AIMC Topic: Emergency Service, Hospital

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Deploying artificial intelligence software in an NHS trust: a how-to guide for clinicians.

The British journal of radiology
Over the past 10 years, artificial intelligence (AI) has become one of the fastest-growing sectors in healthcare. There are now numerous new technologies designed to cut costs and improve diagnoses and treatment pathways. However, there is significan...

Integrating Remote Patient Monitoring Data into Machine Learning Models for Predicting Emergency Department Utilization.

AMIA ... Annual Symposium proceedings. AMIA Symposium
The integration of Remote Patient Monitoring (RPM) data into risk stratification models has emerged as a promising approach for improving healthcare delivery and patient outcomes. In this work, we explore the integration of RPM features - including a...

Improving Emergency Department Visit Risk Prediction: Exploring the Operational Utility of Applied Patient Portal Messages.

AMIA ... Annual Symposium proceedings. AMIA Symposium
Patient portal messages represent a unique source of clinical data due to how they represent the voice of the patient, provide a glimpse into care delivery between episodic synchronous appointments, and capture variations in patient behavior and heal...

Applications of Artificial Intelligence and Machine Learning in Emergency Medicine Triage - A Systematic Review.

Medical archives (Sarajevo, Bosnia and Herzegovina)
BACKGROUND: Overcrowding in Emergency departments adversely impacts efficiency, patient outcomes, and resource allocation. Accurate triage systems are essential for prioritizing care and optimizing resources. While traditional methods provide a found...

Perceptions of Artificial Intelligence-Assisted Care for Children With a Respiratory Complaint.

Hospital pediatrics
OBJECTIVES: To evaluate caregiver opinions on the use of artificial intelligence (AI)-assisted medical decision-making for children with a respiratory complaint in the emergency department (ED).

Combining NLP and Machine Learning for Differential Diagnosis of COPD Exacerbation Using Emergency Room Data.

Studies in health technology and informatics
Chronic Obstructive Pulmonary Disease (COPD) exacerbation exhibits a set of overlapping symptoms with various forms of cardiovascular disease, which makes its early identification challenging. Timely identification of the underlying condition that ca...

Artificial intelligence may enhance emergency triage and management.

The journal of trauma and acute care surgery
The entry of Artificial Intelligence (AI) into Intensive Care has become a reality. We think that only with robust validation studies accomplished by a multidisciplinary team the gap between clinical research and clinical practice can be bridged.

Ethical Perspectives on Implementing AI to Predict Mortality Risk in Emergency Department Patients: A Qualitative Study.

Studies in health technology and informatics
Artificial intelligence (AI) is predicted to improve health care, increase efficiency and save time and recourses, especially in the context of emergency care where many critical decisions are made. Research shows the urgent need to develop principle...

Diagnosis Classification in the Emergency Room Using Natural Language Processing.

Studies in health technology and informatics
Diagnosis classification in the emergency room (ER) is a complex task. We developed several natural language processing classification models, looking both at the full classification task of 132 diagnostic categories and at several clinically applica...

Improving Methods of Identifying Anaphylaxis for Medical Product Safety Surveillance Using Natural Language Processing and Machine Learning.

American journal of epidemiology
We sought to determine whether machine learning and natural language processing (NLP) applied to electronic medical records could improve performance of automated health-care claims-based algorithms to identify anaphylaxis events using data on 516 pa...