Breast Cancer

A deep learning based holistic diagnosis system for immunohistochemistry interpretation and molecular subtyping.

BACKGROUND: Breast cancer in different molecular subtypes, which is determined by the overexpression...

Stratification of tumour cell radiation response and metabolic signatures visualization with Raman spectroscopy and explainable convolutional neural network.

Reprogramming of cellular metabolism is a driving factor of tumour progression and radiation therapy...

Modeling 5-FU-Induced Chemotherapy Selection of a Drug-Resistant Cancer Stem Cell Subpopulation.

(1) Background: Cancer stem cells (CSCs) are a subpopulation of cells in a tumor that can self-regen...

Deep match: A zero-shot framework for improved fiducial-free respiratory motion tracking.

BACKGROUND AND PURPOSE: Motion management is essential to reduce normal tissue exposure and maintain...

dbCRAF: a curated knowledgebase for regulation of radiation response in human cancer.

Radiation therapy (RT) is one of the primary treatment modalities of cancer, with 40-60% of cancer p...

Bone age assessment based on three-dimensional ultrasound and artificial intelligence compared with paediatrician-read radiographic bone age: protocol for a prospective, diagnostic accuracy study.

INTRODUCTION: Radiographic bone age (BA) assessment is widely used to evaluate children's growth dis...

Development and Preliminary Validation of a Novel Convolutional Neural Network Model for Predicting Treatment Response in Patients with Unresectable Hepatocellular Carcinoma Receiving Hepatic Arterial Infusion Chemotherapy.

The goal of this study was to evaluate the performance of a convolutional neural network (CNN) with ...

An Innovative Inducer of Platelet Production, Isochlorogenic Acid A, Is Uncovered through the Application of Deep Neural Networks.

(1) Background: Radiation-induced thrombocytopenia (RIT) often occurs in cancer patients undergoing ...

Ultra-low dose chest CT with silver filter and deep learning reconstruction significantly reduces radiation dose and retains quantitative information in the investigation and monitoring of lymphangioleiomyomatosis (LAM).

PURPOSE: Frequent CT scans to quantify lung involvement in cystic lung disease increases radiation e...

Artificial intelligence's impact on breast cancer pathology: a literature review.

This review discusses the profound impact of artificial intelligence (AI) on breast cancer (BC) diag...

Using deep learning-based denoising and iterative reconstruction to reduce radiation exposure - How low can we go?

A Review of deep learning methods for denoising of medical low-dose CT images.

To prevent patients from being exposed to excess of radiation in CT imaging, the most common solutio...

Exploring the role of large language models in radiation emergency response.

In recent times, the field of artificial intelligence (AI) has been transformed by the introduction ...

Deciphering the fibrotic process: mechanism of chronic radiation skin injury fibrosis.

This review explores the mechanisms of chronic radiation-induced skin injury fibrosis, focusing on t...

A Machine Learning Computational Framework Develops a Multiple Programmed Cell Death Index for Improving Clinical Outcomes in Bladder Cancer.

Comprehensive action patterns of programmed cell death (PCD) in bladder cancer (BLCA) have not yet b...

Artificial Intelligence for Breast Ultrasound: Expert Panel Narrative Review.

Breast ultrasound is used in a wide variety of clinical scenarios, including both diagnostic and scr...

Anti-HER2 therapy response assessment for guiding treatment (de-)escalation in early HER2-positive breast cancer using a novel deep learning radiomics model.

OBJECTIVES: Anti-HER2 targeted therapy significantly reduces risk of relapse in HER2 + breast cancer...

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BACKGROUND:: Efficient and accurate delineation of organs at risk (OARs) is a critical procedure for...

Quantitative evaluation of Saliency-Based Explainable artificial intelligence (XAI) methods in Deep Learning-Based mammogram analysis.

BACKGROUND: Explainable Artificial Intelligence (XAI) is prominent in the diagnostics of opaque deep...

Deep learning-based algorithms for low-dose CT imaging: A review.

The computed tomography (CT) technique is extensively employed as an imaging modality in clinical se...

A multiomics analysis-assisted deep learning model identifies a macrophage-oriented module as a potential therapeutic target in colorectal cancer.

Colorectal cancer (CRC) is a common malignancy involving multiple cellular components. The CRC tumor...