A meta-learning approach for genomic survival analysis

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Background Rectal cancer segmentation in CT is crucial for timely diagnosis. Despite promising methods, challenges remain due to the rectum’s complex anatomy and the lack of a comprehensive annotated dataset. Methods A total of 33,024 slice pairs from 398 ...

Somatic hypermutation in cancer has gained momentum with the increased use of tumour mutation burden as a biomarker for immune checkpoint inhibitors. Spontaneous deamination of 5-methylcytosine to thymine at CpG dinucleotides is one of the most ubiquitous ...

Research on metastatic cancer has been hampered by limited sample availability. Here we present the breast cancer post-mortem tissue donation program UPTIDER and show how it enabled sampling of a median of 31 (range: 5-90) metastases and 5-8 liquids per pa ...

In the past few years, Machine Learning (ML) techniques have ushered in a paradigm shift, allowing the harnessing of ever more abundant sources of data to automate complex tasks. The technical workhorse behind these important breakthroughs arguably lies in ...

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 ...

In the realm of point cloud scene understanding, particularly in indoor scenes, objects are arranged following human habits, resulting in objects of certain semantics being closely positioned and displaying notable inter-object correlations. This can creat ...

Machine learning (ML) enables artificial intelligent (AI) agents to learn autonomously from data obtained from their environment to perform tasks. Modern ML systems have proven to be extremely effective, reaching or even exceeding human intelligence. Altho ...

High-throughput transcriptomics is of increasing fundamental biological and clinical interest. The generation of molecular data from large collections of samples, such as biobanks and drug libraries, is boosting the development of new biomarkers and treatm ...

Dendritic cells (DCs) are specialized myeloid cells with the ability to uptake, process, and present antigens to T lymphocytes. They also generate cytokine and chemokine gradients that regulate immune cell trafficking, activation, and function. Monocyte-de ...

Viral metagenomics is a useful tool for detecting multiple human viruses in urban sewage. However, more refined protocols are required for its effective use in disease surveillance. In this study, we investigated the performance of three different preampli ...

In this thesis we explore the applications of projective geometry, a mathematical theory of the relation between 3D scenes and their 2D images, in modern learning-based computer vision systems. This is an interesting research question which contradicts the ...

Modern neuroscience research is generating increasingly large datasets, from recording thousands of neurons over long timescales to behavioral recordings of animals spanning weeks, months, or even years. Despite a great variety in recording setups and expe ...

The ability to reason, plan and solve highly abstract problems is a hallmark of human intelligence. Recent advancements in artificial intelligence, propelled by deep neural networks, have revolutionized disciplines like computer vision and natural language ...

In the last decade, organoid technology has become a cornerstone in cancer research. Organoids are long-term primary cell cultures, usually of epithelial origin, grown in a three-dimensional (3D) protein matrix and a fully defined medium. Organoids can be ...

While largely neglected over decades during which adaptive immunity captured most of the attention, innate immune mechanisms have now become central to our understanding of immunology. Innate immunity provides the first barrier to infection in vertebrates, ...

The present invention relates to 6-diazo-5-oxo-L-norleucine prodrugs having reduced toxicity and increased tumor specificity and to their therapeutic use for treating cancer. ...

The performance of machine learning algorithms is conditioned by the availability of training datasets, which is especially true for the field of nondestructive evaluation. Here we propose one reconfigurable specimen instead of numerous reference specimens ...

Earth scientists study a variety of problems with remote sensing data, but they most often consider them in isolation from each other, which limits information flows across disciplines. In this work, we present METEOR, a meta-learning methodology for Earth ...

Computing servers have played a key role in developing and processing emerging compute-intensive applications in recent years. Consolidating multiple virtual machines (VMs) inside one server to run various applications introduces severe competence for limi ...

Cancer cell plasticity contributes to therapy resistance and metastasis, which represent the main causes of cancer-related death, including in breast cancer. The tumor microenvironment drives cancer cell plasticity and metastasis, and unraveling the underl ...

A meta-learning approach for genomic survival analysis

Chattez avec Graph Search

Tuning vision foundation models for rectal cancer segmentation from CT scans

Somatic CpG hypermutation is associated with mismatch repair deficiency in cancer

Rapid autopsies to enhance metastatic research: the UPTIDER post-mortem tissue donation program

Topics in statistical physics of high-dimensional machine learning

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

Mitigating Object Dependencies: Improving Point Cloud Self-Supervised Learning through Object Exchange

Few-shot Learning for Efficient and Effective Machine Learning Model Adaptation

Multi-well plate lid for single-step pooling of 96 samples for high-throughput barcode-based sequencing

Cytokine-armed dendritic cell progenitors for antigen-agnostic cancer immunotherapy

Comparison of Three Viral Nucleic Acid Preamplification Pipelines for Sewage Viral Metagenomics

Incorporating Projective Geometry into Deep Learning

Robust machine learning for neuroscientific inference

Infusing structured knowledge priors in neural models for sample-efficient symbolic reasoning

Next-Generation Modeling of Cancer Using Organoids

The conceptual foundations of innate immunity: Taking stock 30 years later

6-diazo-5-oxo-l-norleucine prodrugs

Reduced Training Data for Laser Ultrasound Signal Interpretation by Neural Networks

Meta-learning to address diverse Earth observation problems across resolutions

CloudProphet: A Machine Learning-Based Performance Prediction for Public Clouds

Tumor-educated Gr1+CD11b+cells drive breast cancer metastasis via OSM/IL-6/JAK-induced cancer cell plasticity