Hospital-Based Medicine

Comment on "Utilizing Machine Learning Methods for Preoperative Prediction of Postsurgical Mortality and Intensive Care Unit Admission".

Reducing drug prescription errors and adverse drug events by application of a probabilistic, machine-learning based clinical decision support system in an inpatient setting.

BACKGROUND: Drug prescription errors are made, worldwide, on a daily basis, resulting in a high burd...

A Machine Learning-Based Triage Tool for Children With Acute Infection in a Low Resource Setting.

OBJECTIVES: To deploy machine learning tools (random forests) to develop a model that reliably predi...

Artificial intelligence in the diagnosis of cardiovascular disease.

Artificial intelligence (AI) is a field of computer science that aims to mimic human thought process...

[A Patient with Multiple Colorectal Liver Metastases for Whom Partial Splenic Embolization Contributed Extremely to Maintain Multidisciplinary Treatment].

After approximately 2.5 years of chemotherapy at the referred hospital, a 69-year-old man with doubl...

[Surgical Treatment for Extremely Elderly Patients Over 90 Years of Age with Colorectal Cancer].

We report 18 cases of colorectalcancer in patients aged over 90 years who received surgicaltreatment...

Predicting Inpatient Length of Stay After Brain Tumor Surgery: Developing Machine Learning Ensembles to Improve Predictive Performance.

BACKGROUND: Current outcomes prediction tools are largely based on and limited by regression methods...

Radiology-Pathology Correlation to Facilitate Peer Learning: An Overview Including Recent Artificial Intelligence Methods.

Correlation of pathology reports with radiology examinations has long been of interest to radiologis...

Word Embedding for French Natural Language in Healthcare: A Comparative Study.

Structuring raw medical documents with ontology mapping is now the next step for medical intelligenc...

Development of a Machine Learning Model Predicting an ICU Admission for Patients with Elective Surgery and Its Prospective Validation in Clinical Practice.

Frequent utilization of the Intensive Care Unit (ICU) is associated with higher costs and decreased ...

Identifying Diabetes in Clinical Notes in Hebrew: A Novel Text Classification Approach Based on Word Embedding.

NimbleMiner is a word embedding-based, language-agnostic natural language processing system for clin...

Renal Biopsy Recommendation Based on Text Understanding.

Due to various etiologies and pathogenesis of kidney diseases, an invasive procedure called renal bi...

Extracting Alcohol and Substance Abuse Status from Clinical Notes: The Added Value of Nursing Data.

We applied an open source natural language processing (NLP) system "NimbleMiner" to identify clinica...

Maxwell®: An Unsupervised Learning Approach for 5P Medicine.

In the 5P medicine (Personalized, Preventive, Participative, Predictive and Pluri-expert), the gener...

A Predictive Model for Determining Patients Not Requiring Prolonged Hospital Length of Stay After Elective Primary Total Hip Arthroplasty.

BACKGROUND: Hospital length of stay (LOS) is an important quality metric for total hip arthroplasty....

Artificial neural networks can predict trauma volume and acuity regardless of center size and geography: A multicenter study.

BACKGROUND: Trauma has long been considered unpredictable. Artificial neural networks (ANN) have rec...

Social Robots for Hospitalized Children.

BACKGROUND AND OBJECTIVES: Social robots (SRs) are increasingly present in medical and educational c...

Borderline Personality Features in Inpatients with Bipolar Disorder: Impact on Course and Machine Learning Model Use to Predict Rapid Readmission.

BACKGROUND: Earlier research indicated that nearly 20% of patients diagnosed with either bipolar dis...

Machine Learning-based Risk of Hospital Readmissions: Predicting Acute Readmissions within 30 Days of Discharge.

The objective of this study was to design and develop a 30-day risk of hospital readmission predicti...

Application of Machine Learning to Prediction of Surgical Site Infection.

Surgical site infections are an important health concern, particularly in low-resource areas, where ...

Sparse Embedding for Interpretable Hospital Admission Prediction.

This paper introduces a sparse embedding for electronic health record (EHR) data in order to predict...