Health Policy

From errors to excellence: the pre-analytical journey to improved quality in diagnostics. A scoping review.

This scoping review focuses on the evolution of pre-analytical errors (PAEs) in medical laboratories, a critical area with significant implications for patient care, healthcare costs, hospital length of stay, and operational efficiency. The Covidence Review tool was used to formulate the keywords, and then a comprehensive literature search was performed using several databases, importing the searc...

Development and validation of machine learning-based prediction model for central venous access device-related thrombosis in children.

BACKGROUND: Identifying independent risk factors and implementing high-quality assessment tools for early detection of patients at high risk of central venous access device (CVAD)-related thrombosis (CRT) plays a critical role in delivering timely preventive interventions and reducing the incidence of CRT. Approaches for identifying the risk of CRT in children have not been well-researched.

Optimized Adaboost Support Vector Machine-Based Encryption for Securing IoT-Cloud Healthcare Data.

The Internet of Things (IoT) connects various medical devices that enable remote monitoring, which can improve patient outcomes and help healthcare pr...

MaTableGPT: GPT-Based Table Data Extractor from Materials Science Literature.

Efficiently extracting data from tables in the scientific literature is pivotal for building large-scale databases. However, the tables reported in ma...

Low-cost and scalable machine learning model for identifying children and adolescents with poor oral health using survey data: An empirical study in Portugal.

This empirical study assessed the potential of developing a machine-learning model to identify children and adolescents with poor oral health using on...

Low-Cost Raman Spectroscopy Setup Combined with a Machine Learning Model.

The diagnosis of kidney diseases presents significant challenges, including the reliance on variable and unstable biomarkers and the necessity for com...

Exploring the potential of AI-driven food waste management strategies used in the hospitality industry for application in household settings.

This study explores the potential for adapting AI-driven food waste management strategies from the hospitality industry for application in household s...

Proximity-based solutions for optimizing autism spectrum disorder treatment: integrating clinical and process data for personalized care.

Autism Spectrum Disorder (ASD) affects millions of individuals worldwide, presenting challenges in social communication, repetitive behaviors, and sen...

A novel IoT-based approach using fractional fuzzy Hamacher aggregation operators application in revolutionizing healthcare selection.

In the current era, IoT-based healthcare solutions play a pivotal role in transforming the healthcare landscape by addressing key challenges and signi...

Time series forecasting of bed occupancy in mental health facilities in India using machine learning.

Machine learning models are vital for forecasting and optimizing healthcare parameters, especially in the context of rising mental health issues in In...

Addressing Missing Data Challenges in Geriatric Health Monitoring: A Study of Statistical and Machine Learning Imputation Methods.

In geriatric healthcare, missing data pose significant challenges, especially in systems used for frailty monitoring in elderly individuals. This stud...

Machine learning-driven prediction of medical expenses in triple-vessel PCI patients using feature selection.

Revascularization therapies, such as percutaneous coronary intervention (PCI) and coronary artery bypass grafting (CABG), alleviate symptoms and treat...

Digital Health and Genomics.

Digital health technologies have a crucial role in streamlining the use of genomics and facilitating access to genomic health care. There are efforts ...

Optimizing papermaking wastewater treatment by predicting effluent quality with node-level capsule graph neural networks.

Papermaking wastewater consists of a sizable amount of industrial wastewater; hence, real-time access to precise and trustworthy effluent indices is c...

The promise of AI in healthcare: transforming communication and decision-making for patients.

By addressing communication gaps, the integration of AI tools in healthcare has a greater ability to improve decision-making and to empower patients w...

GAN-based data reconstruction attacks in split learning.

Due to the distinctive distributed privacy-preserving architecture, split learning has found widespread application in scenarios where computational r...

Design of a Cost-Effective Ultrasound Force Sensor and Force Control System for Robotic Extra-Body Ultrasound Imaging.

Ultrasound imaging is widely valued for its safety, non-invasiveness, and real-time capabilities but is often limited by operator variability, affecti...

Integrating Artificial Intelligence in Medical Writing: Balancing Technological Innovation and Human Expertise, with Practical Applications in Lower Extremity Wounds Care.

Artificial Intelligence (AI) is revolutionizing medical writing by enhancing the efficiency and precision of healthcare communication and health resea...

Nutritional intelligence in the food system: Combining food, health, data and AI expertise.

Transformative change is needed across the food system to improve health and environmental outcomes. As food, nutrition, environmental and health data...

Is Artificial Intelligence the Next Co-Pilot for Primary Care in Diagnosing and Recommending Treatments for Depression?

Depression poses significant challenges to global healthcare systems and impacts the quality of life of individuals and their family members. Recent a...