Other Cancers

Deep-learning single-shot detector for automatic detection of brain metastases with the combined use of contrast-enhanced and non-enhanced computed tomography images.

PURPOSE: To develop a deep-learning object detection model for automatic detection of brain metastas...

Predicting response to immunotherapy plus chemotherapy in patients with esophageal squamous cell carcinoma using non-invasive Radiomic biomarkers.

OBJECTIVES: To develop and validate a radiomics model for evaluating treatment response to immune-ch...

Enhanced precision of real-time control photothermal therapy using cost-effective infrared sensor array and artificial neural network.

Photothermal therapy (PTT) requires tight thermal dose control to achieve tumor ablation with minima...

Hierarchical graph representations in digital pathology.

Cancer diagnosis, prognosis, and therapy response predictions from tissue specimens highly depend on...

Improving Machine Learning 30-Day Mortality Prediction by Discounting Surprising Deaths.

BACKGROUND: Machine learning (ML) is an emerging tool for predicting need of end-of-life discussion ...

Deep Learning for Lung Cancer Nodal Staging and Real-World Clinical Practice.

Deep Learning for Prediction of N2 Metastasis and Survival for Clinical Stage I Non-Small Cell Lung Cancer.

Background Preoperative mediastinal staging is crucial for the optimal management of clinical stage ...

Breast Mass Classification Using Diverse Contextual Information and Convolutional Neural Network.

Masses are one of the early signs of breast cancer, and the survival rate of women suffering from br...

Automated Machine-Learning Framework Integrating Histopathological and Radiological Information for Predicting IDH1 Mutation Status in Glioma.

Diffuse gliomas are the most common malignant primary brain tumors. Identification of isocitrate deh...

Dynamic Learning Rate in Deep CNN Model for Metastasis Detection and Classification of Histopathology Images.

Diagnosis of different breast cancer stages using histopathology whole slide images (WSI) is the gol...

Complete Molar Pregnancies with a Coexisting Fetus: Pregnancy Outcomes and Review of Literature.

 The objective of the study was to review the obstetric outcomes of complete hydatidiform molar pre...

Artificial intelligence strategy integrating morphologic and architectural biomarkers provides robust diagnostic accuracy for disease progression in chronic lymphocytic leukemia.

Artificial intelligence-based tools designed to assist in the diagnosis of lymphoid neoplasms remain...

Classification of Basal Cell Carcinoma in Ex Vivo Confocal Microscopy Images from Freshly Excised Tissues Using a Deep Learning Algorithm.

Ex vivo confocal microscopy (EVCM) generates digitally colored purple-pink images similar to H&E wit...

CAMAP: Artificial neural networks unveil the role of codon arrangement in modulating MHC-I peptides presentation.

MHC-I associated peptides (MAPs) play a central role in the elimination of virus-infected and neopla...

Development of S4A-BSA-Au NPs for enhanced anti-tumor therapy of canine breast cancer.

S4A ((1,2,3)-1,2-propanediol acetal-zeylenone) is one of the derivatives of zeylenone and exhibits s...

Tumor Region Location and Classification Based on Fuzzy Logic and Region Merging Image Segmentation Algorithm.

Early diagnosis of tumor plays an important role in the improvement of treatment and survival rate o...

Deep learning-based classification of preclinical breast cancer tumor models using chemical exchange saturation transfer magnetic resonance imaging.

Chemical exchange saturation transfer (CEST) magnetic resonance imaging has shown promise for classi...

Environmentally Adaptive Shape-Morphing Microrobots for Localized Cancer Cell Treatment.

Microrobots have attracted considerable attention due to their extensive applications in microobject...

Deep learning radiomics of dual-energy computed tomography for predicting lymph node metastases of pancreatic ductal adenocarcinoma.

PURPOSE: Diagnosis of lymph node metastasis (LNM) is critical for patients with pancreatic ductal ad...

Automatic identification of triple negative breast cancer in ultrasonography using a deep convolutional neural network.

Triple negative (TN) breast cancer is a subtype of breast cancer which is difficult for early detect...

Self-supervised driven consistency training for annotation efficient histopathology image analysis.

Training a neural network with a large labeled dataset is still a dominant paradigm in computational...