A5068469075- Advanced MRI Techniques and Applications
- Advanced Neuroimaging Techniques and Applications
- Cancer Genomics and Diagnostics
- Fetal and Pediatric Neurological Disorders
- Bioinformatics and Genomic Networks
- Natural Language Processing Techniques
- Radiomics and Machine Learning in Medical Imaging
- Machine Learning in Healthcare
- Single-cell and spatial transcriptomics
- Medical Imaging Techniques and Applications
- Genetics, Bioinformatics, and Biomedical Research
- Protein Degradation and Inhibitors
- Multiple Myeloma Research and Treatments
- Advanced Image Processing Techniques
- Advanced Vision and Imaging
- Scientific Computing and Data Management
- Molecular Biology Techniques and Applications
- Computational Drug Discovery Methods
- Prostate Cancer Treatment and Research
- Image and Signal Denoising Methods
- Artificial Intelligence in Healthcare
- Cancer Immunotherapy and Biomarkers
- NMR spectroscopy and applications
- Lung Cancer Treatments and Mutations
- Health and Medical Research Impacts
Sage Bionetworks
2016-2025
École Polytechnique Fédérale de Lausanne
2019-2024
University of Glasgow
2024
Athinoula A. Martinos Center for Biomedical Imaging
2023
Arvinas (United States)
2023
Siemens (Switzerland)
2022
Centre d'Imagerie BioMedicale
2020-2021
University of Lausanne
2020-2021
Signal Processing (United States)
2021
Cornell University
2020
The AACR Project GENIE is an international data-sharing consortium focused on generating evidence base for precision cancer medicine by integrating clinical-grade genomic data with clinical outcome tens of thousands patients treated at multiple institutions worldwide. In conjunction the first public release from approximately 19,000 samples, we describe goals, structure, and standards report conclusions high-level analysis initial phase data. We also provide examples utility data, such as...
Abstract International cancer registries make real-world genomic and clinical data available, but their joint analysis remains a challenge. AACR Project GENIE, an international registry collecting from 19 centers, makes >130,000 patients publicly available through the cBioPortal for Cancer Genomics (https://genie.cbioportal.org). For 25,000 patients, additional longitudinal data, including treatment outcome are being collected by GENIE Biopharma Collaborative using PRISSMM curation...
<h3>Importance</h3> Mammography screening currently relies on subjective human interpretation. Artificial intelligence (AI) advances could be used to increase mammography accuracy by reducing missed cancers and false positives. <h3>Objective</h3> To evaluate whether AI can overcome interpretation limitations with a rigorous, unbiased evaluation of machine learning algorithms. <h3>Design, Setting, Participants</h3> In this diagnostic study conducted between September 2016 November 2017, an...
Abstract The effectiveness of most cancer targeted therapies is short-lived. Tumors often develop resistance that might be overcome with drug combinations. However, the number possible combinations vast, necessitating data-driven approaches to find optimal patient-specific treatments. Here we report AstraZeneca’s large combination dataset, consisting 11,576 experiments from 910 across 85 molecularly characterized cell lines, and results a DREAM Challenge evaluate computational strategies for...
The BraTS 2021 challenge celebrates its 10th anniversary and is jointly organized by the Radiological Society of North America (RSNA), American Neuroradiology (ASNR), Medical Image Computing Computer Assisted Interventions (MICCAI) society. Since inception, has been focusing on being a common benchmarking venue for brain glioma segmentation algorithms, with well-curated multi-institutional multi-parametric magnetic resonance imaging (mpMRI) data. Gliomas are most primary malignancies central...
White matter bundle segmentation using diffusion MRI fiber tractography has become the method of choice to identify white pathways in vivo human brains. However, like other analyses complex data, there is considerable variability protocols and techniques. This can result different reconstructions same intended pathways, which directly affects results, quantification, interpretation. In this study, we aim evaluate quantify that arises from for segmentation. Through an open call users...
Identification of pregnancies at risk preterm birth (PTB), the leading cause newborn deaths, remains challenging given syndromic nature disease. We report a longitudinal multi-omics study coupled with DREAM challenge to develop predictive models PTB. The findings indicate that whole-blood gene expression predicts ultrasound-based gestational ages in normal and complicated (r = 0.83) and, using data collected before 37 weeks gestation, also delivery date both 0.86) those spontaneous 0.75)....
The American Association for Cancer Research (AACR) Project Genomics Evidence Neoplasia Information Exchange (GENIE) is an international pan-cancer registry with the goal to inform cancer research and clinical care worldwide. Founded in late 2015, milestone GENIE 9.1-public release contains data from >110,000 tumors >100,000 people treated at 19 centers United States, Canada, Kingdom, France, Netherlands, Spain. Here, we demonstrate use of these real-world data, harmonized through a...
