Skin Cancer

Automated gall bladder cancer detection using artificial gorilla troops optimizer with transfer learning on ultrasound images.

The gallbladder (GB) is a small pouch and a deep tissue placed under the liver. GB Cancer (GBC) is a...

The emerging role of AI in enhancing intratumoral immunotherapy care.

The emergence of immunotherapy (IO), and more recently intratumoral IO presents a novel approach to ...

Machine learning-based identification of an immunotherapy-related signature to enhance outcomes and immunotherapy responses in melanoma.

BACKGROUND: Immunotherapy has revolutionized skin cutaneous melanoma treatment, but response variabi...

Vital Characteristics Cellular Neural Network (VCeNN) for Melanoma Lesion Segmentation: A Biologically Inspired Deep Learning Approach.

Cutaneous melanoma is a highly lethal form of cancer. Developing a medical image segmentation model ...

An artificial intelligence-based model exploiting H&E images to predict recurrence in negative sentinel lymph-node melanoma patients.

BACKGROUND: Risk stratification and treatment benefit prediction models are urgent to improve negati...

The transformative potential of AI-driven CRISPR-Cas9 genome editing to enhance CAR T-cell therapy.

This narrative review examines the promising potential of integrating artificial intelligence (AI) w...

Analysis of international publication trends in artificial intelligence in skin cancer.

Bibliometric methods were used to analyze publications on the use of artificial intelligence (AI) in...

The utility and reliability of a deep learning algorithm as a diagnosis support tool in head & neck non-melanoma skin malignancies.

OBJECTIVE: The incidence of non-melanoma skin cancers, encompassing basal cell carcinoma (BCC) and c...

Leveraging AI and patient metadata to develop a novel risk score for skin cancer detection.

Melanoma of the skin is the 17th most common cancer worldwide. Early detection of suspicious skin le...

ConvNext Mitosis Identification-You Only Look Once (CNMI-YOLO): Domain Adaptive and Robust Mitosis Identification in Digital Pathology.

In digital pathology, accurate mitosis detection in histopathological images is critical for cancer ...

Weakly supervised deep learning image analysis can differentiate melanoma from naevi on haematoxylin and eosin-stained histopathology slides.

BACKGROUND: The broad histomorphological spectrum of melanocytic pathologies requires large data set...

Integrated machine learning survival framework to decipher diverse cell death patterns for predicting prognosis in lung adenocarcinoma.

Various forms of programmed cell death (PCD) collectively regulate the occurrence, development and m...

Identification of cancer stem cell-related genes through single cells and machine learning for predicting prostate cancer prognosis and immunotherapy.

BACKGROUND: Cancer stem cells (CSCs) are a subset of cells within tumors that possess the unique abi...

Research progress of the Otubains subfamily in hepatocellular carcinoma.

In cancer research, oncogenesis can be affected by modulating the deubiquitination pathway. Ubiquiti...

Multitask Learning on Graph Convolutional Residual Neural Networks for Screening of Multitarget Anticancer Compounds.

Recently, various modern experimental screening pipelines and assays have been developed to find pro...

Artificial intelligence: A transformative tool in precision oncology.

Artificial intelligence (AI) is revolutionizing society and healthcare, offering new possibilities f...

Machine learning developed a macrophage signature for predicting prognosis, immune infiltration and immunotherapy features in head and neck squamous cell carcinoma.

Macrophages played an important role in the progression and treatment of head and neck squamous cell...

Commentary on "Artificial Intelligence in Dermatology: A Systematic Review of Its Applications in Melanoma and Keratinocyte Carcinoma Diagnosis" and "Artificial Intelligence for Mohs and Dermatologic Surgery: A Systematic Review and Meta-Analysis".

Prediction of CD8+T lymphocyte infiltration levels in gastric cancer from contrast-enhanced CT and clinical factors using machine learning.

BACKGROUND: CD8+ T lymphocyte infiltration is closely associated with the prognosis and immunotherap...

EAAC-Net: An Efficient Adaptive Attention and Convolution Fusion Network for Skin Lesion Segmentation.

Accurate segmentation of skin lesions in dermoscopic images is of key importance for quantitative an...

Hybridizing mechanistic modeling and deep learning for personalized survival prediction after immune checkpoint inhibitor immunotherapy.

We present a study where predictive mechanistic modeling is combined with deep learning methods to p...