Skin Cancer

Automated diagnosis of 7 canine skin tumors using machine learning on H&E-stained whole slide images.

Microscopic evaluation of hematoxylin and eosin-stained slides is still the diagnostic gold standard...

Cuproptosis facilitates immune activation but promotes immune escape, and a machine learning-based cuproptosis-related signature is identified for predicting prognosis and immunotherapy response of gliomas.

AIMS: Cell death, except for cuproptosis, in gliomas has been extensively studied, providing novel t...

Machine-learning and combined analysis of single-cell and bulk-RNA sequencing identified a DC gene signature to predict prognosis and immunotherapy response for patients with lung adenocarcinoma.

BACKGROUND: Innate immune effectors, dendritic cells (DCs), influence cancer prognosis and immunothe...

The accuracy of artificial intelligence used for non-melanoma skin cancer diagnoses: a meta-analysis.

BACKGROUND: With rising incidence of skin cancer and relatively increased mortality rates, an improv...

Combining hyperspectral imaging techniques with deep learning to aid in early pathological diagnosis of melanoma.

BACKGROUND: Cutaneous melanoma, an exceedingly aggressive form of skin cancer, holds the top rank in...

Immunodiagnosis - the promise of personalized immunotherapy.

Immunotherapy showed remarkable efficacy in several cancer types. However, the majority of patients ...

Cancer immunotherapy response prediction from multi-modal clinical and image data using semi-supervised deep learning.

BACKGROUND AND PURPOSE: Immunotherapy is a standard treatment for many tumor types. However, only a ...

The prediction of drug sensitivity by multi-omics fusion reveals the heterogeneity of drug response in pan-cancer.

Cancer drug response prediction based on genomic information plays a crucial role in modern pharmaco...

Prediction of IDO1 Inhibitors by a Fingerprint-Based Stacking Ensemble Model Named IDO1Stack.

Indoleamine 2,3-dioxygenase 1 (IDO1) is viewed as an extremely promising target for cancer immunothe...

Deep Learning-Based Stratification of Gastric Cancer Patients from Hematoxylin and Eosin-Stained Whole Slide Images by Predicting Molecular Features for Immunotherapy Response.

Determining the molecular characteristics of cancer patients is crucial for optimal immunotherapy de...

Artificial Intelligence Applied to a First Screening of Naevoid Melanoma: A New Use of Fast Random Forest Algorithm in Dermatopathology.

Malignant melanoma (MM) is the "great mime" of dermatopathology, and it can present such rare varian...

Deep learning-based scoring of tumour-infiltrating lymphocytes is prognostic in primary melanoma and predictive to PD-1 checkpoint inhibition in melanoma metastases.

BACKGROUND: Recent advances in digital pathology have enabled accurate and standardised enumeration ...

Deep learning-based radiomics: pacing immunotherapy in lung cancer.

Deep learning in computational dermatopathology of melanoma: A technical systematic literature review.

Deep learning (DL) has become one of the major approaches in computational dermatopathology, evidenc...

Biologically Interpretable Deep Learning To Predict Response to Immunotherapy In Advanced Melanoma Using Mutations and Copy Number Variations.

Only 30-40% of advanced melanoma patients respond effectively to immunotherapy in clinical practice,...

The artificial intelligence and machine learning in lung cancer immunotherapy.

Since the past decades, more lung cancer patients have been experiencing lasting benefits from immun...

Deep learning-based methods for classification of microsatellite instability in endometrial cancer from HE-stained pathological images.

BACKGROUND: Microsatellite instability (MSI) is one of the essential tumor biomarkers for cancer tre...

Outcome-Supervised Deep Learning on Pathologic Whole Slide Images for Survival Prediction of Immunotherapy in Patients with Non-Small Cell Lung Cancer.

Although programmed death-(ligand) 1 (PD-(L)1) inhibitors are marked by durable efficacy in patients...

Deep learning detection of melanoma metastases in lymph nodes.

BACKGROUND: In melanoma patients, surgical excision of the first draining lymph node, the sentinel l...

Progressive growing of Generative Adversarial Networks for improving data augmentation and skin cancer diagnosis.

Early melanoma diagnosis is the most important factor in the treatment of skin cancer and can effect...

Synthetic biology, genetic circuits and machine learning: a new age of cancer therapy.

Synthetic biology has made it possible to rewire natural cellular responses to treat disease, notabl...