AIMC Topic: Patient Discharge

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Energy landscapes for a machine-learning prediction of patient discharge.

Physical review. E
The energy landscapes framework is applied to a configuration space generated by training the parameters of a neural network. In this study the input data consists of time series for a collection of vital signs monitored for hospital patients, and th...

Characteristics of outpatient clinical summaries in the United States.

International journal of medical informatics
In the United States, federal regulations require that outpatient practices provide a clinical summary to ensure that patients understand what transpired during their appointment and what to do before the next visit. To determine whether clinical sum...

An automated knowledge-based textual summarization system for longitudinal, multivariate clinical data.

Journal of biomedical informatics
OBJECTIVES: Design and implement an intelligent free-text summarization system: The system's input includes large numbers of longitudinal, multivariate, numeric and symbolic clinical raw data, collected over varying periods of time, and in different ...

Natural Language Processing for Cohort Discovery in a Discharge Prediction Model for the Neonatal ICU.

Applied clinical informatics
OBJECTIVES: Discharging patients from the Neonatal Intensive Care Unit (NICU) can be delayed for non-medical reasons including the procurement of home medical equipment, parental education, and the need for children's services. We previously created ...

Real-time prediction of inpatient length of stay for discharge prioritization.

Journal of the American Medical Informatics Association : JAMIA
OBJECTIVE: Hospitals are challenged to provide timely patient care while maintaining high resource utilization. This has prompted hospital initiatives to increase patient flow and minimize nonvalue added care time. Real-time demand capacity managemen...

The use of artificial neural networks to predict delayed discharge and readmission in enhanced recovery following laparoscopic colorectal cancer surgery.

Techniques in coloproctology
BACKGROUND: Artificial neural networks (ANNs) can be used to develop predictive tools to enable the clinical decision-making process. This study aimed to investigate the use of an ANN in predicting the outcomes from enhanced recovery after colorectal...

Bilingual term alignment from comparable corpora in English discharge summary and Chinese discharge summary.

BMC bioinformatics
BACKGROUND: Electronic medical record (EMR) systems have become widely used throughout the world to improve the quality of healthcare and the efficiency of hospital services. A bilingual medical lexicon of Chinese and English is needed to meet the de...

An end-to-end hybrid algorithm for automated medication discrepancy detection.

BMC medical informatics and decision making
BACKGROUND: In this study we implemented and developed state-of-the-art machine learning (ML) and natural language processing (NLP) technologies and built a computerized algorithm for medication reconciliation. Our specific aims are: (1) to develop a...

Stratifying Risk for Postpartum Depression at Time of Hospital Discharge.

The American journal of psychiatry
OBJECTIVE: Postpartum depression (PPD) is a major contributor to postpartum morbidity and mortality. Beyond efforts at routine screening, risk stratification models could enable more targeted interventions in settings with limited resources. The auth...