Other Cancers

Attention2Minority: A salient instance inference-based multiple instance learning for classifying small lesions in whole slide images.

Multiple instance learning (MIL) models have achieved remarkable success in analyzing whole slide im...

Multiparametric MRI-based radiomics model for predicting human papillomavirus status in oropharyngeal squamous cell carcinoma: optimization using oversampling and machine learning techniques.

OBJECTIVES: To develop and validate a multiparametric MRI-based radiomics model with optimal oversam...

Deep learning to predict breast cancer sentinel lymph node status on INSEMA histological images.

BACKGROUND: Sentinel lymph node (SLN) status is a clinically important prognostic biomarker in breas...

Augmented Decision-Making in wound Care: Evaluating the clinical utility of a Deep-Learning model for pressure injury staging.

BACKGROUND: Precise categorization of pressure injury (PI) stages is critical in determining the app...

A Spitzoid Tumor dataset with clinical metadata and Whole Slide Images for Deep Learning models.

Spitzoid tumors (ST) are a group of melanocytic tumors of high diagnostic complexity. Since 1948, wh...

Predictive function of tumor burden-incorporated machine-learning algorithms for overall survival and their value in guiding management decisions in patients with locally advanced nasopharyngeal carcinoma.

OBJECTIVE: Accurate prognostic predictions and personalized decision-making on induction chemotherap...

Classification of Brain Tumor Images Using CNN.

A brain tumor is a serious malignant condition caused by unregulated as well as aberrant cell partit...

Editorial for "Magnetic Resonance Deep Learning Radiomic Model Based on Distinct Metastatic Vascular Patterns for Evaluating Recurrence-Free Survival in Hepatocellular Carcinoma".

Identifying primary tumor site of origin for liver metastases via a combination of handcrafted and deep learning features.

Liver is one of the most common sites for metastases, which can occur on account of primary tumors f...

Volumetric tumor tracking from a single cone-beam X-ray projection image enabled by deep learning.

Radiotherapy serves as a pivotal treatment modality for malignant tumors. However, the accuracy of r...

Initial experience with the da Vinci SP robot-assisted surgical staging of endometrial cancer: a retrospective comparison with conventional laparotomy.

To compare the perioperative outcomes of surgical staging performed using conventional laparotomy (L...

Multimodal hybrid convolutional neural network based brain tumor grade classification.

An abnormal growth or fatty mass of cells in the brain is called a tumor. They can be either healthy...

Applying an artificial intelligence deep learning approach to routine dermatopathological diagnosis of basal cell carcinoma.

BACKGROUND: Institutes of dermatopathology are faced with considerable challenges including a contin...

Deep learning enables the discovery of a novel cuproptosis-inducing molecule for the inhibition of hepatocellular carcinoma.

Hepatocellular carcinoma (HCC) is one of the most common and deadly cancers in the world. The therap...

A multitask deep learning radiomics model for predicting the macrotrabecular-massive subtype and prognosis of hepatocellular carcinoma after hepatic arterial infusion chemotherapy.

BACKGROUND: The macrotrabecular-massive (MTM) is a special subtype of hepatocellular carcinoma (HCC)...

Comparison and evaluation of different deep learning models of synthetic CT generation from CBCT for nasopharynx cancer adaptive proton therapy.

BACKGROUND: Cone-beam computed tomography (CBCT) scanning is used for patient setup in image-guided ...

Artificial Intelligence in Oncological Hybrid Imaging.

BACKGROUND:  Artificial intelligence (AI) applications have become increasingly relevant across a br...

Deep learning-based solid component measuring enabled interpretable prediction of tumor invasiveness for lung adenocarcinoma.

BACKGROUND: The nature of the solid component of subsolid nodules (SSNs) can indicate tumor patholog...

CT-based deep learning model: a novel approach to the preoperative staging in patients with peritoneal metastasis.

Peritoneal metastasis (PM) is a frequent manifestation of advanced abdominal malignancies. Accuratel...

Hybrid chain reaction and selective recognition-based homogeneous dual-fluorescence analysis of circulating tumor cells in clinical ovarian cancer samples.

BACKGROUND: Oncological analysis is important in tumor diagnosis. We constructed a dual-fluorescence...

Tumor classification of gastrointestinal liver metastases using CT-based radiomics and deep learning.

OBJECTIVES: The goal of this study is to demonstrate the performance of radiomics and CNN-based clas...