Other Cancers

DeepHistoNet: A robust deep-learning model for the classification of hepatocellular, lung, and colon carcinoma.

In recent days, non-communicable diseases (NCDs) require more attention since they require specialized infrastructure for treatment. As per the cancer population registry estimate, nearly 800,000 new cancer cases will be detected yearly. The statistics alarm the need for early cancer detection and diagnosis. Cancer identification can be made either through manual efforts or by computer-aided algor...

Point-wise spatial network for identifying carcinoma at the upper digestive and respiratory tract.

PROBLEM: Artificial intelligence has been widely investigated for diagnosis and treatment strategy design, with some models proposed for detecting oral pharyngeal, nasopharyngeal, or laryngeal carcinoma. However, no comprehensive model has been established for these regions.

Managing Ulcerative Colitis and Crohn's Disease: Should the Target Be Endoscopy, Histology, or Both?

In inflammatory bowel disease (IBD), mucosal healing is the primary long-term treatment goal, encompassing both endoscopic and histological outcomes. ...

Deep learning for tumor margin identification in electromagnetic imaging.

In this work, a novel method for tumor margin identification in electromagnetic imaging is proposed to optimize the tumor removal surgery. This capabi...

Deep Learning Can Predict Bevacizumab Therapeutic Effect and Microsatellite Instability Directly from Histology in Epithelial Ovarian Cancer.

Epithelial ovarian cancer (EOC) remains a significant cause of mortality among gynecologic cancers, with the majority of cases being diagnosed at an a...

A comparison of 18 F-FDG PET-based radiomics and deep learning in predicting regional lymph node metastasis in patients with resectable lung adenocarcinoma: a cross-scanner and temporal validation study.

OBJECTIVE: The performance of 18 F-FDG PET-based radiomics and deep learning in detecting pathological regional nodal metastasis (pN+) in resectable l...

Clinical Feature Ranking Based on Ensemble Machine Learning Reveals Top Survival Factors for Glioblastoma Multiforme.

Glioblastoma multiforme (GM) is a malignant tumor of the central nervous system considered to be highly aggressive and often carrying a terrible survi...

Deep learning to predict lymph node status on pre-operative staging CT in patients with colon cancer.

INTRODUCTION: Lymph node (LN) metastases are an important determinant of survival in patients with colon cancer, but remain difficult to accurately di...

Analysis of cortical cell polarity by imaging flow cytometry.

Metastasis is the main cause of cancer-related death and therapies specifically targeting metastasis are highly needed. Cortical cell polarity (CCP) i...

Robot-assisted fluorescent sentinel lymph node identification in early-stage colon cancer.

BACKGROUND: Patients with cT1-2 colon cancer (CC) have a 10-20% risk of lymph node metastases. Sentinel lymph node identification (SLNi) could improve...

Deep learning in MRI-guided radiation therapy: A systematic review.

Recent advances in MRI-guided radiation therapy (MRgRT) and deep learning techniques encourage fully adaptive radiation therapy (ART), real-time MRI m...

Training of epitope-TCR prediction models with healthy donor-derived cancer-specific T cells.

Discovery of epitope-specific T-cell receptors (TCRs) for cancer therapies is a time consuming and expensive procedure that usually requires a large a...

Gray-to-color image conversion in the classification of breast lesions on ultrasound using pre-trained deep neural networks.

Breast ultrasound (BUS) image classification in benign and malignant classes is often based on pre-trained convolutional neural networks (CNNs) to cop...

Deep learning applied to the histopathological diagnosis of ameloblastomas and ameloblastic carcinomas.

BACKGROUND: Odontogenic tumors (OT) are composed of heterogeneous lesions, which can be benign or malignant, with different behavior and histology. Wi...

Ki67 proliferation index in medullary thyroid carcinoma: a comparative study of multiple counting methods and validation of image analysis and deep learning platforms.

AIMS: The International Medullary Thyroid Carcinoma Grading System, introduced in 2022, mandates evaluation of the Ki67 proliferation index to assign ...

Deep learning-based recurrence detector on magnetic resonance scans in nasopharyngeal carcinoma: A multicenter study.

OBJECTIVES: Accuracy in the detection of recurrent nasopharyngeal carcinoma (NPC) on follow-up magnetic resonance (MR) scans needs to be improved.

Successful Development of a Natural Language Processing Algorithm for Pancreatic Neoplasms and Associated Histologic Features.

OBJECTIVES: Natural language processing (NLP) algorithms can interpret unstructured text for commonly used terms and phrases. Pancreatic pathologies a...

Multicentric Ga-PSMA PET radiomics for treatment response assessment of Lu-PSMA-617 radioligand therapy in patients with metastatic castration-resistant prostate cancer.

OBJECTIVE: The treatment with Lutetium PSMA (Lu-PSMA) in patients with metastatic castration-resistant prostate cancer (mCRPC) has recently been appro...

Prognostic significance of cyclin D1 expression pattern in HPV-negative oral and oropharyngeal carcinoma: A deep-learning approach.

BACKGROUND: We aimed to establish image recognition and survival prediction models using a novel scoring system of cyclin D1 expression pattern in pat...

A robust deep learning workflow to predict CD8 + T-cell epitopes.

BACKGROUND: T-cells play a crucial role in the adaptive immune system by triggering responses against cancer cells and pathogens, while maintaining to...