Latest AI and machine learning research in pneumonia for healthcare professionals.
BackgroundBody composition strongly influences clinical outcomes in older adults, yet body mass index (BMI) lacks discriminatory power, and standard tools such as bioelectrical impedance analysis (BIA), dual-energy X-ray absorptiometry are not routinely accessible. Deep learning enables scalable, opportunistic assessment of body composition from chest radiographs (CXRs), one of the most widely ava...
Deep visual proteomics (DVP) is an emerging approach for cell type-specific and spatially resolved proteomics. However, its broad adoption has been constrained by the lack of an open-source end-to-end workflow in a community-driven ecosystem. Here, we introduce openDVP, an experimental and computational framework for simplifying and democratizing DVP. OpenDVP integrates open-source software for im...
Background: Pneumonia remains a leading cause of morbidity and mortality among children worldwide, emphasizing the need for accurate and efficient dia...
Despite over 13 billion SARS-CoV-2 vaccine doses administered globally, persistent post-vaccination symptoms, termed post-COVID-19 vaccine syndrome (P...
With the rapid advancement of artificial intelligence (AI) and machine learning (ML) technologies, their applications in the medical field have expand...
OBJECTIVE: Half of all adult emergency department (ED) visits with a complaint of dyspnea involve acute heart failure (AHF), exacerbation of chronic o...
Neural networks often excel in short-horizon tasks, but their long-term reliability is less assured. We demonstrate that even a minimal architecture, ...
Klebsiella pneumoniae (K. pneumoniae) has become a serious global health concern due to its rising virulence and antibiotic resistance. As one of the ...
BACKGROUND AND OBJECTIVE: Pneumonia is the leading cause of hospitalisation and mortality among children under five, particularly in low-resource sett...
Tuberculosis (TB) remains a significant global public health threat. Achieving the 2035 target for TB elimination requires interrupting its community ...
Recent works have revisited the infamous task ``Name That Dataset'', demonstrating that non-medical datasets contain underlying biases and that the ...
Recent work has revisited the infamous task Name that dataset and established that in non-medical datasets, there is an underlying bias and achieved...
Despite significant advancements in adapting Large Language Models (LLMs) for radiology report generation (RRG), clinical adoption remains challengi...
Plain X-ray is one of the most common image modalities for clinical diagnosis (e.g. bone fracture, pneumonia, cancer screening, etc.). X-ray image s...
There is a global need for BioImage Analysis (BIA) as advances in life sciences increasingly rely on cutting-edge imaging systems that have dramatic...
Machine learning methods are increasingly applied to analyze health-related public discourse based on large-scale data, but questions remain regardi...
COVID-19 is a severe and acute viral disease that can cause symptoms consistent with pneumonia in which inflammation is caused in the alveolous regi...
Vaccine infodemics, driven by misinformation, disinformation, and inauthentic online behaviours, pose significant threats to global public health. T...
Radiology report generation represents a significant application within medical AI, and has achieved impressive results. Concurrently, large languag...
The global demand for radiologists is increasing rapidly due to a growing reliance on medical imaging services, while the supply of radiologists is ...