Hospitalists

Outpatient Robot-Assisted Radical Prostatectomy: Are Patients Ready for Same-Day Discharge?

Several case series have demonstrated the safety and feasibility of outpatient robot-assisted radic...

Dynamic and explainable machine learning prediction of mortality in patients in the intensive care unit: a retrospective study of high-frequency data in electronic patient records.

BACKGROUND: Many mortality prediction models have been developed for patients in intensive care unit...

Towards Reliable ARDS Clinical Decision Support: ARDS Patient Analytics with Free-text and Structured EMR Data.

In this work, we utilize a combination of free-text and structured data to build Acute Respiratory D...

Computer-assisted estimation of interictal discharge burden in idiopathic generalized epilepsy.

Same-day discharge surgery for robot-assisted radical prostatectomy in the era of ERAS and prehabilitation pathways: a contemporary, comparative, feasibility study.

PURPOSE: To assess the feasibility of same-day discharge (SDD) after robot-assisted radical prostate...

Prediction of general medical admission length of stay with natural language processing and deep learning: a pilot study.

Predicting patient outcomes in psychiatric hospitals with routine data: a machine learning approach.

BACKGROUND: A common problem in machine learning applications is availability of data at the point o...

Mixed-integer optimization approach to learning association rules for unplanned ICU transfer.

After admission to emergency department (ED), patients with critical illnesses are transferred to in...

Monitoring and detecting faults in wastewater treatment plants using deep learning.

Wastewater treatment plants use many sensors to control energy consumption and discharge quality. Th...

Combining deep learning with token selection for patient phenotyping from electronic health records.

Artificial intelligence provides the opportunity to reveal important information buried in large amo...

Benchmarking Deep Learning Architectures for Predicting Readmission to the ICU and Describing Patients-at-Risk.

To compare different deep learning architectures for predicting the risk of readmission within 30 da...

Prediction of Early TBI Mortality Using a Machine Learning Approach in a LMIC Population.

In a time when the incidence of severe traumatic brain injury (TBI) is increasing in low- to middle...

Deep Natural Language Processing Identifies Variation in Care Preference Documentation.

CONTEXT: Documentation of care preferences within 48 hours of admission to an intensive care unit (I...

Prediction of general medical admission length of stay with natural language processing and deep learning: a pilot study.

Length of stay (LOS) and discharge destination predictions are key parts of the discharge planning p...

Intracatheter Tissue Plasminogen Activator for Chronic Subdural Hematomas after Failed Bedside Twist Drill Craniostomy: A Retrospective Review.

Introduction Chronic subdural hematomas (cSDH) are common in neurosurgery with various symptoms and ...

Robotic body weight support enables safe stair negotiation in compliance with basic locomotor principles.

BACKGROUND: After a neurological injury, mobility focused rehabilitation programs intensively train ...

The impact of extraneous features on the performance of recurrent neural network models in clinical tasks.

Electronic Medical Records (EMR) are a rich source of patient information, including measurements re...

Implementation of machine learning algorithms to create diabetic patient re-admission profiles.

BACKGROUND: Machine learning is a branch of Artificial Intelligence that is concerned with the desig...

Development and Validation of a Machine Learning Model to Aid Discharge Processes for Inpatient Surgical Care.

IMPORTANCE: Inpatient overcrowding is associated with delays in care, including the deferral of surg...

Meteorological factors for subarachnoid hemorrhage in the greater Düsseldorf area revisited: a machine learning approach to predict the probability of admission of patients with subarachnoid hemorrhage.

BACKGROUND: Reported data regarding the relation between the incidence of spontaneous subarachnoid h...

Finding relevant free-text radiology reports at scale with IBM Watson Content Analytics: a feasibility study in the UK NHS.

BACKGROUND: Significant amounts of health data are stored as free-text within clinical reports, lett...