Skin Cancer

[ARTIFICIAL INTELLIGENCE-ASSISTED LITERATURE REVIEW: A CASE STUDY IN FUMARATE HYDRATASE-DEFICIENT RENAL CELL CARCINOMA].

Fumarate hydratase-deficient renal cell carcinoma (FHdRCC) is a rare and aggressive form of kidney cancer that presents significant therapeutic challenges. Due to its rarity, treatment decisions often rely on comprehensive literature reviews to identify potential therapeutic options. This article presents a case of a 37-year-old patient with metastatic FHdRCC who showed partial response to Nivolum...

LightCTL: lightweight contrastive TCR-pMHC specificity learning with context-aware prompt.

Identification of T cell receptor (TCR) specificities for antigens from large-scale single-cell or bulk TCR repertoire data plays a vital role in disease diagnosis and immunotherapy. In silico prediction models have emerged in recent years. However, the generalizability and transferability of current computational models remain significant hurdles in accurately predicting TCR-pMHC binding specific...

Deep scSTAR: leveraging deep learning for the extraction and enhancement of phenotype-associated features from single-cell RNA sequencing and spatial transcriptomics data.

Single-cell sequencing has advanced our understanding of cellular heterogeneity and disease pathology, offering insights into cellular behavior and im...

Omics data classification using constitutive artificial neural network optimized with single candidate optimizer.

Recent technical advancements enable omics-based biological study of molecules with very high throughput and low cost, such as genomic, proteomic, and...

Discovery of hematopoietic progenitor kinase 1 inhibitors using machine learning-based screening and free energy perturbation.

Hematopoietic progenitor kinase 1 (HPK1) is a key negative regulator of T-cell receptor (TCR) signaling and a promising target for cancer immunotherap...

Artificial intelligence-driven microsatellite instability profiling reveals distinctive genetic features in patients with lung cancer.

BACKGROUND: Microsatellite instability (MSI) has emerged as a predictive biomarker for immunotherapy response in various cancers, but its role in non-...

Enhancing TCR-Peptide Interaction Prediction with Pretrained Language Models and Molecular Representations

Understanding the binding specificity between T-cell receptors (TCRs) and peptide-major histocompatibility complexes (pMHCs) is central to immunothe...

Identification of a telomere-related gene signature for the prognostic and immune landscape prediction in head and neck squamous cell carcinoma by integrated analysis of machine learning and Mendelian randomization.

Telomere-related genes (TRGs) are vital in diverse tumor types. Nevertheless, there is a notable lack of in-depth research concerning their significan...

Machine Learning Unveils Sphingolipid Metabolism's Role in Tumour Microenvironment and Immunotherapy in Lung Cancer.

TME is a core player in the development of a cancerous lesion, the immune evasive potential of the lesion, and its response to therapy. Sphingolipid m...

PD-L1 Scoring Models for Non-Small Cell Lung Cancer in China: Current Status, AI-Assisted Solutions and Future Perspectives.

Immunotherapy has revolutionized the diagnosis and treatment model for patients with advanced non-small cell lung cancer (NSCLC). Numerous clinical tr...

A Multi-Stage Auto-Context Deep Learning Framework for Tissue and Nuclei Segmentation and Classification in H&E-Stained Histological Images of Advanced Melanoma

Melanoma is the most lethal form of skin cancer, with an increasing incidence rate worldwide. Analyzing histological images of melanoma by localizin...

ProtoBERT-LoRA: Parameter-Efficient Prototypical Finetuning for Immunotherapy Study Identification

Identifying immune checkpoint inhibitor (ICI) studies in genomic repositories like Gene Expression Omnibus (GEO) is vital for cancer research yet re...

Geometric deep learning and multiple-instance learning for 3D cell-shape profiling.

The three-dimensional (3D) morphology of cells emerges from complex cellular and environmental interactions, serving as an indicator of cell state and...

Cracking the PUMA Challenge in 24 Hours with CellViT++ and nnU-Net

Automatic tissue segmentation and nuclei detection is an important task in pathology, aiding in biomarker extraction and discovery. The panoptic seg...

Assessing the effects of immune checkpoint inhibitors on bone utilizing machine learning-assisted opportunistic quantitative computed tomography.

Immune checkpoint inhibitors (ICIs) are widely used in cancer treatment, yet their impact on bone health remains unclear. This study aimed to perform ...

ScaleFusionNet: Transformer-Guided Multi-Scale Feature Fusion for Skin Lesion Segmentation

Melanoma is a malignant tumor originating from skin cell lesions. Accurate and efficient segmentation of skin lesions is essential for quantitative ...

Differentially private fine-tuned NF-Net to predict GI cancer type

Based on global genomic status, the cancer tumor is classified as Microsatellite Instable (MSI) and Microsatellite Stable (MSS). Immunotherapy is us...

PathFinder: A Multi-Modal Multi-Agent System for Medical Diagnostic Decision-Making Applied to Histopathology

Diagnosing diseases through histopathology whole slide images (WSIs) is fundamental in modern pathology but is challenged by the gigapixel scale and...

Cancer Vaccine Adjuvant Name Recognition from Biomedical Literature using Large Language Models

Motivation: An adjuvant is a chemical incorporated into vaccines that enhances their efficacy by improving the immune response. Identifying adjuvant...

Treatment response as a latent variable

Scientists often need to analyze the samples in a study that responded to treatment in order to refine their hypotheses and find potential causal dr...