Hospital-Based Medicine

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 patients with severe limitations in walking, rehabilitation is a challenge. The Hybrid Assistive Limb (HAL) is a gait machine that captures voluntary actions and support gait motions. Previous studies of HAL indicate beneficial effects on walking, but these results need to be confirmed in blinded, randomi...

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

Prediction of perioperative transfusions using an artificial neural network.

BACKGROUND: Accurate prediction of operative transfusions is essential for resource allocation and identifying patients at risk of postoperative adver...

IoT Based Predictive Maintenance Management of Medical Equipment.

Technological advancements are the main drivers of the healthcare industry as it has a high impact on delivering the best patient care. Recent years w...

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...

Pharmacometrics and Machine Learning Partner to Advance Clinical Data Analysis.

Clinical pharmacology is a multidisciplinary data sciences field that utilizes mathematical and statistical methods to generate maximal knowledge from...

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

Adversarial Representation Learning for Robust Patient-Independent Epileptic Seizure Detection.

Epilepsy is a chronic neurological disorder characterized by the occurrence of spontaneous seizures, which affects about one percent of the worlds pop...

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 ...

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 linked to reductions in mortality, intensive care unit ...

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 partial nephrectomy (RAPN) via the retroperitoneal ap...

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 of decision making. The aim of the present study wa...

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 admission could improve clinical and operational decis...

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...

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)...

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 medical rehabilitation. While there are advantage...

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...

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 achieve the promise of precision medicine, individualiz...

Economic Evaluation of Robot-Based Telemedicine Consultation Services.

Through information and communication technology, telemedicine can deliver medical care without time and place restrictions, increasing health care a...