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Inpatients

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Quantitative Evaluation of Performance during Robot-assisted Treatment.

Methods of information in medicine
INTRODUCTION: This article is part of the Focus Theme of Methods of Information in Medicine on "Methodologies, Models and Algorithms for Patients Rehabilitation".

POETenceph - Automatic identification of clinical notes indicating encephalopathy using a realist ontology.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Identifying inpatients with encephalopathy is important. The disorder is prevalent, often missed, and puts patients at risk. We describe POETenceph, natural language processing pipeline, which ranks clinical notes on the extent to which they indicate...

Predicting inpatient stay lasting 2 midnights or longer after robotic surgery for endometrial cancer.

Journal of minimally invasive gynecology
OBJECTIVE: To estimate the rate of inpatient stay and the factors predicting inpatient status after robotic surgery for endometrial cancer following the change in the Medicare definition of "inpatient" to include hospitalization spanning 2 midnights.

Rapid Response System Restructure: Focus on Prevention and Early Intervention.

Critical care nursing quarterly
This article describes the staged restructure of the rapid response program into a dedicated 24/7 proactive rapid response system in a quaternary academic medical center in the southern United States. Rapid response nurses (RRNs) completed clinical l...

Exploratory Analysis of Nationwide Japanese Patient Safety Reports on Suicide and Suicide Attempts Among Inpatients With Cancer Using Large Language Models.

Psycho-oncology
OBJECTIVE: Patients with cancer have a high risk of suicide. However, evidence-based preventive measures remain unclear. This study aimed to investigate suicide prevention strategies for hospitalized patients with cancer by analyzing nationwide patie...

Explainable Machine Learning Model to Preoperatively Predict Postoperative Complications in Inpatients With Cancer Undergoing Major Operations.

JCO clinical cancer informatics
PURPOSE: Preoperative prediction of postoperative complications (PCs) in inpatients with cancer is challenging. We developed an explainable machine learning (ML) model to predict PCs in a heterogenous population of inpatients with cancer undergoing s...

Effects of Language Differences on Inpatient Fall Detection Using Deep Learning.

Studies in health technology and informatics
This study examined the effects of language differences between Korean and English on the performance of natural language processing in the classification task of identifying inpatient falls from unstructured nursing notes.

Evaluation of inpatient medication guidance from an artificial intelligence chatbot.

American journal of health-system pharmacy : AJHP : official journal of the American Society of Health-System Pharmacists
PURPOSE: To analyze the clinical completeness, correctness, usefulness, and safety of chatbot and medication database responses to everyday inpatient medication-use questions.

Self-supervised machine learning using adult inpatient data produces effective models for pediatric clinical prediction tasks.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Development of electronic health records (EHR)-based machine learning models for pediatric inpatients is challenged by limited training data. Self-supervised learning using adult data may be a promising approach to creating robust pediatri...

Multimodal Deep Learning for Integrating Chest Radiographs and Clinical Parameters: A Case for Transformers.

Radiology
Background Clinicians consider both imaging and nonimaging data when diagnosing diseases; however, current machine learning approaches primarily consider data from a single modality. Purpose To develop a neural network architecture capable of integra...