Abstract: Although activation of brain catecholaminergic systems has been implicated in the cerebrovascular and metabolic changes during subarachnoid hemorrhage, cerebral ischemia, cortical ablation, freeze lesions, little is known response regional catecholamine to traumatic injury. The present study was designed characterize temporal concentrations norepinephrine (NE), dopamine (DA), epinephrine (E) discrete regions following experimental fluid‐percussion injury rats. Anesthetized rats...
The recent advent of CRISPR and other molecular tools enabled the reconstruction cell lineages based on induced DNA mutations promises to solve ones more complex organisms. To date, no lineage algorithms have been rigorously examined for their performance robustness across dataset types number cells. benchmark such methods, we decided organize a DREAM challenge using in vitro experimental intMEMOIR recordings silico data C. elegans tree about 1,000 cells Mus musculus 10,000 Some 22...
Limitations in the accuracy of brain pathways reconstructed by diffusion MRI (dMRI) tractography have received considerable attention. While technical advances spearheaded Human Connectome Project (HCP) led to significant improvements dMRI data quality, it remains unclear how these should be analyzed maximize accuracy. Over a period two years, we engaged community IronTract Challenge, which aims answer this question leveraging unique dataset. Macaque brains that both tracer injections and ex...
Predictive biomarkers of immune checkpoint inhibitor (ICI) efficacy are currently lacking for non-small cell lung cancer (NSCLC). Here, we describe the results from Anti-PD-1 Response Prediction DREAM Challenge, a crowdsourced initiative that enabled assessment predictive models by using data two randomized controlled clinical trials (RCTs) ICIs in first-line metastatic NSCLC.
Abstract Deep proteomics profiling using labeled LC-MS/MS experiments has been proven to be powerful study complex diseases. However, due the dynamic nature of discovery mass spectrometry, generated data contain a substantial fraction missing values. This poses great challenges for analyses, as many tools, especially those high dimensional data, cannot deal with values directly. To address this problem, NCI-CPTAC Proteogenomics DREAM Challenge was carried out develop effective imputation...
While the past decade has seen meaningful improvements in clinical outcomes for multiple myeloma patients, a subset of patients does not benefit from current therapeutics unclear reasons. Many gene expression-based models risk have been developed, but each model uses different combination genes and often involves assaying many making them difficult to implement. We organized Multiple Myeloma DREAM Challenge, crowdsourced effort develop rapid progression newly diagnosed benchmark these...
Abstract We evaluate deconvolution methods, which infer levels of immune infiltration from bulk expression tumor samples, through a community-wide DREAM Challenge. assess six published and 22 community-contributed methods using in vitro silico transcriptional profiles admixed cancer healthy cells. Several predict most cell types well, though they either were not trained to all functional CD8+ T states or do so with low accuracy. address this gap, including deep learning-based approach, whose...
PURPOSE The American Association for Cancer Research Project Genomics Evidence Neoplasia Information Exchange Biopharma Collaborative is a multi-institution effort to build pan-cancer repository of genomic and clinical data curated from the electronic health record. For research community be confident that extracted record text are reliable, transparency approach used ensure quality essential. MATERIALS AND METHODS Four institutions participating in AACR's GENIE created an observational...
Recovering the T2 distribution from multi-echo magnetic resonance (MR) signals is challenging but has high potential as it provides biomarkers characterizing tissue micro-structure, such myelin water fraction (MWF). In this work, we propose to combine machine learning and aspects of parametric (fitting MRI signal using biophysical models) non-parametric (model-free fitting signal) approaches relaxometry in brain by a multi-layer perceptron (MLP) for reconstruction. For training our network,...
The accurate identification and quantitation of RNA isoforms present in the cancer transcriptome is key for analyses ranging from inference impacts somatic variants to pathway analysis biomarker development subtype discovery. ICGC-TCGA DREAM Somatic Mutation Calling (SMC-RNA) challenge was a crowd-sourced effort benchmark methods isoform quantification fusion detection bulk sequencing (RNA-seq) data. It concluded 2018 with comparison 77 entries 65 on 51 synthetic tumors 32 cell lines...
Multi-component T2 relaxometry allows probing tissue microstructure by assessing compartment-specific relaxation times and water fractions, including the myelin fraction. Non-negative least squares (NNLS) with zero-order Tikhonov regularization is conventional method for estimating smooth distributions. Despite improved estimation provided this compared to non-regularized NNLS, solution still sensitive underlying noise weight. This especially relevant clinically achievable signal-to-noise...
<h3>Importance</h3> An automated, accurate method is needed for unbiased assessment quantifying accrual of joint space narrowing and erosions on radiographic images the hands wrists, feet clinical trials, monitoring damage over time, assisting rheumatologists with treatment decisions. Such a has potential to be directly integrated into electronic health records. <h3>Objectives</h3> To design implement an international crowdsourcing competition catalyze development machine learning methods...