors for Intensive Care Unit Admission of Patients With COVID-19: Retrospective Study Using Machine Learning and Natural Language Processing".

Authors' Reply to: Minimizing Selection and Classification Biases Comment on "Clinical Characteristics and Prognostic Factors for Intensive Care Unit Admission of Patients With COVID-19: Retrospective Study Using Machine Learning and Natural Language Processing".

Prediction of Bedridden Duration of Hospitalized Patients by Machine Learning Based on EMRs at Admission.

Being bedridden is a frequent comorbid condition that leads to a series of complications in clinical...

Comparison of machine-learning methodologies for accurate diagnosis of sepsis using microarray gene expression data.

We investigate the feasibility of molecular-level sample classification of sepsis using microarray g...

Blending Knowledge in Deep Recurrent Networks for Adverse Event Prediction at Hospital Discharge.

Deep learning architectures have an extremely high-capacity for modeling complex data in a wide vari...

Development and Validation of Machine Learning Models to Predict Admission From Emergency Department to Inpatient and Intensive Care Units.

STUDY OBJECTIVE: This study aimed to develop and validate 2 machine learning models that use histori...

Use of deep learning to develop continuous-risk models for adverse event prediction from electronic health records.

Early prediction of patient outcomes is important for targeting preventive care. This protocol descr...

Machine learning analysis: general features, requirements and cardiovascular applications.

Artificial intelligence represents the science which will probably change the future of medicine by ...

Diagnostic and prognostic capabilities of a biomarker and EMR-based machine learning algorithm for sepsis.

Sepsis is a major cause of mortality among hospitalized patients worldwide. Shorter time to administ...

Neural network predicts need for red blood cell transfusion for patients with acute gastrointestinal bleeding admitted to the intensive care unit.

Acute gastrointestinal bleeding is the most common gastrointestinal cause for hospitalization. For h...

Degradation and mechanism analysis of chloroxylenol in aqueous solution by gas-liquid discharge plasma combined with ozonation.

Gas-liquid discharge non-thermal plasma (NTP) coupled with an ozonation reactor was used to investig...

Relationship between Artificial Intelligence-Based General Anesthetics and Postoperative Cognitive Dysfunction.

Postoperative cognitive dysfunction (POCD) refers to the complications of the central nervous system...

The characteristics and evolution of pulmonary fibrosis in COVID-19 patients as assessed by AI-assisted chest HRCT.

The characteristics and evolution of pulmonary fibrosis in patients with coronavirus disease 2019 (C...

Mixed-data deep learning in repeated predictions of general medicine length of stay: a derivation study.

The accurate prediction of likely discharges and estimates of length of stay (LOS) aid in effective ...