Hospital-Based Medicine

Multidimensional correlates of psychological stress: Insights from traditional statistical approaches and machine learning using a nationally representative Canadian sample.

Approximately one-fifth of Canadians report high levels of psychological stress. This is alarming, as chronic stress is associated with non-communicable diseases and premature mortality. In order to create effective interventions and public policy for stress reduction, factors associated with stress must be identified and understood. We analyzed data from the 2012 'Canadian Community Health Survey...

PROGNOSTIC ACCURACY OF MACHINE LEARNING MODELS FOR IN-HOSPITAL MORTALITY AMONG CHILDREN WITH PHOENIX SEPSIS ADMITTED TO THE PEDIATRIC INTENSIVE CARE UNIT.

Objective: The Phoenix sepsis criteria define sepsis in children with suspected or confirmed infection who have ≥2 in the Phoenix Sepsis Score. The adoption of the Phoenix sepsis criteria eliminated the Systemic Inflammatory Response Syndrome criteria from the definition of pediatric sepsis. The objective of this study is to derive and validate machine learning models predicting in-hospital mortal...

Deep Learning and Multidisciplinary Imaging in Pediatric Surgical Oncology: A Scoping Review.

BACKGROUND: Medical images play an important role in diagnosis and treatment of pediatric solid tumors. The field of radiology, pathology, and other i...

Predicting metabolic syndrome: Machine learning techniques for improved preventive medicine.

Metabolic syndrome (MetS) has a significant impact on health. MetS is the umbrella term for a group of interdependent metabolic threats that contribu...

Construction of a Multi-View Deep Learning Model for the Severity Classification of Acute Pancreatitis.

BACKGROUND: Acute pancreatitis (AP) is a prevalent pathological condition of abdomen characterized by sudden onset, high incidence and complex progres...

Identifying protected health information by transformers-based deep learning approach in Chinese medical text.

In the context of Chinese clinical texts, this paper aims to propose a deep learning algorithm based on Bidirectional Encoder Representation from Tra...

Leveraging artificial intelligence to promote COVID-19 appropriate behaviour in a healthcare institution from north India: A feasibility study.

Background & Objectives Non-pharmacological interventions (NPI) were crucial in curbing the initial COVID-19 pandemic waves, but compliance was diffic...

A Contrastive Pretrain Model with Prompt Tuning for Multi-center Medication Recommendation

Medication recommendation is one of the most critical health-related applications, which has attracted extensive research interest recently. Most ex...

Precision ICU Resource Planning: A Multimodal Model for Brain Surgery Outcomes

Although advances in brain surgery techniques have led to fewer postoperative complications requiring Intensive Care Unit (ICU) monitoring, the rout...

Continuous Patient Monitoring with AI: Real-Time Analysis of Video in Hospital Care Settings

This study introduces an AI-driven platform for continuous and passive patient monitoring in hospital settings, developed by LookDeep Health. Levera...

PT: A Plain Transformer is Good Hospital Readmission Predictor

Hospital readmission prediction is critical for clinical decision support, aiming to identify patients at risk of returning within 30 days post-disc...

RareAgents: Advancing Rare Disease Care through LLM-Empowered Multi-disciplinary Team

Rare diseases, despite their low individual incidence, collectively impact around 300 million people worldwide due to the vast number of diseases. T...

Evaluating the Efficacy of Vectocardiographic and ECG Parameters for Efficient Tertiary Cardiology Care Allocation Using Decision Tree Analysis

Use real word data to evaluate the performance of the electrocardiographic markers of GEH as features in a machine learning model with Standard ECG ...

Superhuman performance of a large language model on the reasoning tasks of a physician

A seminal paper published by Ledley and Lusted in 1959 introduced complex clinical diagnostic reasoning cases as the gold standard for the evaluatio...

Large Language Models for Medical Forecasting -- Foresight 2

Foresight 2 (FS2) is a large language model fine-tuned on hospital data for modelling patient timelines (GitHub 'removed for anon'). It can understa...

Harnessing Large Language Models for Mental Health: Opportunities, Challenges, and Ethical Considerations

Large Language Models (LLMs) are transforming mental health care by enhancing accessibility, personalization, and efficiency in therapeutic interven...

From Intention To Implementation: Automating Biomedical Research via LLMs

Conventional biomedical research is increasingly labor-intensive due to the exponential growth of scientific literature and datasets. Artificial int...

CSSDH: An Ontology for Social Determinants of Health to Operational Continuity of Care Data Interoperability

The rise of digital platforms has led to an increasing reliance on technology-driven, home-based healthcare solutions, enabling individuals to monit...

Assisted morbidity coding: the SISCO.web use case for identifying the main diagnosis in Hospital Discharge Records

Coding morbidity data using international standard diagnostic classifications is increasingly important and still challenging. Clinical coders and p...

Utilizing Machine Learning Models to Predict Acute Kidney Injury in Septic Patients from MIMIC-III Database

Sepsis is a severe condition that causes the body to respond incorrectly to an infection. This reaction can subsequently cause organ failure, a majo...