Pulmonology

Pneumonia

Latest AI and machine learning research in pneumonia for healthcare professionals.

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How intra-source imbalanced datasets impact the performance of deep learning for COVID-19 diagnosis using chest X-ray images.

Over the past decade, the use of deep learning has been widely increasing in the medical image diagn...

Preclinical efficacy of a cell division protein candidate gonococcal vaccine identified by artificial intelligence.

Vaccines to curb the global spread of multidrug-resistant gonorrhea are urgently needed. Here, 26 va...

MultiCOVID: a multi modal deep learning approach for COVID-19 diagnosis.

The rapid spread of the severe acute respiratory syndrome coronavirus 2 led to a global overextensio...

Soundscapes and deep learning enable tracking biodiversity recovery in tropical forests.

Tropical forest recovery is fundamental to addressing the intertwined climate and biodiversity loss ...

Computer-aided diagnosis of chest X-ray for COVID-19 diagnosis in external validation study by radiologists with and without deep learning system.

To evaluate the diagnostic performance of our deep learning (DL) model of COVID-19 and investigate w...

A Deep Learning-Based Radiomic Classifier for Usual Interstitial Pneumonia.

BACKGROUND: Because chest CT scan has largely supplanted surgical lung biopsy for diagnosing most ca...

Update on ethical aspects in clinical research: Addressing concerns in the development of new AI tools in radiology.

The analysis of ethical aspects in clinical research has always been a challenge and has required co...

Automatic Quantification of COVID-19 Pulmonary Edema by Self-supervised Contrastive Learning.

We proposed a self-supervised machine learning method to automatically rate the severity of pulmonar...

A Novel Deep Learning Model for Medical Report Generation by Inter-Intra Information Calibration.

Automatic generation of medical reports can provide diagnostic assistance to doctors and reduce thei...

Distilling BlackBox to Interpretable Models for Efficient Transfer Learning.

Building generalizable AI models is one of the primary challenges in the healthcare domain. While ra...

scikit-matter : A Suite of Generalisable Machine Learning Methods Born out of Chemistry and Materials Science.

Easy-to-use libraries such as scikit-learn have accelerated the adoption and application of machine ...

Capturing Emerging Experiential Knowledge for Vaccination Guidelines Through Natural Language Processing: Proof-of-Concept Study.

BACKGROUND: Experience-based knowledge and value considerations of health professionals, citizens, a...

Testing the performance, adequacy, and applicability of an artificial intelligence model for pediatric pneumonia diagnosis.

BACKGROUND: Community-acquired Pneumonia (CAP) is a common childhood infectious disease. Deep learni...

Are there accurate and legitimate ways to machine-quantify predatoriness, or an urgent need for an automated online tool?

Yamada and Teixeira da Silva voiced valid concerns with the inadequacies of an online machine learni...

Combination of deep XLMS with deep learning reveals an ordered rearrangement and assembly of a major protein component of the vaccinia virion.

An outstanding problem in the understanding of poxvirus biology is the molecular structure of the ma...

Improving chest X-ray report generation by leveraging warm starting.

Automatically generating a report from a patient's Chest X-rays (CXRs) is a promising solution to re...

Learning from the machine: AI assistance is not an effective learning tool for resident education in chest x-ray interpretation.

OBJECTIVES: To assess whether a computer-aided detection (CADe) system could serve as a learning too...

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