Publications associées à Improving the efficiency of identifying malignant pulmonary nodules before surgery via a combination of artificial intelligence CT image recognition and serum autoantibodies

Publications associées (37)

In an era of combinatorial immunotherapy: elucidating and targeting mechanisms of systemic immunosuppression in HPV16+ cervical cancer to improve therapeutic vaccine responses

Immunotherapy has revolutionized cancer treatment, yet many patients, including those with cervical cancers induced by high-risk human papillomaviruses such as HPV16, remain unresponsive due to immune evasion mechanisms. While the tumor microenvironment (T ...

EPFL2025

From Forest to Zoo: Great Ape Behavior Recognition with Chimpbehave

Jean-Marc Odobez

This paper addresses the significant challenge of recognizing behaviors in non-human primates, specifically focusing on chimpanzees. Automated behavior recognition is crucial for both conservation efforts and the advancement of behavioral research. However ...

SPRINGER2025

Functionalization of harmonic nanoparticles for drug release and multimodal imaging applications

Adrian Stefan Gheata

Cancer is among the leading causes of death worldwide, and as knowledge of the disease continues to grow there is an increasing interest towards precision medicine: more specifically towards the theranostics field, i.e the development of targeted molecular ...

EPFL2024

Deep learning approach for identification of H II regions during reionization in 21-cm observations - II. Foreground contamination

Jean-Paul Richard Kneib, Emma Elizabeth Tolley, Michele Bianco, Tianyue Chen

The upcoming Square Kilometre Array Observatory will produce images of neutral hydrogen distribution during the epoch of reionization by observing the corresponding 21-cm signal. However, the 21-cm signal will be subject to instrumental limitations such as ...

Oxford Univ Press2024

NMR and MS reveal characteristic metabolome atlas and optimize esophageal squamous cell carcinoma early detection

Lijing Xin

Metabolic changes precede malignant histology. However, it remains unclear whether detectable characteristic metabolome exists in esophageal squamous cell carcinoma (ESCC) tissues and biofluids for early diagnosis. Here, we conduct NMR- and MS-based metabo ...

Nature Portfolio2024

GANDALF: Graph-based transformer and Data Augmentation Active Learning Framework with interpretable features for multi-label chest Xray classification

Seyedbehzad Bozorgtabar

Informative sample selection in an active learning (AL) setting helps a machine learning system attain optimum performance with minimum labeled samples, thus reducing annotation costs and boosting performance of computer-aided diagnosis systems in the pres ...

Elsevier2024

The role of computational methods in cardiovascular medicine: a narrative review

Alfio Quarteroni, Luca Dede', Christian Vergara, Stefano Pagani

Background and Objective: Computational models of the cardiovascular system allow for a detailed and quantitative investigation of both physiological and pathological conditions, thanks to their ability to combine clinical-possibly patient-specific-data wi ...

Ame Publishing Company2024

Deep learning predicts malignancy and metastasis of solid pulmonary nodules from CT scans

Jiancheng Yang

In the clinic, it is difficult to distinguish the malignancy and aggressiveness of solid pulmonary nodules (PNs). Incorrect assessments may lead to delayed diagnosis and an increased risk of complications. We developed and validated a deep learning-based m ...

FRONTIERS MEDIA SA2023

Deep learning diagnostic and severity-stratification for interstitial lung diseases and chronic obstructive pulmonary disease in digital lung auscultations and ultrasonography: clinical protocol for an observational case-control study

Mary-Anne Hartley, Jonathan Dönz

BackgroundInterstitial lung diseases (ILD), such as idiopathic pulmonary fibrosis (IPF) and non-specific interstitial pneumonia (NSIP), and chronic obstructive pulmonary disease (COPD) are severe, progressive pulmonary disorders with a poor prognosis. Prom ...

BMC2023

Rapid low-cost hyperspectral imaging system for quantitative assessment of infantile hemangioma

Viktor Vorobev

Hemangioma, the predominant benign tumor occurring in infancy, exhibits a wide range of prognoses and associated outcomes. The accurate determination of prognosis through noninvasive imaging modalities holds essential importance in enabling effective perso ...

