Hospital-Based Medicine

Commentary: Machine Learning With Feature Domains Elucidates Candidate Drivers of Hospital Readmission Following Spine Surgery in a Large Single-Center Patient Cohort.

[Risk factors for postoperative intestinal obstruction in patients undergoing robot-assisted laparoscopic radical prostatectomy].

To analyze the risk factors of postoperative intestinal obstruction (POI) in patients undergoing robot-assisted laparoscopic radical prostatectomy (RARP). The clinical data of 573 patients receiving RARP from January to December 2019 in Nanjing Drum Tower Hospital were analyzed retrospectively. According to the occurrence of POI, the cases were divided into the occurrence group and the non-occur...

[Necessity of Pelvic Drain Placement after Robot-Assisted Radical Prostatectomy].

Sixty eight patients had robot-assisted radical prostatectomy (RARP) from January 2016 to April 2017 with estimated blood loss of less than 500 ml. We...

Machine Learning for Predictive Modeling of 90-day Readmission, Major Medical Complication, and Discharge to a Facility in Patients Undergoing Long Segment Posterior Lumbar Spine Fusion.

STUDY DESIGN: Retrospective case control study.

Concordance between treatment recommendations provided by IBM Watson for Oncology and a multidisciplinary tumor board for breast cancer in China.

OBJECTIVE: Watson for Oncology (WFO), an artificial intelligence from IBM Corporation, can provide a treatment plan by analyzing patient's disease cha...

Omitting Cortical Renorrhaphy in Robot-Assisted Partial Nephrectomy: Is it Safe? A Single Center Large Case Series.

Preserving renal function after robot-assisted partial nephrectomy (RAPN) is important and influenced by the technique of renal reconstruction among ...

Machine Learning Prognostic Models for Gastrointestinal Bleeding Using Electronic Health Record Data.

Risk assessment tools for patients with gastrointestinal bleeding may be used for determining level of care and informing management decisions. Develo...

Patients' Perceptions After Robot-Assisted Surgery: An Integrative Review.

Surgical techniques have greatly changed and advanced with the advent of robot-assisted surgery (RAS). Patient outcome measures for RAS generally focu...

Designing an optimal inventory management model for the blood supply chain: Synthesis of reusable simulation and neural network.

Blood supply managers in the blood supply chain have always sought to create enough reserves to increase access to different blood products and reduce...

A Survey of Nurses' Need for Care Robots in Children's Hospitals: Combining Robot-Care, Game-Care, and Edu-Care.

The purpose of this study was to investigate nurses' need for care robots in children's hospitals and to help develop care robots that can be used by ...

Collaborative, Multidisciplinary Evaluation of Cancer Variants Through Virtual Molecular Tumor Boards Informs Local Clinical Practices.

PURPOSE: The cancer research community is constantly evolving to better understand tumor biology, disease etiology, risk stratification, and pathways ...

Real-time finger force prediction via parallel convolutional neural networks: a preliminary study.

Continuous and accurate decoding of intended motions is critical for human-machine interactions. Here, we developed a novel approach for real-time con...

Dexterous Force Estimation during Finger Flexion and Extension Using Motor Unit Discharge Information.

With the development of advanced robotic hands, a reliable neural-machine interface is essential to take full advantage of the functional dexterity of...

Predicting Length of Stay for Cardiovascular Hospitalizations in the Intensive Care Unit: Machine Learning Approach.

Predicting Cardiovascular Length of stay based hospitalization at the time of patients' admitting to the coronary care unit (CCU) or (cardiac intensiv...

Comparison of Machine Learning Algorithms for Classifying Adverse-Event Related 30-Day Hospital Readmissions: Potential Implications for Patient Safety.

Studies in the last decade have focused on identifying patients at risk of readmission using predictive models, in an objective to decrease costs to t...

[Integration of production-university-research based on artificial intelligence for technological innovation and transformation in gastrointestinal surgery].

Medical artificial intelligence is a deeply integrated field of production-university-research. The collaborative innovation system of "industry, educ...

Evaluating Performance and Interpretability of Machine Learning Methods for Predicting Delirium in Gerontopsychiatric Patients.

Delirium is an acute mental disturbance that particularly occurs during hospital stay. Current clinical assessment instruments include the Delirium Ob...

Comparison of Unplanned 30-Day Readmission Prediction Models, Based on Hospital Warehouse and Demographic Data.

Anticipating unplanned hospital readmission episodes is a safety and medico-economic issue. We compared statistics (Logistic Regression) and machine l...

Neural Networks for Cause of Hospitalization and Final Cause of Death Extraction from Discharge Summaries.

Determining the cause of death of hospitalized patients with cardiovascular disease is of the utmost importance. This is usually recorded in free text...

Study on intelligent syndrome differentiation neural network model of stomachache in traditional Chinese medicine based on the real world.

Stomachache is not only disease name of Traditional Chinese medicine (TCM) but also the clinical symptom. It is a common and multiple diseases. TCM ha...