Hospital-Based Medicine

A Scalable Smartwatch-Based Medication Intake Detection System Using Distributed Machine Learning.

Poor Medication adherence causes significant economic impact resulting in hospital readmission, hosp...

A randomized controlled study incorporating an electromechanical gait machine, the Hybrid Assistive Limb, in gait training of patients with severe limitations in walking in the subacute phase after stroke.

Early onset, intensive and repetitive, gait training may improve outcome after stroke but for patien...

Prediction of perioperative transfusions using an artificial neural network.

BACKGROUND: Accurate prediction of operative transfusions is essential for resource allocation and i...

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...

Pharmacometrics and Machine Learning Partner to Advance Clinical Data Analysis.

Clinical pharmacology is a multidisciplinary data sciences field that utilizes mathematical and stat...

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

An Artificial Neural Network-based Predictive Model to Support Optimization of Inpatient Glycemic Control.

Achieving glycemic control in critical care patients is of paramount importance, and has been linke...

Comparison Studies of "Ultrathin Parenchyma" Resection and Sharp Dissection in Robotic Partial Nephrectomy for Renal Tumors.

The aim of this study was to introduce the "ultrathin parenchyma" resection in a robot-assisted par...

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...

Prospective and External Evaluation of a Machine Learning Model to Predict In-Hospital Mortality of Adults at Time of Admission.

IMPORTANCE: The ability to accurately predict in-hospital mortality for patients at the time of admi...

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...

Big Data Analytics and Sensor-Enhanced Activity Management to Improve Effectiveness and Efficiency of Outpatient Medical Rehabilitation.

Numerous societal trends are compelling a transition from inpatient to outpatient venues of care for...

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...

Learning Personalized Treatment Rules from Electronic Health Records Using Topic Modeling Feature Extraction.

To address substantial heterogeneity in patient response to treatment of chronic disorders and achie...

Economic Evaluation of Robot-Based Telemedicine Consultation Services.

Through information and communication technology, telemedicine can deliver medical care without tim...

Improving breast cancer care coordination and symptom management by using AI driven predictive toolkits.

Integrated breast cancer care is complex, marked by multiple hand-offs between primary care and spec...

The Antifungal Peptide MCh-AMP1 Derived From Inhibits Growth via Inducing ROS Generation and Altering Fungal Cell Membrane Permeability.

The rise of antifungal drug resistance in species responsible for life threatening candidiasis is c...

Predicting Chronic Subdural Hematoma Recurrence and Stroke Outcomes While Withholding Antiplatelet and Anticoagulant Agents.

The aging of the western population and the increased use of oral anticoagulation (OAC) and antipla...

Dynamic readmission prediction using routine postoperative laboratory results after radical cystectomy.

OBJECTIVE: To determine if the addition of electronic health record data enables better risk stratif...

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...