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Patient Discharge

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Use of machine learning to identify protective factors for death from COVID-19 in the ICU: a retrospective study.

PeerJ
BACKGROUND: Patients in serious condition due to COVID-19 often require special care in intensive care units (ICUs). This disease has affected over 758 million people and resulted in 6.8 million deaths worldwide. Additionally, the progression of the ...

Predicting adverse long-term neurocognitive outcomes after pediatric intensive care unit admission.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Critically ill children may suffer from impaired neurocognitive functions years after ICU (intensive care unit) discharge. To assess neurocognitive functions, these children are subjected to a fixed sequence of tests. Underg...

A nursing note-aware deep neural network for predicting mortality risk after hospital discharge.

International journal of nursing studies
BACKGROUND: ICU readmissions and post-discharge mortality pose significant challenges. Previous studies used EHRs and machine learning models, but mostly focused on structured data. Nursing records contain crucial unstructured information, but their ...

Translational artificial intelligence-led optimization and realization of estimated discharge with a supportive weekend interprofessional flow team (TAILORED-SWIFT).

Internal and emergency medicine
Weekend discharges occur less frequently than discharges on weekdays, contributing to hospital congestion. Artificial intelligence algorithms have previously been derived to predict which patients are nearing discharge based upon ward round notes. In...

The Application Artificial Intelligence-Assisted Robot System in Nursing Follow-up of Discharged Patients.

Studies in health technology and informatics
To construct a robot intelligent discharge follow-up platform and explore its application effects in clinical discharge follow-up scenarios Applying intelligent voice technology to build a robot intelligent discharge follow-up platform, replacing nur...

A systematic literature review of predicting patient discharges using statistical methods and machine learning.

Health care management science
Discharge planning is integral to patient flow as delays can lead to hospital-wide congestion. Because a structured discharge plan can reduce hospital length of stay while enhancing patient satisfaction, this topic has caught the interest of many hea...

From admission to discharge: a systematic review of clinical natural language processing along the patient journey.

BMC medical informatics and decision making
BACKGROUND: Medical text, as part of an electronic health record, is an essential information source in healthcare. Although natural language processing (NLP) techniques for medical text are developing fast, successful transfer into clinical practice...

Automation of Trainable Datasets Generation for Medical-Specific Language Model: Using MIMIC-IV Discharge Notes.

Studies in health technology and informatics
This study introduces a novel approach for generating machine-generated instruction datasets for fine-tuning medical-specialized language models using MIMIC-IV discharge records. The study created a large-scale text dataset comprising instructions, c...

Predicting whether patients in an acute medical unit are physiologically fit-for-discharge using machine learning: A proof-of-concept.

International journal of medical informatics
INTRODUCTION: Delays in discharging patients from Acute Medical Units hamper patient flows throughout the hospital. The decision to discharge a patient is mainly based on the patients' physiological condition, but may vary between physicians. An obje...

Application of artificial intelligence (AI) in the creation of discharge summaries in psychiatric clinics.

International journal of psychiatry in medicine
BackgroundThe integration of artificial intelligence (AI; ChatGPT 4.0) into medical workflow presents a great potential to enhance efficiency and quality. The use of AI in the creation of discharge summaries is particularly promising. The course of e...