Hospital-Based Medicine

Improving patient flow during infectious disease outbreaks using machine learning for real-time prediction of patient readiness for discharge.

BACKGROUND: Delays in patient flow and a shortage of hospital beds are commonplace in hospitals duri...

Opportunities and Barriers to Rural Telerobotic Surgical Health Care in 2021: Report and Research Agenda from a Stakeholder Workshop.

There are well-recognized challenges to delivering specialty health care in rural settings. These c...

Evaluation of the Postoperative Nursing Effect of Thoracic Surgery Assisted by Artificial Intelligence Robot.

In order to evaluate the postoperative nursing effect of artificial intelligence robot-assisted thor...

Artificial intelligence (AI) in breast cancer care - leveraging multidisciplinary skills to improve care.

Annual nationwide analysis of costs and post-operative outcomes after radical prostatectomy according to the surgical approach (open, laparoscopic, and robotic).

OBJECTIVE: Annual countrywide data are scarce when comparing surgical approaches in terms of hospita...

Concomitant robot-assisted laparoscopic surgeries for upper and lower urinary tract malignancies: a comprehensive literature review.

Worldwide, we have witnessed an expansion of robot-assisted laparoscopic surgery (RALS) and thanks t...

Mandate to evaluate robotic surgery implementation: a 12-year retrospective analysis of impact and future implications.

The introduction of robotic surgery in hospitals has raised much debate given the various effects on...

Robotic repair of post-oesophagectomy hiatal hernia.

Diaphragmatic hiatal hernia is a potential complication of oesophagectomy in cancer patients. Over t...

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 experiencin...

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

Acute bronchiolitis is one of the most common respiratory infections in infancy. Although most infa...

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

Robot-assisted stereoelectroencephalography (sEEG) is frequently employed to localize epileptogenic ...

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 transf...

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 o...

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

Length of stay (LOS) estimates are important for patients, doctors and hospital administrators. Howe...

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 h...

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) ro...

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 ...

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) alon...

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,...

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, in...

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 c...