Hospitalists

Correlation of Measured and Estimated Creatinine Clearance in Hospitalized Elderly Patients: A Retrospective Cohort Study.

Accurate assessment of renal function is essential in hospitalized elderly patients. Few studies have examined the accuracy of Cockcroft-Gault (C-G) estimates of creatinine clearance (CrCl) compared with measured clearance in these patients. The objective of this study was to determine the correlation between C-G estimates of CrCl and measured CrCl in hospitalized elderly patients. This Institu...

A machine learning approach to risk assessment for alcohol withdrawal syndrome.

At present, risk assessment for alcohol withdrawal syndrome relies on clinical judgment. Our aim was to develop accurate machine learning tools to predict alcohol withdrawal outcomes at the individual subject level using information easily attainable at patients' admission. An observational machine learning analysis using nested cross-validation and out-of-sample validation was applied to alcohol-...

Exploration of critical care data by using unsupervised machine learning.

BACKGROUND AND OBJECTIVE: Identification of subgroups may be useful to understand the clinical characteristics of ICU patients. The purposes of this s...

A machine learning model for predicting risk of hospital readmission within 30 days of discharge: validated with LACE index and patient at risk of hospital readmission (PARR) model.

The objective of this study was to design and develop a predictive model for 30-day risk of hospital readmission using machine learning techniques. Th...

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 radical prostatectomy (RARP) in well-selected patients;...

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 units (ICUs); most are based on data available at ICU ...

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 Distress Syndrome(ARDS) prediction models and ARDS ...

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 prostatectomy (RARP) in the context of enhanced recovery a...

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

QuPWM: Feature Extraction Method for Epileptic Spike Classification.

Epilepsy is a neurological disorder ranked as the second most serious neurological disease known to humanity, after stroke. Inter-ictal spiking is an ...

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 intensive care unit (ICU) due to unexpected clinical...

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 amounts of complex data. Electronic health records (e...

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

Wastewater treatment plants use many sensors to control energy consumption and discharge quality. These sensors produce a vast amount of data which ca...

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 days of discharge from the intensive care unit (ICU)...

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-income countries (LMICs), it is important to unde...

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 (ICU) is a National Quality Forum-endorsed quality m...

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 process for general medical hospital inpatients. It...

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 significant morbidity and mortality. Treatment var...

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 walking on treadmills or overground. However, afte...