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Alpha-1 Trailblazers

11/18/2024

During Alpha-1 Awareness Month, OSIC founding member CSL Behring shares three inspiring stories from the Alpha-1 Antitrypsin Deficiency community, one of which is a profile of OSIC’s research initiatives in this space.

World Orphan Drug Congress

10/24/2024

Executive Director Elizabeth Estes discussed OSIC’s progress in developing biomarkers for rare lung disease as a result of collaboration between academia, industry and philanthropy.

Vision Intelligence Assisted Lung Function Estimation Based on Transformer Encoder–Decoder Network With Invertible Modeling

10/22/2024

OSIC is mentioned in this research.

READ MORE ON IEEE XPLORE

In Non-IPF Fibrosing ILD, E-Lung Biomarkers are Associated with the Future Development of Progressive Pulmonary Fibrosis Independent of UIP Status on CT Scan

10/8/2024

Data from the OSIC Data Repository was used to conduct this research.

Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge

10/1/2024

Data from the OSIC Data Repository was used to conduct this research.

Metric learning guided sinogram denoising for cone beam CT enhancement

10/1/2024

Data from the OSIC Data Repository was used to conduct this research.

8th Annual IPF Summit

8/22/2024

Executive Director Elizabeth Estes shared insights on how robust clinical data curation, global normalization, and advanced data power can drive radical progress in drug development for fibrosing lung diseases.

Computed tomography machine learning classifier correlates with mortality in interstitial lung disease

7/1/2024

Data from the OSIC Data Repository was used to conduct this research.

Medical Image Segmentation using DUCK-Net

6/1/2024

Data from the OSIC Data Repository was used to conduct this research.

Utilization of Imaging and Clinical Data in Predicting Lung Capacity Progression in Patients with Fibrosis

6/1/2024

Data from the OSIC Data Repository was used to conduct this research.

Machine learning classifier is associated with mortality in interstitial lung disease: a retrospective validation study leveraging registry data

5/23/2024

Data from the OSIC Data Repository was used to conduct this research.

From pixels to prognosis: unlocking the potential of deep learning in fibrotic lung disease imaging analysis

5/23/2024

OSIC is mentioned in this research.

Multi-modal Machine Learning Classifier for Idiopathic Pulmonary Fibrosis Predicts Mortality in Interstitial Lung Diseases

5/21/2024

Data from the OSIC Data Repository was used to conduct this research.

ATS 2024 International Conference

5/21/2024

Dr. Kevin Brown and Dr. Simon Walsh discussed recent developments in machine learning algorithms using the OSIC Cloud Data Repository during this Industry Theater presentation.

Evaluating Radiomic-derived Features Across Different Image Convolution Kernels for Predicting IPF Patient Survival

5/20/2024

Data from the OSIC Data Repository was used to conduct this research.

Towards the adoption of quantitative computed tomography in the management of interstitial lung disease

4/17/2024

OSIC members discuss how quantitative CT software has huge potential to develop imaging biomarkers to improve the management of fibrosing ILDs, but optimizing their adoption will require technical and societal challenges to be addressed.

Enhanced Multimodal Timely Prediction of Pulmonary Fibrosis Progression with Uncertainty Estimation from Chest CT Images and Clinical Metadata

2/28/2024

Data from the OSIC Data Repository was used to conduct this research.

Lung Parenchyma Segmentation Based on U-Net Fused With Shape Stream

2/13/2024

Data from the OSIC Data Repository was used to conduct this research.

READ MORE ON IEEE XPLORE

Application of Neural-Controlled Differential Equations in Disease Progression Modeling Using Irregularly Sampled Multimodal Data

1/16/2024

Data from the OSIC Data Repository was used to conduct this research.

READ MORE ON IEEE XPLORE

Vision Intelligence Assisted Lung Function Estimation Based on Transformer Encoder–Decoder Network With Invertible Modeling

1/1/2024

OSIC is mentioned in this research.

READ MORE ON IEEE XPLORE

A Bayesian Neural Network-Based Method For The Extraction Of A Metabolite Corrected Arterial Input Function From Dynamic [11C]PBR28 PET

12/13/2023

Data from the OSIC Data Repository was used to conduct this research.

READ MORE ON IEEE XPLORE

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Alpha-1 Trailblazers

World Orphan Drug Congress

Vision Intelligence Assisted Lung Function Estimation Based on Transformer Encoder–Decoder Network With Invertible Modeling

In Non-IPF Fibrosing ILD, E-Lung Biomarkers are Associated with the Future Development of Progressive Pulmonary Fibrosis Independent of UIP Status on CT Scan

Hunting imaging biomarkers in pulmonary fibrosis: Benchmarks of the AIIB23 challenge

Metric learning guided sinogram denoising for cone beam CT enhancement

8th Annual IPF Summit

Computed tomography machine learning classifier correlates with mortality in interstitial lung disease

Medical Image Segmentation using DUCK-Net

Utilization of Imaging and Clinical Data in Predicting Lung Capacity Progression in Patients with Fibrosis

Machine learning classifier is associated with mortality in interstitial lung disease: a retrospective validation study leveraging registry data

From pixels to prognosis: unlocking the potential of deep learning in fibrotic lung disease imaging analysis

Multi-modal Machine Learning Classifier for Idiopathic Pulmonary Fibrosis Predicts Mortality in Interstitial Lung Diseases

ATS 2024 International Conference

Evaluating Radiomic-derived Features Across Different Image Convolution Kernels for Predicting IPF Patient Survival

Towards the adoption of quantitative computed tomography in the management of interstitial lung disease

A Machine Learning System to Indicate Diagnosis of Idiopathic Pulmonary Fibrosis Non-Invasively in Challenging Cases

Revolutionizing Pulmonary Diagnostics: A Narrative Review of Artificial Intelligence Applications in Lung Imaging

ASPPH 2024 Annual Meeting

Rare Disease Summit 2024

Enhanced Multimodal Timely Prediction of Pulmonary Fibrosis Progression with Uncertainty Estimation from Chest CT Images and Clinical Metadata

Lung Parenchyma Segmentation Based on U-Net Fused With Shape Stream

Application of Neural-Controlled Differential Equations in Disease Progression Modeling Using Irregularly Sampled Multimodal Data

Vision Intelligence Assisted Lung Function Estimation Based on Transformer Encoder–Decoder Network With Invertible Modeling

A Bayesian Neural Network-Based Method For The Extraction Of A Metabolite Corrected Arterial Input Function From Dynamic [11C]PBR28 PET

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