Latest AI and machine learning research in pneumonia for healthcare professionals.
Medical imaging plays a crucial role in clinical diagnosis, however, deep learning models often struggle with imbalanced datasets, which has a negative impact on the accuracy and robustness of pneumonia image classification. This study proposes a deep learning based diagnostic system for pneumonia detection using chest X-ray images. Using the pneumonia MNIST dataset, including pediatric lung image...
Artificial intelligence (AI) is increasingly utilized in the medical field, primarily for diagnostic purposes. Although AI has demonstrated efficacy in pneumothorax detection using chest X-rays (CXR), it has yet to be applied for decision-making regarding subsequent treatment. This study aims to develop and evaluate an AI-based system capable of predicting the necessity of chest tube drainage (CTD...
Introduction. Misinformation is a barrier to immunization. The objective was to describe and categorize vaccine-related myths reported by healthcare p...
Bimodality-the coexistence of two peaks in trait distributions-is common in natural ecosystems. In microbiomes, bimodality of species abundances is kn...
Methane production from wastewater sludge via anaerobic digestion is a complex process and a disturbance in any one of the microbial stages can lead t...
BACKGROUND: The growing use of artificial intelligence (AI) chatbots for seeking health-related information is concerning, as they were not originally...
The global wine market faces persistent threats from counterfeiting, particularly for high-value segments like sparkling wines. Traditional authentica...
BACKGROUND: With the accelerating aging of the global population, muscle health issue occurs commonly as an age-related process in older people. The c...
BACKGROUND: To characterize temporal and geographic patterns of metabolic dysfunction-associated steatotic liver disease (MASLD) across Asia from 1990...
Antimicrobial resistance (AMR) is a major global health challenge that threatens the effective prevention and treatment of infections. It arises from ...
BACKGROUND: Plasma biomarkers have emerged as robust indicators of Alzheimer's disease (AD) pathology, offering accessible tools for staging and strat...
Klebsiella oxytoca is a clinically significant opportunistic bacterium that contributes to global morbidity and mortality. Despite its clinical releva...
BACKGROUND: Efficient community-based screening for individuals at high risk of mortality is a major public health challenge. While many predictors ha...
OBJECTIVES: To describe the structured process of threshold optimisation for a commercially available multiclass chest X-ray (CXR) deep learning model...
Systemic barriers, including language, navigation complexity, and long specialist wait-times, result in the under-utilization of mental health service...
INTRODUCTION: Tuberculosis (TB), a leading infectious cause of death, remains a global health challenge. Imaging is central to diagnosis and screening...
INTRODUCTION: High costs of screening and diagnostic tests remain a major barrier to timely tuberculosis (TB) identification in resource-limited setti...
BACKGROUND: Fascioliasis is a neglected infectious disease affecting agricultural communities worldwide, with the Peruvian Andes among the most severe...
PURPOSE OF REVIEW: The literature review is pertinent because diagnosing pediatric tuberculosis (PdTB) remains quite challenging, especially in areas ...
OBJECTIVES: Incomplete or incorrect causal theories are a key source of bias in machine learning (ML) algorithms. Community-engaged methodologies prov...