Latest science, research and ideas

Identification of non-covalent inhibitors for the atypical peroxiredoxin PRDX5 as a therapeutic strategy in malignant pleural mesothelioma

CONFIDENT-HFpEF: A Machine Learning-Based Risk Stratification for Mortality and Hospitalization Using Multimodal Real-World Data

Can AI Scientist Agents Learn from Lab-in-the-Loop Feedback? Evidence from Iterative Perturbation Discovery

CytoSyn: a Foundation Diffusion Model for Histopathology - Tech Report

Multi-modal benchmarking of the Ultima UG100 and Illumina NovaSeq sequencing platforms using clinically relevant FFPE tissues

Spatially Integrated Multi-Omics reveals the Multicellular Landscape of Progenitor-Driven Glioblastoma Progression

Subgroup analysis methods for time-to-event outcomes in heterogeneous randomized controlled trials

OKN4395, a first-in-class EP2/EP4/DP1 triple antagonist reprograms prostanoid-driven immunosuppression to restore antitumor immunity

IMILIA: interpretable multiple instance learning for inflammation prediction in IBD from H&E whole slide images

A deep learning-based multiscale integration of spatial omics with tumor morphology

Multimodal machine learning models enhance outcome prediction in intrahepatic cholangiocarcinoma

Prescription of off-label medications in patients on dialysis: time to challenge contraindications?

Deciphering Cellular Ecosystems Driving Tumor Progression and Immune Escape from Spatial Transcriptomics and Single-Cell with COMPOTES

Multimodal prediction of metastatic relapse using federated deep learning in soft-tissue sarcoma with a complex genomic profile

Multiple instance learning with spatial transcriptomics for interpretable patient-level predictions: application in glioblastoma

Histology and spatial transcriptomic integration revealed infiltration zone with specific cell composition as a prognostic hotspot in glioblastoma

Deep Learning on Histologic Slides Accurately Predicts Consensus Molecular Subtypes and Spatial Heterogeneity in Colon Cancer

OwkinZero: Accelerating Biological Discovery with AI

Towards Comprehensive Cellular Characterisation of H&E slides

FedECA: federated external control arms for causal inference with time-to-event data in distributed settings

Clinical Validation of RlapsRisk BC in an international multi-cohorts setting

Joint probabilistic modeling of pseudobulk and single-cell transcriptomics enables accurate estimation of cell type composition

Deep learning assessment of metastatic relapse risk from digitized breast cancer histological slides

MOSAIC: Intra-tumoral heterogeneity characterization through large-scale spatial and cell-resolved multi-omics profiling

Robust sensitivity control in digital pathology via tile score distribution matching

Predicting gene essentiality and drug response from perturbation screens in preclinical cancer models with LEAP: Layered Ensemble of Autoencoders and Predictors

Distilling foundation models for robust and efficient models in digital pathology

AI allows pre-screening of FGFR3 mutational status using routine histology slides of muscle-invasive bladder cancer

Deep learning uncovers histological patterns of YAP1/TEAD activity related to disease aggressiveness in cancer patients

FedPyDESeq2: a federated framework for bulk RNA-seq differential expression analysis

Transcriptome Analysis of Archived Tumor Tissues by Visium, GeoMx DSP, and Chromium Methods Reveals Inter- and Intra-Patient Heterogeneity

Legitimate ground-truth-free metrics for deep uncertainty classification scoring

Phikon-v2, A large and public feature extractor for biomarker prediction

MYC Rearrangement Prediction from LYSA Whole Slide Images in Large B-cell Lymphoma: A Multi-centric Validation of Self-supervised Deep Learning Models

CARMIL: Context-Aware Regularization on Multiple Instance Learning models for Whole Slide Images

Development of a Deep Learning model Tailored for HER2 Detection in Breast Cancer to aid pathologists in interpreting HER2-Low cases

Robust Evaluation of Deep Learning-based Representation Methods for Survival and Gene Essentiality Prediction on Bulk RNA-seq Data

Combining a deep learning model with clinical data better predicts hepatocellular carcinoma behavior following surgery

Validation of MSIntuit as an AI-based pre-screening tool for MSI detection from colorectal cancer histology slides

PyDESeq2: a python package for bulk RNA-seq differential expression analysis

The use of deep learning models to predict progression-free survival in patients with neuroendocrine tumors

Response heterogeneity as a new biomarker of treatment response in patients with neuroendocrine tumors