Wiley-V C H Verlag Gmbh2023

Prognostic impact of deep learning-based quantification in clinical stage 0-I lung adenocarcinoma

Li Zhang, Jiancheng Yang

Objectives To evaluate the performance of automatic deep learning (DL) algorithm for size, mass, and volume measurements in predicting prognosis of lung adenocarcinoma (LUAD) and compared with manual measurements. ...

SPRINGER2023

Automatic pathological speech assessment

Parvaneh Janbakhshi

Many pathologies cause impairments in the speech production mechanism resulting in reduced speech intelligibility and communicative ability. To assist the clinical diagnosis, treatment and management of speech disorders, automatic pathological speech asses ...

EPFL2022

Characterization of Cyclo His-Pro for the prevention and treatment of liver disease and muscular dystrophy

Alessia De Masi

The natural compound Cyclo Histidine-Proline (CHP) was initially discovered in the brain, but thereafter evaluated in the context of diabetes because of its hypoglycemic action. The pharmacokinetics and the toxicological profile of CHP showed it can be dos ...

EPFL2023

Colon tumour cell death causes mTOR dependence by paracrine P2X4 stimulation

Andrea Ablasser

Solid cancers exhibit a dynamic balance between cell death and proliferation ensuring continuous tumour maintenance and growth(1,2). Increasing evidence links enhanced cancer cell apoptosis to paracrine activation of cells in the tumour microenvironment in ...

NATURE PORTFOLIO2022

Perturbation theory models for LSST-era galaxy clustering: Tests with subpercent mock catalog measurements in Fourier and configuration space

Jonathan Andrew Blazek

We analyze the clustering of galaxies using the z = 1.006 snapshot of the CosmoDC2 simulation, a high-fidelity synthetic galaxy catalog designed to validate analysis methods for the Vera C. Rubin Observatory Legacy Survey of Space and Time (LSST). We prese ...

American Physical Society2022

Monitoring of Protein and pH Levels in Human Biofluids using FD-SOI Silicon Nanowire Arrays

Luca Capua

Medical research and technological advancements are heading towards tailored healthcare approaches that prioritize individual needs, allowing for more accurate diagnoses, more effective treatments, and better patient outcomes overall. One such approach is ...

EPFL2023

Self-Supervised Learning for Patient Stratification and Survival Analysis in Computational Pathology: An Application to Colorectal Cancer

Christian Robert Abbet

Over the years, clinical institutes accumulated large amounts of digital slides from resected tissue specimens. These digital images, called whole slide images (WSIs), are high-resolution tissue snapshots that depict the complex interaction of cells at the ...

EPFL2023

OptTTA: Learnable Test-Time Augmentation for Source-Free Medical Image Segmentation Under Domain Shift

Jean-Philippe Thiran, Seyedbehzad Bozorgtabar, Guillaume Marc Georges Vray, Devavrat Tomar

As distribution shifts are inescapable in realistic clinical scenarios due to inconsistencies in imaging protocols, scanner vendors, and across different centers, well-trained deep models incur a domain generalization problem in unseen environments. Despit ...

PMLR2022

Roles of Clinical Features and Chest CT in Predicting the Outcomes of Hospitalized Patients with COVID-19 Developing AKI

Ali Falsafi

This research aimed to evaluate the clinical features and computed tomography (CT) scans associated with poor outcomes in COVID-19 patients with acute kidney injury (AKI). A total of 351 COVID-19 patients (100 AKI, 251 non-AKI) hospitalized at Imam Hossein ...

IRANIAN SOC NEPHROLGY2023

Coupling remote sensing and particle tracking to estimate trajectories in large water bodies

Tamar Kohn, Alfred Johny Wüest, Damien Bouffard, Chaojie Li

Propelled by the rapid development of equipment, technology and computational power, the monitoring and simulation of the hydrodynamics in lakes have steadily advanced. In contrast, water quality simulations are more difficult to implement, due to the diff ...

Elsevier2022