Hospital-Based Medicine

Malnutrition risk assessment using a machine learning-based screening tool: A multicentre retrospective cohort.

BACKGROUND: Malnutrition is associated with increased morbidity, mortality, and healthcare costs. Early detection is important for timely intervention. This paper assesses the ability of a machine learning screening tool (MUST-Plus) implemented in registered dietitian (RD) workflow to identify malnourished patients early in the hospital stay and to improve the diagnosis and documentation rate of m...

Understanding metric-related pitfalls in image analysis validation.

Validation metrics are key for tracking scientific progress and bridging the current chasm between artificial intelligence research and its translation into practice. However, increasing evidence shows that, particularly in image analysis, metrics are often chosen inadequately. Although taking into account the individual strengths, weaknesses and limitations of validation metrics is a critical pre...

Acute Kidney Injury in Acute Myocardial Infarction and Its Outcome at 3 and 6 Months.

Epidemiological data on the prevalence of acute kidney injury (AKI) in acute coronary syndrome are sparse, with most studies having been conducted ret...

A comparative study of explainable ensemble learning and logistic regression for predicting in-hospital mortality in the emergency department.

This study addresses the challenges associated with emergency department (ED) overcrowding and emphasizes the need for efficient risk stratification t...

Minimally invasive sacrocolpopexy: efficiency of robotic assistance compared to standard laparoscopy.

Minimally invasive abdominal sacrocolpopexy (SC) is the treatment of choice for symptomatic, high-grade, apical or multi-compartmental pelvic organ pr...

Perspectives on Preparedness for Chemical, Biological, Radiological, and Nuclear Threats in the Middle East and North Africa Region: Application of Artificial Intelligence Techniques.

Over the past 3 decades, the diversity of ethnic, religious, and political backgrounds worldwide, particularly in countries of the Middle East and Nor...

Robotic surgery for bowel endometriosis: a multidisciplinary management of a complex entity.

BACKGROUND: Bowel endometriosis impacts quality of life. Treatment requires complex surgical procedures with associated morbidity. Precision approach ...

The Intersections of COVID-19, HIV, and Race/Ethnicity: Machine Learning Methods to Identify and Model Risk Factors for Severe COVID-19 in a Large U.S. National Dataset.

We investigate risk factors for severe COVID-19 in persons living with HIV (PWH), including among racialized PWH, using the U.S. population-sampled Na...

Use of Temporally Validated Machine Learning Models To Predict Outcomes of Percutaneous Nephrolithotomy Using Data from the British Association of Urological Surgeons Percutaneous Nephrolithotomy Audit.

BACKGROUND AND OBJECTIVE: Machine learning (ML) is a subset of artificial intelligence that uses data to build algorithms to predict specific outcomes...

Methodology for Good Machine Learning with Multi-Omics Data.

In 2020, Novartis Pharmaceuticals Corporation and the U.S. Food and Drug Administration (FDA) started a 4-year scientific collaboration to approach co...

Mixtures Recomposition by Neural Nets: A Multidisciplinary Overview.

Artificial Neural Networks (ANNs) are transforming how we understand chemical mixtures, providing an expressive view of the chemical space and multisc...

Special Issue-Biosensors and Neuroscience: Is Biosensors Engineering Ready to Embrace Design Principles from Neuroscience?

In partnership with the Air Force Office of Scientific Research (AFOSR), the National Science Foundation's (NSF) Emerging Frontiers and Multidisciplin...

Validate robot-assisted total laparoscopic hysterectomy with four equally-spaced ports without an assistant port.

To evaluate the usefulness of robot-assisted total laparoscopic hysterectomy with four equally-spaced ports (RA-TLH/4e) without an assistant port. In ...

Application of multi-gene genetic programming to the prognosis prediction of COVID-19 using routine hematological variables.

Identifying patients who may develop severe COVID-19 has been of interest to clinical physicians since it facilitates personalized treatment and optim...

Artificial intelligence (AI)-it's the end of the tox as we know it (and I feel fine).

The rapid progress of AI impacts diverse scientific disciplines, including toxicology, and has the potential to transform chemical safety evaluation. ...

Multi-omics approaches to studying gastrointestinal microbiome in the context of precision medicine and machine learning.

The human gastrointestinal (gut) microbiome plays a critical role in maintaining host health and has been increasingly recognized as an important fact...

Comparing robotic with laparoscopic beyond total mesorectal excision for advanced rectal cancer-a propensity-matched analysis.

AIM: Robotic surgery is increasingly being used for rectal resection, with short-term benefits such as reduced hospital stay, faster bowel recovery an...

Risk factors and clinical significance of subcutaneous emphysema after robot-assisted laparoscopic rectal surgery: a single-center experience.

Subcutaneous emphysema (SE) is a complication of laparoscopic surgery, potentially resulting in severe respiratory failure. No reports to date have fo...

Building Prediction Models for 30-Day Readmissions Among ICU Patients Using Both Structured and Unstructured Data in Electronic Health Records.

ICU readmissions are associated with poor outcomes for patients and poor performance of hospitals. Patients who are readmitted have an increased risk ...

Evaluation of robot-assisted laparoscopic versus conventional laparoscopic hiatal hernia repair in children.

Laparoscopic approach is the gold standard for repairing hiatal hernia (HH). Robotic technology is now widely accepted, but it is rarely used in child...