Scaling Self-Supervised Learning for Histopathology with Masked Image Modeling

Deep learning predicts patients outcome and mutations from digitized histology slides in gastrointestinal stromal tumor

Adjuvant endocrine therapy uptake, toxicity, quality of life, and prediction of early discontinuation

Industry-scale orchestrated federated learning for drug discovery

A benchmark of computational pipelines for single-cell histone modification data

SRATTA : Sample Re-ATTribution Attack of secure aggregation in federated learning

Pacpaint: a histology-based deep learning model uncovers the extensive intratumor molecular heterogeneity of pancreatic adenocarcinoma

More efficient and inclusive time-to-event trials with covariate adjustment: a simulation study

Owkin's Jean-Philippe Vert shared his thoughts on how generative AI might disrupt drug discovery with Nature Biotechnology

Semiautomated segmentation of hepatocellular carcinoma tumors with MRI using convolutional neural networks

Multiomic analysis of malignant pleural mesothelioma identifies molecular axes and specialized tumor profiles driving intertumor heterogeneity

A Statistical Learning Take on the Concordance Index for Survival Analysis

Federated learning for predicting histological response to neoadjuvant chemotherapy in triple-negative breast cancer

External control arm analysis: an evaluation of propensity score approaches, G-computation, and doubly debiased machine learning

FLamby: Datasets and Benchmarks for Cross-Silo Federated Learning in Realistic Healthcare Settings

SecureFedYJ: a safe feature Gaussianization protocol for Federated Learning

An artificial intelligence model predicts the survival of solid tumour patients from imaging and clinical data

Can machine learning bring cardiovascular risk assessment to the next level? A methodological study using FOURIER trial data

Collaborative Federated Learning behind Hospitals’ Firewalls for Predicting Histological Response to Neoadjuvant Chemotherapy in Triple-Negative Breast Cancer

A deep learning method for predicting knee osteoarthritis radiographic progression from MRI

SAFER: Sparse Secure Aggregation for Federated Learning

Prediction of distant relapse in patients with invasive breast cancer from deep learning models applied to digital pathology slides

Self supervised learning improves dMMR/MSI detection from histology slides across multiple cancers

Differentially Private Federated Learning for Cancer Prediction

Integrating deep learning CT-scan model, biological and clinical variables to predict severity of COVID-19 patients

Identification of pancreatic adenocarcinoma molecular subtypes on histology slides using deep learning models

Abdominal musculature segmentation and surface prediction from CT using deep learning for sarcopenia assessment

Self-Supervision Closes the Gap Between Weak and Strong Supervision in Histology

Using StyleGAN for Visual Interpretability of Deep Learning Models on Medical Images

Fully automatic segmentation of diffuse large B cell lymphoma lesions on 3D FDG-PET/CT for total metabolic tumour volume prediction using a convolutional neural network

The future of digital health with federated learning

Siloed Federated Learning for Multi-Centric Histopathology Datasets

A deep learning model to predict RNA-Seq expression of tumours from whole slide images

Comprehensive Molecular and Pathologic Evaluation of Transitional Mesothelioma Assisted by Deep Learning Approach: A Multi-Institutional Study of the International Mesothelioma Panel from the MESOPATH Reference Center

Federated Survival Analysis with Discrete-Time Cox Models

Predicting Survival After Hepatocellular Carcinoma Resection Using Deep Learning on Histological Slides

Prognostic value of anthropometric measures extracted from whole-body CT using deep learning in patients with non-small-cell lung cancer

Efficient Per-Example Gradient Computations in Convolutional Neural Networks

Substra: a framework for privacy-preserving, traceable and collaborative Machine Learning

Deep learning-based classification of mesothelioma improves prediction of patient outcome

Comparative performances of machine learning methods for classifying Crohn Disease patients using genome-wide genotyping data

ToxicBlend: Virtual screening of toxic compounds with ensemble predictors

Detection and characterization of MRI breast lesions using deep learning

Diagnosis of focal liver lesions from ultrasound using deep learning

How to estimate the age of your brain with MRI data

Deterministic and generalized framework for unsupervised learning with restricted boltzmann machines

Brain age prediction of healthy subjects on anatomic MRI with deep learning: going beyond with an" explainable AI

Classification and disease localization in histopathology using only global labels: A weakly-supervised approach

Robust Detection of Covariate-Treatment Interactions in Clinical Trials