Pulmonology

Radiomics for differentiating adenocarcinoma and squamous cell carcinoma in non-small cell lung cancer beyond nodule morphology in chest CT.

Distinguishing between primary adenocarcinoma (AC) and squamous cell carcinoma (SCC) within non-small cell lung cancer (NSCLC) tumours holds significant management implications. We assessed the performance of radiomics-based models in distinguishing primary there is from SCC presenting as lung nodules on Computed Tomography (CT) scans. We studied individuals with histopathologically proven adenoca...

Development and validation of a web-based calculator for determining the risk of psychological distress based on machine learning algorithms: A cross-sectional study of 342 lung cancer patients.

PURPOSE: Early and accurate identification of the risk of psychological distress allows for timely intervention and improved prognosis. Current methods for predicting psychological distress among lung cancer patients using readily available data are limited. This study aimed to develop a robust machine learning (ML) model for determining the risk of psychological distress among lung cancer patient...

The Role of Machine Learning in the Detection of Cardiac Fibrosis in Electrocardiograms: Scoping Review.

BACKGROUND: Cardiovascular disease remains the leading cause of mortality worldwide. Cardiac fibrosis impacts the underlying pathophysiology of many c...

An appropriate DNA input for bisulfite conversion reveals LINE-1 and Alu hypermethylation in tissues and circulating cell-free DNA from cancers.

The autonomous and active Long-Interspersed Element-1 (LINE-1, L1) and the non-autonomous Alu retrotransposon elements, contributing to 30% of the hum...

Hyaluronic Acid is Associated with Severity and Prognosis in Patients with Community-Acquired Pneumonia.

PURPOSE: Hyaluronic acid (HA) is a novel inflammatory biomarker with a prognostic value for several infectious diseases. This study investigated the a...

Machine learning-based prediction of non-aeration linear alkylbenzene sulfonate mineralization in an oxygenic microalgal-bacteria biofilm.

Microalgal-bacteria biofilm shows great potential in low-cost greywater treatment. Accurately predicting treated greywater quality is of great signifi...

Feasibility of AI as first reader in the 4-IN-THE-LUNG-RUN lung cancer screening trial: impact on negative-misclassifications and clinical referral rate.

BACKGROUND: Lung cancer screening (LCS) with low-dose CT (LDCT) reduces lung-cancer-related mortality in high-risk individuals. AI can potentially red...

Optimizing adult-oriented artificial intelligence for pediatric chest radiographs by adjusting operating points.

The purpose of this study was to evaluate whether the optimal operating points of adult-oriented artificial intelligence (AI) software differ for pedi...

Multimodal Deep Learning Fusing Clinical and Radiomics Scores for Prediction of Early-Stage Lung Adenocarcinoma Lymph Node Metastasis.

RATIONALE AND OBJECTIVES: To develop and validate a multimodal deep learning (DL) model based on computed tomography (CT) images and clinical knowledg...

Multi-Energy Evaluation of Image Quality in Spectral CT Pulmonary Angiography Using Different Strength Deep Learning Spectral Reconstructions.

RATIONALE AND OBJECTIVES: To evaluate and compare image quality of different energy levels of virtual monochromatic images (VMIs) using standard versu...

Fluorescence excitation-emission matrix spectroscopy combined with machine learning for the classification of viruses for respiratory infections.

Significant efforts were currently being made worldwide to develop a tool capable of distinguishing between various harmful viruses through simple ana...

Multi-stain deep learning prediction model of treatment response in lupus nephritis based on renal histopathology.

The response of the kidney after induction treatment is one of the determinants of prognosis in lupus nephritis, but effective predictive tools are la...

Comparative investigation of lung adenocarcinoma and squamous cell carcinoma transcriptome to reveal potential candidate biomarkers: An explainable AI approach.

Patients with Non-Small Cell Lung Cancer (NSCLC) present a variety of clinical symptoms, such as dyspnea and chest pain, complicating accurate diagnos...

A novel interpretable deep learning model for diagnosis in emergency department dyspnoea patients based on complete data from an entire health care system.

BACKGROUND: Dyspnoea is one of the emergency department's (ED) most common and deadly chief complaints, but frequently misdiagnosed and mistreated. We...

Hope for the best prepare for the worst: acute kidney disease and catastrophic comorbidities (a case report).

It is evident that Acute Kidney Injury (AKI) is an independent risk factor for both the survival of patients and their kidneys. Here, we present a cas...

Noninvasive estimation of PaCO from volumetric capnography in animals with injured lungs: an Artificial Intelligence approach.

To investigate the feasibility of non-invasively estimating the arterial partial pressure of carbon dioxide (PaCO) using a computational Adaptive Neur...

Impact of a trace mineral injection at weaning on growth, behavior, and inflammatory, antioxidant, and immune responses of beef calves.

Two experiments evaluated the effects of an injectable trace mineral (ITM) solution at weaning on trace mineral (TM) status, inflammatory and antioxid...

How small is big enough? Big data-driven machine learning predictions for a full-scale wastewater treatment plant.

Wastewater treatment plants (WWTPs) generate vast amounts of water quality, operational, and biological data. The potential of these big data, particu...

AVP-GPT2: A Transformer-Powered Platform for De Novo Generation, Screening, and Explanation of Antiviral Peptides.

Human respiratory syncytial virus (RSV) remains a significant global health threat, particularly for vulnerable populations. Despite extensive researc...

Mask R-CNN assisted diagnosis of spinal tuberculosis.

The prevalence of spinal tuberculosis (ST) is particularly high in underdeveloped regions with inadequate medical conditions. This not only leads to m...