Skin Cancer

Machine learning-based integration develops a multiple programmed cell death signature for predicting the clinical outcome and drug sensitivity in colorectal cancer.

Tumorigenesis and treatment are closely associated with various programmed cell death (PCD) patterns...

A Self-Supervised Learning Based Framework for Eyelid Malignant Melanoma Diagnosis in Whole Slide Images.

Eyelid malignant melanoma (MM) is a rare disease with high mortality. Accurate diagnosis of such dis...

IRnet: Immunotherapy response prediction using pathway knowledge-informed graph neural network.

INTRODUCTION: Immune checkpoint inhibitors (ICIs) are potent and precise therapies for various cance...

Artificial Intelligence Applications in Oral Cancer and Oral Dysplasia.

Oral squamous cell carcinoma (OSCC) is a highly unpredictable disease with devastating mortality rat...

Artificial intelligence-assisted metastasis and prognosis model for patients with nodular melanoma.

OBJECTIVE: The objective of this study was to identify the risk factors that influence metastasis an...

Utilizing deep learning model for assessing melanocytic density in resection margins of lentigo maligna.

BACKGROUND: Surgical excision with clear histopathological margins is the preferred treatment to pre...

Integrated machine learning screened glutamine metabolism-associated biomarker SLC1A5 to predict immunotherapy response in hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) stands as one of the most prevalent malignancies. While PD-1 immune c...

Cheminformatics analysis of indoleamine and tryptophan 2,3-dioxygenase inhibitors: A descriptor and fingerprint based machine learning approach to disclose selectivity measures.

Indoleamine 2,3-dioxygenase (IDO) and tryptophan 2,3-dioxygenase (TDO) are attractive drug targets f...

CT-based deep learning radiomics biomarker for programmed cell death ligand 1 expression in non-small cell lung cancer.

BACKGROUND: Programmed cell death ligand 1 (PD-L1), as a reliable predictive biomarker, plays an imp...

A stemness-based signature with inspiring indications in discriminating the prognosis, immune response, and somatic mutation of endometrial cancer patients revealed by machine learning.

Endometrial cancer (EC) is a fatal gynecologic tumor. Bioinformatic tools are increasingly developed...

Using deep learning to decipher the impact of telomerase promoter mutations on the dynamic metastatic morpholome.

Melanoma showcases a complex interplay of genetic alterations and intra- and inter-cellular morpholo...

Single-cell hdWGCNA reveals metastatic protective macrophages and development of deep learning model in uveal melanoma.

BACKGROUND: Although there has been some progress in the treatment of primary uveal melanoma (UVM), ...

Deep learning algorithms for melanoma detection using dermoscopic images: A systematic review and meta-analysis.

BACKGROUND: Melanoma is a serious risk to human health and early identification is vital for treatme...

Performance of a Machine Learning Algorithm on Lesions with a High Preoperative Suspicion of Invasive Melanoma.

Asymmetric lesion detection with geometric patterns and CNN-SVM classification.

In dermoscopic images, which allow visualization of surface skin structures not visible to the naked...

Developing a machine learning-based prognosis and immunotherapeutic response signature in colorectal cancer: insights from ferroptosis, fatty acid dynamics, and the tumor microenvironment.

INSTRUCTION: Colorectal cancer (CRC) poses a challenge to public health and is characterized by a hi...

Uveal melanoma distant metastasis prediction system: A retrospective observational study based on machine learning.

Uveal melanoma (UM) patients face a significant risk of distant metastasis, closely tied to a poor p...

A novel CAF-cancer cell crosstalk-related gene prognostic index based on machine learning: prognostic significance and prediction of therapeutic response in head and neck squamous cell carcinoma.

BACKGROUND: Cancer-associated fibroblast (CAF)-cancer cell crosstalk (CCCT) plays an important role ...

Cancer Immunotherapies Ignited by a Thorough Machine Learning-Based Selection of Neoantigens.

Identification of neoantigens, derived from somatic DNA alterations, emerges as a promising strategy...

Prediction of molecular subclasses of uveal melanoma by deep learning using routine haematoxylin-eosin-stained tissue slides.

AIMS: Uveal melanoma has a high propensity to metastasize. Prognosis is associated with specific dri...

From Genotype to Phenotype: Raman Spectroscopy and Machine Learning for Label-Free Single-Cell Analysis.

Raman spectroscopy has made significant progress in biosensing and clinical research. Here, we descr...