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Cystic Fibrosis

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A Framework for Using Real-World Data and Health Outcomes Modeling to Evaluate Machine Learning-Based Risk Prediction Models.

Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research
OBJECTIVES: We propose a framework of health outcomes modeling with dynamic decision making and real-world data (RWD) to evaluate the potential utility of novel risk prediction models in clinical practice. Lung transplant (LTx) referral decisions in ...

Sweat Proteomics in Cystic Fibrosis: Discovering Companion Biomarkers for Precision Medicine and Therapeutic Development.

Cells
In clinical routine, the diagnosis of cystic fibrosis (CF) is still challenging regardless of international consensus on diagnosis guidelines and tests. For decades, the classical Gibson and Cooke test measuring sweat chloride concentration has been ...

Deep learning-based segmentation of the lung in MR-images acquired by a stack-of-spirals trajectory at ultra-short echo-times.

BMC medical imaging
BACKGROUND: Functional lung MRI techniques are usually associated with time-consuming post-processing, where manual lung segmentation represents the most cumbersome part. The aim of this study was to investigate whether deep learning-based segmentati...

Explainable Artificial Intelligence for Deep-Learning Based Classification of Cystic Fibrosis Lung Changes in MRI.

Studies in health technology and informatics
Algorithms increasing the transparence and explain ability of neural networks are gaining more popularity. Applying them to custom neural network architectures and complex medical problems remains challenging. In this work, several algorithms such as...

OrgaSegment: deep-learning based organoid segmentation to quantify CFTR dependent fluid secretion.

Communications biology
Epithelial ion and fluid transport studies in patient-derived organoids (PDOs) are increasingly being used for preclinical studies, drug development and precision medicine applications. Epithelial fluid transport properties in PDOs can be measured th...

Symptom phenotyping in people with cystic fibrosis during acute pulmonary exacerbations using machine-learning K-means clustering analysis.

Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society
INTRODUCTION: People with cystic fibrosis (PwCF) experience frequent symptoms associated with chronic lung disease. A complication of CF is a pulmonary exacerbation (PEx), which is often preceded by an increase in symptoms and a decline in lung funct...

Artificial intelligence-driven volumetric CT outcome score in cystic fibrosis: longitudinal and multicenter validation with/without modulators treatment.

European radiology
OBJECTIVES: Holistic segmentation of CT structural alterations with 3D deep learning has recently been described in cystic fibrosis (CF), allowing the measurement of normalized volumes of airway abnormalities (NOVAA-CT) as an automated quantitative o...

Protocol for functional screening of CFTR-targeted genetic therapies in patient-derived organoids using DETECTOR deep-learning-based analysis.

STAR protocols
Here, we present a protocol for the rapid functional screening of gene editing and addition strategies in patient-derived organoids using the deep-learning-based tool DETECTOR (detection of targeted editing of cystic fibrosis transmembrane conductanc...

AI-facilitated home monitoring for cystic fibrosis exacerbations across pediatric and adult populations.

Journal of cystic fibrosis : official journal of the European Cystic Fibrosis Society
BACKGROUND: AI-aided home stethoscopes offer the opportunity of continuous remote monitoring of cystic fibrosis (CF) patients, reducing the need for clinic visits.