Skin Cancer

Comparative Analysis of Pathology Foundation Models for Automated Detection of Tertiary Lymphoid Structures in H&E-Stained Digital Pathology Images

Tertiary lymphoid structures (TLS) have been observed in solid tumors and have been associated with better outcomes in patients treated with immunotherapy, but their dynamic nature makes identifying TLS in clinical samples challenging. Recently, pathology foundation models have emerged as powerful tools in computational pathology. In this study, we aimed to develop a computational tool capable of ...

Predictive power of different Akkermansia phylogroups in clinical response to PD-1 blockade against non-small cell lung cancer

Immune checkpoint blockade has emerged as a promising form of cancer therapy. However, only some patients respond to checkpoint inhibitors, while a significant proportion of patients do not, calling for the discovery of reliable biomarkers. Recent studies reported the importance of the gut microbiome in the clinical response to PD-1 blockade against non-small cell lung cancer (NSCLC), highlighting...

A unified language model bridging de novo and fragment-based 3D molecule design delivers potent CBL-B inhibitors for cancer treatment

The rational design of small molecules is central to drug discovery, yet current artificial intelligence (AI) methodologies for generating three-dimen...

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...

IMMUNIA: A Multi-LLM Reasoning Agent for Immunoregulatory Surfaceome Discovery

Biomarker discovery for immunotherapy often requires reasoning across complex immune contexts. We present IMMUNIA, a multi-large-language-model (multi...

Targeting peptide–MHC complexes with designed T cell receptors and antibodies

Class I major histocompatibility complexes (MHCs), expressed on the surface of all nucleated cells, present peptides derived from intracellular protei...

TEIP: A Compact, Open-Source Framework for Predicting Tumor Epitope Immunogenicity in Glioblastoma Using Deep Learning and Multi-Modal Biological Features

This work introduces a modular, open-source computational pipeline for glioblastoma (GBM) vaccine design that integrates omics-based OIP5 target disco...

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...

A transcription factor-responsive enhancer discovery platform for targeted immunotherapy

Synthetic enhancers with high specificity are crucial for therapeutic gene control. Although existing experimental screens and machine learning-based ...

A Computational Pipeline for Glioblastoma Vaccine Development: Integrating Novel Omics-Driven OIP5 Target Discovery to Create a Deep Learning-Based Immunogenicity Framework for Personalized Immunotherapy

This work introduces a modular, open-source computational pipeline for glioblastoma (GBM) vaccine design that integrates omics-based OIP5 target disco...

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...

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...

Development of an artificial intelligence-generated, explainable treatment recommendation system for urothelial carcinoma and renal cell carcinoma to support multidisciplinary cancer conferences

Decisions on the best available treatment in clinical oncology are based on expert opinions in multidisciplinary cancer conferences (MCC). Artificial ...

Automated Detection of Faciobrachial Dystonic Seizures Related Events in LGI1 Autoimmune Encephalitis Patients with Wearables

To evaluate the potential of wrist-worn wearable devices to detect and quantify Faciobrachial Dystonic Seizures (FBDS) and related events associated w...

Patient Attitudes Toward Artificial Intelligence in Cancer Care: A Scoping Review

To synthesize existing literature on patient attitudes toward AI in cancer care and identify knowledge gaps that can inform future research and clinic...

CNNeoPP: A Deep Learning Pipeline for Personalized Neoantigen Prediction and Liquid Biopsy Applications

Neoantigens have emerged as promising targets for personalized cancer immunotherapy. However, accurate identification of immunogenic neoantigens remai...

Bridging Data Gaps in Oncology: Large Language Models and Collaborative Filtering for Cancer Treatment Recommendations

Patients with rare cancers face substantial challenges due to limited evidence-based treatment options, resulting from sparse clinical trials. Advance...

Clinicodemographic Prediction of Overall Survival in Patients with Head and Neck Merkel Cell Carcinoma: A Machine Learning Approach

Merkel cell carcinoma (MCC) is a rare cutaneous neuroendocrine malignancy with a higher case-fatality rate than melanoma. The prognosis of MCC is comp...