Hospital-Based Medicine

Hospitalists

Latest AI and machine learning research in hospitalists for healthcare professionals.

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Reconstruction of missing spring discharge by using deep learning models with ensemble empirical mode decomposition of precipitation.

A continuous and complete spring discharge record is critical in understanding the hydrodynamic beha...

Liver Damage Is Related to the Degree of Being Underweight in Anorexia Nervosa and Improves Rapidly with Weight Gain.

Background: The present study investigates the relationship between hypertransaminasemia and malnutr...

Deep learning-based lesion subtyping and prediction of clinical outcomes in COVID-19 pneumonia using chest CT.

The main objective of this work is to develop and evaluate an artificial intelligence system based o...

A Long Short-Term Memory Network for Plasma Diagnosis from Langmuir Probe Data.

Electrostatic probe diagnosis is the main method of plasma diagnosis. However, the traditional diagn...

Optimization of Reservoir Flood Control Operation Based on Multialgorithm Deep Learning.

With the rapid development of China's social economy, it is the most important task for the water co...

Optimizing discharge after major surgery using an artificial intelligence-based decision support tool (DESIRE): An external validation study.

BACKGROUND: In the DESIRE study (Discharge aftEr Surgery usIng aRtificial intElligence), we have pre...

Experimental analysis and parameter optimization on the reduction of NOx from diesel engine using RSM and ANN Model.

The major emission sources of NO are from automobiles, trucks, and various non-road vehicles, power ...

Cloud-based neuro-fuzzy hydro-climatic model for water quality assessment under uncertainty and sensitivity.

River water quality is a function of various bio-physicochemical parameters which can be aggregated ...

Outcome Prediction in Patients with Severe Traumatic Brain Injury Using Deep Learning from Head CT Scans.

Background After severe traumatic brain injury (sTBI), physicians use long-term prognostication to g...

Natural language processing of admission notes to predict severe maternal morbidity during the delivery encounter.

BACKGROUND: Severe maternal morbidity and mortality remain public health priorities in the United St...

Preliminary Outcomes After Same Day Discharge Protocol for Robot-Assisted Partial Nephrectomy: A Single Centre Experience.

OBJECTIVE: To assess the feasibility and safety of same-day discharge (SDD) surgery after robot-assi...

FoSSA Optimization-Based SVM Classifier for the Recognition of Partial Discharge Patterns in HV Cables.

In order to enhance the classification accuracy and the generalization performance of the SVM classi...

Early identification of ICU patients at risk of complications: Regularization based on robustness and stability of explanations.

The aim of this study is to build machine learning models to predict severe complications using admi...

Characteristics of Computed Tomography Images for Patients with Acute Liver Injury Caused by Sepsis under Deep Learning Algorithm.

This study was aimed at exploring the application of image segmentation based on full convolutional ...

Automatic Deep-Learning Segmentation of Epicardial Adipose Tissue from Low-Dose Chest CT and Prognosis Impact on COVID-19.

Background: To develop a deep-learning (DL) pipeline that allowed an automated segmentation of epica...

Neuronal Apoptosis in Patients with Liver Cirrhosis and Neuronal Epileptiform Discharge Model Based upon Multi-Modal Fusion Deep Learning.

Neurons refer to nerve cells. Each neuron is connected with thousands of other neurons to form a cor...

Network analytics and machine learning for predicting length of stay in elderly patients with chronic diseases at point of admission.

BACKGROUND: An aging population with a burden of chronic diseases puts increasing pressure on health...

Water clarity mapping of global lakes using a novel hybrid deep-learning-based recurrent model with Landsat OLI images.

Information regarding water clarity at large spatiotemporal scales is critical for understanding com...

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