Hospital-Based Medicine

[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 double colon cancer and unresectable liver metastases(H3)sought consultation. A total of 8 liver metastases were deemed resectable; however, the disease was progressive. He received 2 courses of mFOLFOX6 plus Bmab before hepatectomy. Seven weeks after starting chemotherapy, Grade 4 thrombocytopenia occur...

[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 . Except for 2 patients who had StageⅣ colorectal cancer, all patients underwent R0 colorectal resection. The mean operation time, blood loss, and length of hospitalization were 167 min, 115 mL, and 23.5 days, respectively. Postoperative complications occurred in 15 patients(83%), of which the most...

[Computer instruments for the management of isolated pulmonary nodule. Detectability and prediction of malignancy].

Lung cancer remains the most common cause of cancer deaths in the world, but its mortality can be significantly reduced by diagnosis and early detecti...

[Actively promoting the research and development of artificial intelligence diagnosis and treatment of orbital disease].

Medical artificial intelligence (AI) promotes technological revolution and industrial transformation in the medical field, and the medical level of or...

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. Utilization of machine learning (ML) methods tha...

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 radiologists and helps to facilitate peer learning. Such cor...

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 intelligence. Deep learning models take as input mathematical...

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 availability for patients who urgently need it. Co...

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 clinical text classification. Previously, NimbleMiner ...

Renal Biopsy Recommendation Based on Text Understanding.

Due to various etiologies and pathogenesis of kidney diseases, an invasive procedure called renal biopsy may be needed to determine the specific type ...

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 clinical notes with mentions of alcohol and substance abu...

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

In the 5P medicine (Personalized, Preventive, Participative, Predictive and Pluri-expert), the general trend is to process data by displacing the bary...

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. Accurately predicting LOS is important to expecta...

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 recently shown the ability to predict admission volum...

Social Robots for Hospitalized Children.

BACKGROUND AND OBJECTIVES: Social robots (SRs) are increasingly present in medical and educational contexts, but their use in inpatient pediatric sett...

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 disorder (BD) or borderline personality disorder (BPD...

Monitoring of Patient Blanket Coverage using 3D Camera Data.

Nurses in a hospital are responsible for the monitoring and care of a large number of patients. Regularly checking if patients are sufficiently covere...

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 predictive model using machine learning techniques. The pr...

Application of Machine Learning to Prediction of Surgical Site Infection.

Surgical site infections are an important health concern, particularly in low-resource areas, where there is poor access to clinical facilities or tra...

Sparse Embedding for Interpretable Hospital Admission Prediction.

This paper introduces a sparse embedding for electronic health record (EHR) data in order to predict hospital admission. We use a k-sparse autoencoder...