Hospital-Based Medicine

Predictive Modeling of Comorbid Depression and Anxiety Symptoms Among Prospective University Students: A GIS-Based and Machine Learning Study.

Prospective university students are highly susceptible to mental health issues such as depression and anxiety. This study investigates the prevalence and risk factors associated with comorbid depression and anxiety suffering, integrating GIS and Machine Learning techniques to comprehensively understand their spatial distribution and predictive factors. Data from 1485 participants were collected vi...

Explainable deep learning model WAL-net for individualized assessment of potentially reversible malnutrition in patients with cancer: a multicenter cohort study.

Persistent malnutrition is associated with poor clinical outcomes in cancer. However, assessing its reversibility can be challenging. The present study aimed to utilize machine learning (ML) to predict reversible malnutrition (RM) in patients with cancer. A multicenter cohort study including hospitalized oncology patients. Malnutrition was diagnosed using an international consensus. RM was defined...

Value-Based Care in Orthopaedic Surgery: Outcomes, Costing, and Policy Updates.

➢ Strategic action following the measurement of outcomes in the context of cost allows for the reallocation of resources to value-adding interventions...

AI Predictive Model of Mortality and Intensive Care Unit Admission in the COVID-19 Pandemic: Retrospective Population Cohort Study of 12,000 Patients.

BACKGROUND: One of the main challenges with COVID-19 has been that although there are known factors associated with a worse prognosis, clinicians have...

Inflammatory, fibrotic and endothelial biomarker profiles in COVID-19 patients during and following hospitalization.

Survivors of severe COVID-19 often suffer from long-term respiratory issues, but the molecular drivers of this damage remain unclear. This study explo...

A Comprehensive Review of Terahertz Time-Domain Spectroscopy for Agri-Food Safety Detection: Enhanced Sensing Performance Through Multidisciplinary Technology Integration.

The development of efficient and accurate methods for detecting contamination in agri-foods is critical for ensuring food safety. Terahertz time-domai...

Advantages and effectiveness of AI three-dimensional reconstruction technology in the preoperative planning of total hip arthroplasty.

In order to explore the application effect of artificial intelligence (AI) 3D reconstruction technology in total hip arthroplasty (THA), this study in...

Application of Transformer Neural Networks for Data Cleaning in Emergency Room Logs: A Case Study from the Bordeaux University Hospital.

Emergency Rooms (ERs) are at the center of various optimization research due to the growing number of visits in recent decades. The accurate logging o...

Development and Validation of a Rule-Based Natural Language Processing Algorithm to Identify Falls in Inpatient Records of Older Adults: Retrospective Analysis.

BACKGROUND: In order to address fall underestimation by the International Classification of Diseases (ICD) in clinical settings, information from clin...

Strategies to decipher neuron identity from extracellular recordings in behaving non-human primates.

Identification of neuron type is critical when using extracellular recordings in awake, behaving animal subjects to understand computation in neural c...

Multi-task reinforcement learning and explainable AI-Driven platform for personalized planning and clinical decision support in orthodontic-orthognathic treatment.

This study presents a novel clinical decision support platform for orthodontic-orthognathic treatment that integrates multi-task reinforcement learnin...

Implementing Artificial Intelligence in Critical Care Medicine: a consensus of 22.

Artificial Intelligence (AI) is rapidly transforming the landscape of critical care, offering opportunities for enhanced diagnostic precision and pers...

Simulation of emitter discharge along drip laterals under drip fertigation system using artificial neural network.

Simulation of emitter discharge under a drip fertigation system is important for capturing the variation in water and nutrient distribution to crops. ...

Fairness of machine learning readmission predictions following open ventral hernia repair.

INTRODUCTION: Few models have predicted readmission following open ventral hernia repair (VHR), and none have assessed fairness. Fairness evaluation a...

Machine learning approaches for predicting heart failure readmissions.

PURPOSE: This study aims to develop and evaluate machine learning (ML) models to predict the likelihood of hospital readmission within 30 days after d...

Benchmarking Ensemble Models to Predict Prolonged Hospital Stay in Traumatic Brain Injury: A Single-Institution Study.

INTRODUCTION: Prolonged length of stay (PLOS) in hospitals is a critical metric representing quality and efficiency of care, especially for patients w...

Development of a Risk Prediction Model for Linezolid-Induced Thrombocytopenia Based on the Machine Learning Algorithm.

The research aimed to develop a validated model for predicting the risk of linezolid-induced thrombocytopenia (LIT). An XGBoost model and SelectFromMo...

How well does GPT-4 perform on an emergency medicine board exam? A comparative assessment.

BACKGROUND: Recent advancements in artificial intelligence have shown promise in enhancing diagnostic precision within healthcare sectors. In emergenc...

Correction: Use of machine learning to predict creativity among nurses: a multidisciplinary approach.

Development and external validation of machine learning models for the early prediction of malnutrition in critically ill patients: a prospective observational study.

BACKGROUND: Early detection of malnutrition in critically ill patients is crucial for timely intervention and improved clinical outcomes. However, ide...