Hospital-Based Medicine

Hospitalists

Latest AI and machine learning research in hospitalists for healthcare professionals.

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Early heart rate variability evaluation enables to predict ICU patients' outcome.

Heart rate variability (HRV) is a mean to evaluate cardiac effects of autonomic nervous system activ...

Automatic classification of nerve discharge rhythms based on sparse auto-encoder and time series feature.

BACKGROUND: Nerve discharge is the carrier of information transmission, which can reveal the basic r...

Assessment of the da Vinci Single Port Robotic Platform on Cholecystectomy in Adolescents.

The new da Vinci single port (SP) robotic platform has great appeal for pediatric surgery. To asses...

Development and validation of a machine learning algorithm-based risk prediction model of pressure injury in the intensive care unit.

The study aimed to establish a machine learning-based scoring nomogram for early recognition of like...

Analysis and prediction of water quality using deep learning and auto deep learning techniques.

Natural water sources like ponds, lakes and rivers are facing a great threat because of activities l...

Evaluation of shape factor impact on discharge coefficient of side orifices using boost simulation model with extreme learning machine data-driven.

In this paper, for the first time, the impact of the shape factor on the discharge coefficient of si...

Unstructured clinical notes within the 24 hours since admission predict short, mid & long-term mortality in adult ICU patients.

Mortality prediction for intensive care unit (ICU) patients is crucial for improving outcomes and ef...

Outpatient Inpatient Robot-Assisted Radical Prostatectomy: An Evidence-Based Analysis of Comparative Outcomes.

To provide a systematic analysis of outcomes comparing outpatient and inpatient robot-assisted radi...

Comparison of Higher-Than-Standard to D-Dimer Driven Thromboprophylaxis in Hospitalized Patients With COVID-19.

Coronavirus disease 2019 is a global health threat often accompanied with coagulopathy. Despite use...

Computational signatures for post-cardiac arrest trajectory prediction: Importance of early physiological time series.

BACKGROUND: There is an unmet need for timely and reliable prediction of post-cardiac arrest (CA) cl...

Diagnostic Value of SonoVue Contrast-Enhanced Ultrasonography in Nipple Discharge Based on Artificial Intelligence.

This paper aims to explore the application value of SonoVue contrast-enhanced ultrasonography based ...

Deep-Learning Approach to Predict Survival Outcomes Using Wearable Actigraphy Device Among End-Stage Cancer Patients.

Survival prediction is highly valued in end-of-life care clinical practice, and patient performance ...

A Comparison of Models Predicting One-Year Mortality at Time of Admission.

CONTEXT: Hospitalization provides an opportunity to address end-of-life care (EoLC) preferences if p...

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...

Intelligent Monitoring of Care Status for COPD Patients Based on Deep Learning.

To discuss the application method and effect of COPD patients in deep learning in intelligent monito...

An efficient strategy for predicting river dissolved oxygen concentration: application of deep recurrent neural network model.

Dissolved oxygen (DO) concentration in water is one of the key parameters for assessing river water ...

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...

Using explainable machine learning to identify patients at risk of reattendance at discharge from emergency departments.

Short-term reattendances to emergency departments are a key quality of care indicator. Identifying p...

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

BACKGROUND: Disease prediction based on electronic health records (EHRs) is essential for personaliz...

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...

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