Dermatology

FFixR: A Machine Learning Framework for Accurate Somatic Mutation Calling from FFPE RNA-Seq Data in Cancer

Formalin-fixed paraffin-embedded (FFPE) tissues are widely used in clinical and research settings, yet their use for detecting somatic mutations from RNA sequencing (RNA-seq) is hindered by artefactual mutations introduced by cytosine deamination and strand-specific damage. Existing FFPE noise-filtering tools are tailored to DNA-seq and rely on strand bias, rendering them unsuitable for RNA-seq. H...

Uncertainty-Aware Tau Detection in Progressive Supranuclear Palsy Using Object Detection Models

Abnormal tau accumulation is a hallmark of neurodegenerative tauopathies such as Progressive Supranuclear Palsy (PSP). Traditional post-mortem assessments rely on manual lesion annotation, which is time-consuming and subjective. Existing machine learning methods typically involve multi-stage, feature-based pipelines, resulting in limited scalability and reliance on handcrafted features. This work ...

Finetuning Foundation Models for Temporal Clinical Transcriptomics Data

Timeseries clinical transcriptomic datasets offer the opportunity to gain insights into the dynamics of disease mechanisms/treatment responses. Howeve...

Spatially varying cell-specific gene regulation network inference

Gene regulatory networks (GRNs), involving interactions between large numbers of genes, govern expression levels of mRNA and their resulting proteins ...

Gut Microbiota Modulates and Predicts Disease Severity in Experimental Pemphigoid Disease

Pemphigoid diseases (PD) are autoimmune blistering diseases with reported alterations in skin and gut microbiota, though their causal contribution to ...

Language may be all omics needs: Harmonizing multimodal data for omics understanding with CellHermes

Decoding cellular systems requires integrating diverse omics data, yet most models are trained from scratch on a single modality, restricting generali...

Multiplex imaging combined to machine learning enable automated profiling of cortical malformations: applications in tuberous sclerosis complex

Malformations of cortical development such as tuberous sclerosis complex arise within a heterogeneous cellular landscape that conventional histopathol...

OS2CR-Diff: A Self-Refining Diffusion Framework for CD8 Imputation from One-Step Inference to Conditional Representation

Stain imputation in multiplex immunofluorescence (mIF) imaging addresses the challenge of missing or damaged biomarker channels by reconstructing targ...

Design of Allosteric Inhibitors for Mutant EGFR by Combined use of Machine Learning and Molecular Dynamics Simulations

The non-small cell lung cancer (NSCLC)-associated Epidermal Growth Factor Receptor (EGFR) mutant L858R/T790M confers resistance to first- and second-g...

Biologically Inspired Digital Histology for Deep Phenotyping of Placental Composition Changes Across Major Lesion Types

Placenta pathology provides diagnostic insights for understanding pregnancy complications and guides maternal and perinatal care. While placental abno...

scE2TM improves single-cell embedding interpretability and reveals cellular perturbation signatures

Single-cell RNA sequencing technologies have revolutionized our understanding of cellular heterogeneity, yet computational methods often struggle to b...

Cellular interactions in the sentinel lymph node predict melanoma recurrence

Melanoma outcomes have dramatically improved over the past decade, but some patients still experience disease recurrence, particularly those who prese...

Exploiting pair correlation function to describe biological tissue structure

Multiplexed imaging technologies now enable the simultaneous profiling of hundreds to thousands of molecular targets in intact tissues, providing unpr...

Excellent agreement between automated deep learning-based and manual DWI infarct volume measurements in hyperacute stroke

Diffusion-weighted imaging (DWI) lesion volume and infarct growth are important imaging markers in acute ischemic stroke, but manual volume measuremen...

Evaluating the Diagnostic and Treatment Recommendation Capabilities of GPT-4 Vision in Dermatology

The integration of artificial intelligence (AI) in dermatology presents a promising frontier for enhancing diagnostic accuracy and treatment planning....

Automatic segmentation of spinal cord lesions in MS: A robust tool for axial T2-weighted MRI scans

Deep learning models have achieved remarkable success in segmenting brain white matter lesions in multiple sclerosis (MS), becoming integral to both r...

Multi-resolution vision transformer model for skin cancer subtype classification using histopathology slides

Digital pathology has significantly advanced cancer diagnosis by enabling high-resolution visualisation and assessment of tissue specimens. However, t...

An Efficient and Interpretable Foundation Model for Retinal Image Analysis in Disease Diagnosis

Artificial intelligence (AI) foundation models for colour fundus photography (CFP) have been extensively studied and demonstrated great potential for ...

Integration of CA attention and KAN algorithm to predict EGFR mutation status in lung cancer

Epidermal Growth Factor Receptor (EGFR) mutations are critical biomarkers for targeted therapies in non-small cell lung cancer (NSCLC). However, conve...

Cutaneous leishmaniasis in Casablanca-Settat region (Morocco): spatio-temporal analysis of disease dynamic and machine learning based case prediction

Cutaneous leishmaniasis (CL) caused by Leishmania protozoa and transmitted through infected sandfly bites, poses a significant public health burden in...