Skin Cancer

Deep Learning-Based Classification for Melanoma Detection Using XceptionNet.

Skin cancer is one of the most common types of cancer in the world, accounting for at least 40% of all cancers. Melanoma is considered as the 19th most commonly occurring cancer among the other cancers in the human society, such that about 300,000 new cases were found in 2018. While cancer diagnosis is based on interventional methods such as surgery, radiotherapy, and chemotherapy, studies show th...

Cell segmentation for immunofluorescence multiplexed images using two-stage domain adaptation and weakly labeled data for pre-training.

Cellular profiling with multiplexed immunofluorescence (MxIF) images can contribute to a more accurate patient stratification for immunotherapy. Accurate cell segmentation of the MxIF images is an essential step. We propose a deep learning pipeline to train a Mask R-CNN model (deep network) for cell segmentation using nuclear (DAPI) and membrane (NaKATPase) stained images. We used two-stage domain...

Melanoma segmentation using deep learning with test-time augmentations and conditional random fields.

In a computer-aided diagnostic (CAD) system for skin lesion segmentation, variations in shape and size of the skin lesion makes the segmentation task ...

A Cloud Approach for Melanoma Detection Based on Deep Learning Networks.

In the era of digitized images, the goal is to extract information from them and create new knowledge thanks to Computer Vision techniques, Machine Le...

Deep learning using bulk RNA-seq data expands cell landscape identification in tumor microenvironment.

The tumor microenvironment (TME) profoundly influences tumor progression and affects immunotherapy responses and resistance. Understanding its heterog...

Functions of RNF Family in the Tumor Microenvironment and Drugs Prediction in Grade II/III Gliomas.

Increasing evidence has demonstrated that RING finger (RNF) proteins played a vital role in cellular and physiological processes and various diseases....

Specific IgE and IgG4 Profiles of House Dust Mite Components in Allergen-Specific Immunotherapy.

BACKGROUND: Allergen immunotherapy (AIT) can induce immune tolerance to allergens by activating multiple mechanisms, including promoting IgG4 synthesi...

Artificial intelligence and melanoma: A comprehensive review of clinical, dermoscopic, and histologic applications.

Melanoma detection, prognosis, and treatment represent challenging and complex areas of cutaneous oncology with considerable impact on patient outcome...

Machine Learning of Single Cell Transcriptomic Data From anti-PD-1 Responders and Non-responders Reveals Distinct Resistance Mechanisms in Skin Cancers and PDAC.

Immune checkpoint therapies such as PD-1 blockade have vastly improved the treatment of numerous cancers, including basal cell carcinoma (BCC). Howeve...

New Trends in Melanoma Detection Using Neural Networks: A Systematic Review.

Due to its increasing incidence, skin cancer, and especially melanoma, is a serious health disease today. The high mortality rate associated with mela...

Integrated Machine Learning and Bioinformatic Analyses Constructed a Novel Stemness-Related Classifier to Predict Prognosis and Immunotherapy Responses for Hepatocellular Carcinoma Patients.

Immunotherapy has made great progress in hepatocellular carcinoma (HCC), yet there is still a lack of biomarkers for predicting response to it. Cancer...

DNA-based artificial dendritic cells for in situ cytotoxic T cell stimulation and immunotherapy.

In immunotherapy, ex vivo stimulation of T cells requires significant resources and effort. Here, we report artificial dendritic cell-mimicking DNA mi...

A Prediction Model to Discriminate Small Choroidal Melanoma from Choroidal Nevus.

OBJECTIVE: This study aimed to develop a validated machine learning model to diagnose small choroidal melanoma.

Pharmacological, Technological, and Digital Innovative Aspects in Rhinology.

Innovation refers to the introduction of a product, a process, a service or a solution resulting in something new or significantly improved compared t...

A Pan-Cancer Analysis of Predictive Methylation Signatures of Response to Cancer Immunotherapy.

Recently, tumor immunotherapy based on immune checkpoint inhibitors (ICI) has been introduced and widely adopted for various tumor types. Nevertheless...

A Computer-Aided Diagnosis System Using Deep Learning for Multiclass Skin Lesion Classification.

In the USA, each year, almost 5.4 million people are diagnosed with skin cancer. Melanoma is one of the most dangerous types of skin cancer, and its s...

Robotic Extended Ultrasound-Guided Distal Pancreatectomy for Pancreatic Metastases from Uveal Melanoma.

BACKGROUND: Isolated pancreatic metastasis from melanoma is extremely uncommon and accounts for approximately only 2% of visceral disseminations of me...

Deep learning model enables the discovery of a novel immunotherapeutic agent regulating the kynurenine pathway.

Kynurenine (Kyn) is a key inducer of an immunosuppressive tumor microenvironment (TME). Although indoleamine 2,3-dioxygenase (IDO)-selective inhibitor...

Detecting immunotherapy-sensitive subtype in gastric cancer using histologic image-based deep learning.

Immune checkpoint inhibitor (ICI) therapy is widely used but effective only in a subset of gastric cancers. Epstein-Barr virus (EBV)-positive and micr...

Imaging flow cytometry data analysis using convolutional neural network for quantitative investigation of phagocytosis.

Macrophages play an important role in the adaptive immune system. Their ability to neutralize cellular targets through Fc receptor-mediated phagocytos...