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 ...

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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 ...

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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 ...

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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. ...

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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

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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