Hospital-Based Medicine

Beneficial Effects of Robot-Assisted Gait Training on Functional Recovery in Women after Stroke: A Cohort Study.

Robot-assisted gait training (RAGT) could be a rehabilitation option for patients after experiencing a stroke. This study aims to determine the sex-related response to robot-assisted gait training in a cohort of subacute stroke patients considering mixed results previously reported. In this study, 236 participants (145 males, 91 females) were admitted to a rehabilitation facility after experienc...

Interpretable time-aware and co-occurrence-aware network for medical prediction.

BACKGROUND: Disease prediction based on electronic health records (EHRs) is essential for personalized healthcare. But it's hard due to the special data structure and the interpretability requirement of methods. The structure of EHR is hierarchical: each patient has a sequence of admissions, and each admission has some co-occurrence diagnoses. However, the existing methods only partially model the...

Recurrent Wheeze Exacerbations Following Acute Bronchiolitis-A Machine Learning Approach.

Acute bronchiolitis is one of the most common respiratory infections in infancy. Although most infants with bronchiolitis do not get hospitalized, in...

Robot-assisted stereoelectroencephalography in young children: technical challenges and considerations.

Robot-assisted stereoelectroencephalography (sEEG) is frequently employed to localize epileptogenic zones in patients with medically refractory epilep...

Does the magic of BERT apply to medical code assignment? A quantitative study.

Unsupervised pretraining is an integral part of many natural language processing systems, and transfer learning with language models has achieved rema...

Development of a Machine Learning Algorithm for Prediction of Complications and Unplanned Readmission Following Reverse Total Shoulder Arthroplasty.

BACKGROUND: Reverse total shoulder arthroplasty (rTSA) offers tremendous promise for the treatment of complex pathologies beyond the scope of anatomic...

Machine learning in the prediction of medical inpatient length of stay.

Length of stay (LOS) estimates are important for patients, doctors and hospital administrators. However, making accurate estimates of LOS can be diffi...

A machine-learning parsimonious multivariable predictive model of mortality risk in patients with Covid-19.

The COVID-19 pandemic is impressively challenging the healthcare system. Several prognostic models have been validated but few of them are implemented...

Single-port Mini-Pfannenstiel Robotic Pyeloplasty: Establishing a Non-narcotic Pathway Along With a Same-day Discharge Protocol.

OBJECTIVE: To analyze the feasibility of a same day discharge protocol following single-port (SP) robotic pyeloplasty.

The Route of Motor Recovery in Stroke Patients Driven by Exoskeleton-Robot-Assisted Therapy: A Path-Analysis.

: Exoskeleton-robot-assisted therapy is known to positively affect the recovery of arm functions in stroke patients. However, there is a lack of evide...

A novel artificial intelligence based intensive care unit monitoring system: using physiological waveforms to identify sepsis.

A massive amount of multimodal data are continuously collected in the intensive care unit (ICU) along each patient stay, offering a great opportunity ...

The Potential Cost-Effectiveness of a Machine Learning Tool That Can Prevent Untimely Intensive Care Unit Discharge.

OBJECTIVES: The machine learning prediction model Pacmed Critical (PC), currently under development, may guide intensivists in their decision-making p...

Can Deep Learning-Based Volumetric Analysis Predict Oxygen Demand Increase in Patients with COVID-19 Pneumonia?

: This study aimed to investigate whether predictive indicators for the deterioration of respiratory status can be derived from the deep learning data...

Predictive modeling for 14-day unplanned hospital readmission risk by using machine learning algorithms.

BACKGROUND: Early unplanned hospital readmissions are associated with increased harm to patients, increased medical costs, and negative hospital reput...

Prediction of Readmission in Geriatric Patients From Clinical Notes: Retrospective Text Mining Study.

BACKGROUND: Prior literature suggests that psychosocial factors adversely impact health and health care utilization outcomes. However, psychosocial fa...

Early prediction of in-hospital death of COVID-19 patients: a machine-learning model based on age, blood analyses, and chest x-ray score.

An early-warning model to predict in-hospital mortality on admission of COVID-19 patients at an emergency department (ED) was developed and validated ...

Early prediction of severe acute pancreatitis using machine learning.

BACKGROUND: Acute pancreatitis (AP) is one of the most common causes of gastrointestinal-related hospitalizations in the United States. Severe AP (SAP...

Sentiment Analysis Based on the Nursing Notes on In-Hospital 28-Day Mortality of Sepsis Patients Utilizing the MIMIC-III Database.

In medical visualization, nursing notes contain rich information about a patient's pathological condition. However, they are not widely used in the pr...

Content-based Image Retrieval by Using Deep Learning for Interstitial Lung Disease Diagnosis with Chest CT.

Background Evaluation of interstitial lung disease (ILD) at CT is a challenging task that requires experience and is subject to substantial interreade...

Simultaneous degradation of glucocorticoids and sterilization using bubbling corona discharge plasma based systems: A promising terminal water treatment facility for hospital wastewater.

Glucocorticoids (GCs) have drawn great concern due to their widespread contamination in the environment and application in treating patients with COVI...