Pneumonia

The sweet spot in protein design-Where deep learning meets first principles.

This Perspective explores recent methods and prospective ideas for developing hybrid AI-physics-based pipelines for protein and antibody de novo design. We argue that the highest-confidence candidates emerge where deep learning and first-principles models agree, a "sweet spot" that balances generative flexibility with thermodynamic realism. For example, although interface confidence scores such as...

Optimising Pharmacovigilance Efficiency with MLIT (Machine Learning for Intelligent Triage): A Tool for Statistical Safety Alerts.

BACKGROUND AND AIM: Pharmacovigilance is essential to ensuring patient safety by enabling timely identification of adverse reactions in increasingly complex and voluminous data. Routine quantitative signal detection methods generate statistical alerts for product-event pairs based on predefined criteria; however, most alerts do not warrant further investigation, creating inefficiencies and signifi...

Large language models in respiratory care: safety and clinical integration.

BACKGROUND: Large language models (LLMs) are rapidly entering respiratory medicine workflows. Their clinical role remains unclear. A central concern i...

Healthcare access inequalities in Quilombola rural and riverside communities in the Brazilian Amazon: Associations with social, organizational, and territorial factors.

BACKGROUND: Equitable access to healthcare services is a core principle of Brazil's Unified Health System and remains a persistent challenge in territ...

The Open Data Commons for Traumatic Brain Injury: An Interagency Community Platform for Pre-Clinical Data Management and Sharing.

The Open Data Commons for Traumatic Brain Injury (ODC-TBI.org) was launched in 2018 to support data sharing in pre-clinical TBI. As data science and a...

Beyond Accuracy: A Mixed-Methods Audit of Chain-of-Thought Failures in LLM-Based COVID-19 Vaccine Stance Detection.

This mixed-methods study assessed whether reasoning-enabled large language models (LLMs) can classify stances towards COVID-19 vaccination on X (forme...

Agentic AI-Assisted Coding Offers a Unique Opportunity to Instill Epistemic Grounding during Software Development.

The capabilities of AI-assisted coding are progressing at a breakneck speed. Chat-based vibe coding has evolved into fully fledged AI-assisted, agenti...

Modelling the impact of awareness campaigns on HPV transmission dynamics: a neural network-enhanced mathematical model.

HPV is the most common sexually transmitted infection; most sexually active individuals are exposed to HPV at some point in their lives, and the major...

Trust-Centered Design and Feasibility Evaluation of an AI-Enabled Conversational Health Tool for Sexual and Reproductive Health Among Rural Young Adults: Protocol for a Mixed Methods Study.

BACKGROUND: Young adults aged 18 to 25 years in rural communities face barriers to sexual and reproductive health (SRH) information, including clinici...

Large Language Models for Classifying Usual Interstitial Pneumonia from Radiology Reports: Native Reasoning Versus Structured Prompting.

Extracting disease labels from radiology reports is essential for developing deep learning-based diagnostic models and enabling large-scale retrospect...

Implementing AI-enabled chest X-ray for community-based integrated screening for tuberculosis, chronic respiratory diseases, and cardiovascular diseases in Nigeria.

BACKGROUND: Low- and middle-income countries face a growing dual burden of communicable and non-communicable diseases, while services remain verticall...

Theranostic innovation in infectious lung diseases: integrating biotechnology and nanotechnology for precision medicine.

INTRODUCTION: Introduction: Infectious lung diseases, including pneumonia, tuberculosis (TB), COVID-19, influenza, and emerging fungal infections, are...

Smartphone-Based Physical Performance and Multidimensional Determinants of Self-Reported Knee Pain in Community-Dwelling Older Adults: Cross-Sectional Machine Learning and Network Analysis Study.

BACKGROUND: Knee pain affects 22.9% of individuals aged 40 years and over globally and is associated with body function, activity, environmental, and ...

Predicting antifouling paint particle contamination based on 16S rRNA gene sequencing data using random forest-based machine learning.

Antifouling paints often contain biocides designed to inhibit biological growth, and antifouling paint particles (APPs) have been previously shown to ...

Diagnostic performance with sensitivity/specificity optimized computer-aided detection to detect common abnormalities in chest radiography.

PURPOSE: To evaluate how two fixed computer-aided detection (CAD) operating modes-sensitivity-optimized (SE-CAD) and specificity-optimized (SP-CAD)-af...

Subphenotypes of pneumonia defined by pulmonary histopathological features.

RATIONALE: Establishing subphenotypes of pneumonia based on host biology will be a step toward using host-directed therapies (to complement microbe-di...

Predicting Care Needs in Community-Dwelling Older Adults Using Explainable Machine Learning and a Multidimensional Approach Integrating Health, Social, and Environmental Factors: Cross-Sectional Study.

BACKGROUND: Rapid population aging and a worsening shortage of care workers necessitate the identification of older adults who require proactive inter...

Transposable elements in the era of data science EMBO course: a call for open, accessible, and collaborative TE resources.

This community letter represents a collective outcome from the EMBO Practical Course "Transposable Elements in the Era of Data Science" held at the Ro...

RETRACTION: Multithreshold Segmentation and Machine Learning Based Approach to Differentiate COVID-19 from Viral Pneumonia.

[This retracts the article DOI: 10.1155/2022/2728866.].

Development of a deep learning-based model for personal identification using postmortem CT and antemortem chest x-rays.

PURPOSE: To facilitate personal identification for mass disaster victims, we aimed to develop and evaluate a deep learning method for matching postmor...