Skin Cancer

Leveraging Artificial Intelligence for Neoantigen Prediction.

Neoantigens represent a class of antigens within tumor microenvironments that arise from diverse som...

Artificial Intelligence Can Predict Personalized Immunotherapy Outcomes in Cancer.

The rapid advancement of artificial intelligence (AI) technologies has opened new avenues for advanc...

Advancing T-cell immunotherapy for cellular senescence and disease: Mechanisms, challenges, and clinical prospects.

Cellular senescence is a complex biological process with a dual role in tissue homeostasis and aging...

Establishment of an intelligent analysis system for clinical image features of melanonychia based on deep learning image segmentation.

Melanonychia, a condition that can be indicative of malignant melanoma, presents a significant chall...

Integrating multi-omics data with artificial intelligence to decipher the role of tumor-infiltrating lymphocytes in tumor immunotherapy.

Tumor-infiltrating lymphocytes (TILs) are capable of recognizing tumor antigens, impacting tumor pro...

Comparing the number-needed-to-biopsy ratio for melanoma diagnosis by artificial intelligence as a medical device, teledermatology and face-to-face models of care.

[Progress in neoadjuvant immunotherapy for locally advanced rectal cancer].

Neoadjuvant chemoradiotherapy (NACRT) is the standard treatment for locally advanced rectal cancer (...

Nanotechnology-Enhanced siRNA Delivery: Revolutionizing Cancer Therapy.

RNA interference (RNAi) has emerged as a transformative approach for cancer therapy, enabling precis...

Characterization of m6A-Related Genes in Tumor-Associated Macrophages for Prognosis, Immunotherapy, and Drug Prediction in Lung Adenocarcinomas Based on Machine Learning Algorithms.

Tumor-associated macrophages (TAMs) are a vital immune component within the tumor microenvironment (...

Artificial Intelligence and Machine Learning in the Development of Vaccines and Immunotherapeutics Yesterday, Today, and Tomorrow

In the past, the development of vaccines and immunotherapeutics relied heavily on trial-and-error ...

Immunological mechanisms and immunoregulatory strategies in intervertebral disc degeneration

Intervertebral discs are avascular and maintain immune privilege. However, during intervertebral d...

Knowledge-guided Contextual Gene Set Analysis Using Large Language Models

Gene set analysis (GSA) is a foundational approach for interpreting genomic data of diseases by li...

Deep learning model for predicting immunotherapy response in patients with advanced NSCLC: Study findings demonstrate a strong and independent deep learning-based feature associated with an immune checkpoint inhibitor response in patients with NSCLC across cohorts.

Self-supervised multi-modality learning for multi-label skin lesion classification.

BACKGROUND: The clinical diagnosis of skin lesions involves the analysis of dermoscopic and clinical...

A machine learning-derived angiogenesis signature for clinical prognosis and immunotherapy guidance in colon adenocarcinoma.

Colon adenocarcinoma (COAD) is one of the most prevalent malignancies worldwide and its prognosis is...

Comprehensive biobanking strategy with clinical impact at the European Cancer Moonshot Lund Center.

This white paper presents a comprehensive biobanking framework developed at the European Cancer Moon...

Skin Lesion Phenotyping via Nested Multi-modal Contrastive Learning

We introduce SLIMP (Skin Lesion Image-Metadata Pre-training) for learning rich representations of ...

ImmunoDiff: A Diffusion Model for Immunotherapy Response Prediction in Lung Cancer

Accurately predicting immunotherapy response in Non-Small Cell Lung Cancer (NSCLC) remains a criti...

Machine learning identifies SRD5A3 as a propionate-related prognostic biomarker in triple-negative breast cancer.

The increased risk of recurrence and metastasis are obstacles to treating TNBC. Propionate-related g...

Chaperonin containing TCP1 subunit 5 as a novel pan-cancer prognostic biomarker for tumor stemness and immunotherapy response: insights from multi-omics data, integrated machine learning, and experimental validation.

BACKGROUND: Chaperonin containing TCP1 subunit 5 (CCT5), a vital component of the molecular chaperon...

Integrating machine learning and multi-omics analysis to unveil key programmed cell death patterns and immunotherapy targets in kidney renal clear cell carcinoma.

Kidney renal clear cell carcinoma (KIRC), a cancer characterized by substantial immune infiltration,...