Oncology/Hematology

Skin Cancer

Latest AI and machine learning research in skin cancer for healthcare professionals.

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Showing 169-189 of 9,298 articles
Smart MXene-based microrobots for targeted drug delivery and synergistic therapies.

MXenes and their composites exhibit remarkable electrical conductivity, mechanical flexibility, and ...

Integrative Multi-Omics Analysis Reveals Molecular Subtypes of Ovarian Cancer and Constructs Prognostic Models.

Ovarian cancer (OV) remains the most lethal gynecological malignancy. The aim of this study was to i...

Integrated bioinformatics analysis to develop diagnostic models for malignant transformation of chronic proliferative diseases.

The combined analysis of dual diseases can provide new insights into pathogenic mechanisms, identify...

101 Machine Learning Algorithms for Mining Esophageal Squamous Cell Carcinoma Neoantigen Prognostic Models in Single-Cell Data.

Esophageal squamous cell carcinoma (ESCC) is one of the most aggressive malignant tumors in the dige...

MIST: An interpretable and flexible deep learning framework for single-T cell transcriptome and receptor analysis.

Joint analysis of transcriptomic and T cell receptor (TCR) features at single-cell resolution provid...

Prediction of PD-L1 expression in NSCLC patients using PET/CT radiomics and prognostic modelling for immunotherapy in PD-L1-positive NSCLC patients.

AIM: To develop a positron emission tomography/computed tomography (PET/CT)-based radiomics model fo...

A weakly supervised deep learning framework for automated PD-L1 expression analysis in lung cancer.

The growing application of immune checkpoint inhibitors (ICIs) in cancer immunotherapy has underscor...

Multiomics evaluation and machine learning optimize molecular classification, prediction of prognosis and immunotherapy response for ovarian cancer.

BACKGROUND: Ovarian cancer (OC), owing to its substantial heterogeneity and high invasiveness, has h...

Deciphering aging-associated prognosis and heterogeneity in gastric cancer through a machine learning-driven approach.

Gastric cancer (GC) is a prevalent malignancy with a high mortality rate and limited treatment optio...

Machine learning based intratumor heterogeneity related signature for prognosis and drug sensitivity in breast cancer.

Intratumor heterogeneity (ITH) is involved in tumor evolution and drug resistance. Drug sensitivity ...

Unveiling the power of Treg.Sig: a novel machine-learning derived signature for predicting ICI response in melanoma.

BACKGROUND: Although immune checkpoint inhibitor (ICI) represents a significant breakthrough in canc...

Automated assessment of skin histological tissue structures by artificial intelligence in cutaneous melanoma.

BACKGROUND: Prognostic histopathological features such as mitosis in melanoma are excluded from the ...

The Role of Eosinophils, Eosinophil-Related Cytokines and AI in Predicting Immunotherapy Efficacy in NSCLC Cancer.

Immunotherapy and chemoimmunotherapy are standard treatments for non-oncogene-addicted advanced non-...

SIMVI disentangles intrinsic and spatial-induced cellular states in spatial omics data.

Spatial omics technologies enable analysis of gene expression and interaction dynamics in relation t...

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