COPD

The impact of clinical history on the predictive performance of machine learning and deep learning models for renal complications of diabetes.

BACKGROUND AND OBJECTIVE: Diabetes is a chronic disease characterised by a high risk of developing diabetic nephropathy. The early identification of individuals at heightened risk of such complications or their exacerbation can be crucial to set a correct course of treatment. However, there are currently no widely accepted predictive tools for this task and, additionally, most of these models rely...

A Weakly Supervised Transformer to Support Rare Disease Diagnosis from Electronic Health Records: Methods and Applications in Rare Pulmonary Disease

Rare diseases affect an estimated 300-400 million people worldwide, yet individual conditions often remain poorly characterized and difficult to diagnose due to their low prevalence and limited clinician familiarity. While computational phenotyping algorithms show promise for automating rare disease detection, their development is hindered by the scarcity of labeled data and biases in existing l...

Machine Learning-Driven Multi-Emission Fluorescence Array for Simultaneous Size Discrimination and Quantification of Gold Nanoparticles.

Gold nanoparticles (AuNPs) exhibit size-dependent environmental behaviors and bioaccumulation risks, necessitating precise characterization of their h...

Diagnostic tools in respiratory medicine (Review).

Recent advancements in diagnostic technologies have significantly transformed the landscape of respiratory medicine, aiming for early detection, impro...

The machine learning prediction model of non-alcoholic fatty liver; the role of hydrogen and methane breath tests.

Nonalcoholic fatty liver disease (NAFLD) is now the leading cause of global chronic liver disease, affecting approximately 32.4% of the population in ...

Prediction of Insulin Resistance in Nondiabetic Population Using LightGBM and Cohort Validation of Its Clinical Value: Cross-Sectional and Retrospective Cohort Study.

BACKGROUND: Insulin resistance (IR), a precursor to type 2 diabetes and a major risk factor for various chronic diseases, is becoming increasingly pre...

Ground Reaction Force Estimation via Time-aware Knowledge Distillation

Human gait analysis with wearable sensors has been widely used in various applications, such as daily life healthcare, rehabilitation, physical ther...

Exploring nanoparticles in lungs under COPD conditions for nanospray drug flow and deposition: CFD simulations and AI predictions.

Chronic obstructive pulmonary disease (COPD) plays a heavy burden on individuals and the social health system, not only causing direct medical costs b...

Whole Brain 3D T1 Mapping in Multiple Sclerosis Using Standard Clinical Images Compared to MP2RAGE and MR Fingerprinting.

Quantitative T1 and T2 mapping is a useful tool to assess properties of healthy and diseased tissues. However, clinical diagnostic imaging remains dom...

Comparing efficiency of an attention-based deep learning network with contemporary radiological workflow for pulmonary embolism detection on CTPA: A retrospective study.

RATIONAL AND OBJECTIVES: Pulmonary embolism (PE) is the third most fatal cardiovascular disease in the United States. Currently, Computed Tomography P...

Transforming pulmonary health care: the role of artificial intelligence in diagnosis and treatment.

INTRODUCTION: Respiratory diseases like pneumonia, asthma, and COPD are major global health concerns, significantly impacting morbidity and mortality ...

DeepFuse: A multi-rater fusion and refinement network for computing silver-standard annotations.

Achieving a reliable and accurate biomedical image segmentation is a long-standing problem. In order to train or adapt the segmentation methods or mea...

Breaking the Gold Standard: Extracting Forgotten Data under Exact Unlearning in Large Language Models

Large language models are typically trained on datasets collected from the web, which may inadvertently contain harmful or sensitive personal inform...

Multipath cycleGAN for harmonization of paired and unpaired low-dose lung computed tomography reconstruction kernels

Reconstruction kernels in computed tomography (CT) affect spatial resolution and noise characteristics, introducing systematic variability in quanti...

A robust chronic obstructive pulmonary disease classification model using dragonfly optimized kernel extreme learning machine.

Chronic obstructive pulmonary disease (COPD) is considered to be one of the most commonly occurring respiratory disorders and is proliferating at an e...

Lost in the Haystack: Smaller Needles are More Difficult for LLMs to Find

Large language models (LLMs) face significant challenges with needle-in-a-haystack tasks, where relevant information ("the needle") must be drawn fr...

Open and Sustainable AI: challenges, opportunities and the road ahead in the life sciences

Artificial intelligence (AI) has recently seen transformative breakthroughs in the life sciences, expanding possibilities for researchers to interpr...

Machine learning prediction model with shap interpretation for chronic bronchitis risk assessment based on heavy metal exposure: a nationally representative study.

BACKGROUND: Chronic bronchitis (CB), as a core precursor of Chronic Obstructive Pulmonary Disease (COPD), is crucial for global disease burden prevent...

Integrating bioinformatics and machine learning to unravel shared mechanisms and biomarkers in chronic obstructive pulmonary disease and type 2 diabetes.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) and type 2 diabetes mellitus (T2DM) are on the rise. While there is evidence of a link betwee...

Assessing the Quality of AI-Generated Clinical Notes: A Validated Evaluation of a Large Language Model Scribe

In medical practices across the United States, physicians have begun implementing generative artificial intelligence (AI) tools to perform the funct...