Hospital-Based Medicine

Robot-assisted and conventional urology surgical procedures: comparison of average length of stay, economic status, operative time and patient's expenditure in a tertiary care hospital of North India.

Robot-assisted surgeries allows the surgeons to operate using remote-controlled robotic arms that are more effective in comparison to conventional (open/laparoscopic) surgeries. However, there is substantial lack of evidence on the effectiveness of robot-assisted surgeries in low to middle income countries (LMICs) like India. A study was conducted with an aim to evaluate the average length of stay...

Implementation of Hospital-to-Home Model for Nutritional Nursing Management of Patients with Chronic Kidney Disease Using Artificial Intelligence Algorithm Combined with CT Internet.

The objective of this study was to evaluate the application value of "Internet + hospital-to-home (H2H)" nutritional care model using the improved wavelet transform algorithm based on computed tomography (CT) images in the nutritional care management of chronic kidney disease (CKD) stages 3-5. A total of 120 patients with CKD were the research objects and they were randomly divided into two groups...

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 classifier in cable partial discharge (PD) pattern recog...

Information Extraction From Electronic Health Records to Predict Readmission Following Acute Myocardial Infarction: Does Natural Language Processing Using Clinical Notes Improve Prediction of Readmission?

Background Social risk factors influence rehospitalization rates yet are challenging to incorporate into prediction models. Integration of social risk...

Efficacy of a Deep Learning Convolutional Neural Network System for Melanoma Diagnosis in a Hospital Population.

(1) Background: The purpose of this study was to evaluate the efficacy in terms of sensitivity, specificity, and accuracy of the quantusSKIN system, a...

Scalable deep learning algorithm to compute percent pulmonary contusion among patients with rib fractures.

BACKGROUND: Pulmonary contusion exists along a spectrum of severity, yet is commonly binarily classified as present or absent. We aimed to develop a d...

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 administrative and clinical elements that are collecte...

Effect of Different Nursing Interventions on Discharged Patients with Cardiac Valve Replacement Evaluated by Deep Learning Algorithm-Based MRI Information.

This study was aimed to explore the application of cardiac magnetic resonance imaging (MRI) image segmentation model based on U-Net in the diagnosis o...

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 neural network (FCN) in liver computed tomography ...

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 epicardial adipose tissue (EAT) from low-dose computed ...

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 corresponding functional area and carry out complex c...

Application of Da Vinci Robot and Thoracoscopy in Radical Lung Cancer Surgery.

In this article, we have explored the feasibility and safety of Da Vinci's robotic surgery system in the radical resection of lung cancer. For this pu...

The Role of Gabapentinoids in the Substance Use Pattern of Adult Germans Seeking Inpatient Detoxification Treatment - A Pilot Study.

To shed more light on the addictive power of the gabapentinoids (GPTs) gabapentin and pregabalin, we performed a structured face-to-face interview wit...

A hybrid machine learning/deep learning COVID-19 severity predictive model from CT images and clinical data.

COVID-19 clinical presentation and prognosis are highly variable, ranging from asymptomatic and paucisymptomatic cases to acute respiratory distress s...

Artificial intelligence and multidisciplinary team meetings; a communication challenge for radiologists' sense of agency and position as spider in a web?

PURPOSE: This paper focuses on how the implementation of artificial intelligence algorithms (AI) challenges and changes the existing communication pra...

Machine Learning Improves Prediction Over Logistic Regression on Resected Colon Cancer Patients.

INTRODUCTION: Despite advances, readmission and mortality rates for surgical patients with colon cancer remain high. Prediction models using regressio...

Robotic versus hand-assisted laparoscopic living donor nephrectomy: comparison of two minimally invasive techniques in kidney transplantation.

Robot-assisted donor nephrectomy (RDN) is increasingly used due to its advantages such as its precision and reduced learning curve when compared to la...

Implementing the Robotic deep inferior epigastric perforator Flap in daily practice: A series of 10 cases.

The deep inferior epigastric perforator (DIEP) flap is the workhorse in microvascular breast reconstruction. Rectus muscle sacrifice or denervation an...

Robot-Assisted Prostate-Specific Membrane Antigen-Radioguided Surgery in Primary Diagnosed Prostate Cancer.

The objective of this study was to evaluate the safety and feasibility of Tc-based prostate-specific membrane antigen (PSMA) robot-assisted-radioguide...

E-Learning Research Trends in Higher Education in Light of COVID-19: A Bibliometric Analysis.

This paper provides a broad bibliometric overview of the important conceptual advances that have been published during COVID-19 within "e-learning in ...