Lung Cancer

Technological advances in body CT: a primer for beginners.

Many technological advances have entered the clinical routine of Computed Tomography (CT) imaging. The new CT scanners have specific solutions in gantry design to bear the mechanical solicitations. The X-ray tubes have been improved for faster acquisitions at low radiation exposure, while the innovations in CT detectors provide a better image quality. The optimization of image quality and contrast...

Artificial Intelligence for Image Registration in Radiation Oncology.

Automatic image registration plays an important role in many aspects of the radiation oncology workflow ranging from treatment simulation, image guided and adaptive radiotherapy, motion management and response evaluation. Traditional automatic registration algorithms are often time-consuming and further improvements in registration accuracy are required. Recently, a variety of AI-driven strategies...

Quality Assurance for AI-Based Applications in Radiation Therapy.

Recent advancements in artificial intelligence (AI) in the domain of radiation therapy (RT) and their integration into modern software-based systems r...

Ethical Aspects of Artificial Intelligence in Radiation Oncology.

Radiation oncology is a field that heavily relies on new technology. Data science and artificial intelligence will have an important role in the entir...

DEMoS: a deep learning-based ensemble approach for predicting the molecular subtypes of gastric adenocarcinomas from histopathological images.

MOTIVATION: The molecular subtyping of gastric cancer (adenocarcinoma) into four main subtypes based on integrated multiomics profiles, as proposed by...

Clinical validation of deep learning algorithms for radiotherapy targeting of non-small-cell lung cancer: an observational study.

BACKGROUND: Artificial intelligence (AI) and deep learning have shown great potential in streamlining clinical tasks. However, most studies remain con...

Clinical significance of hepatic function in Graves disease with type 2 diabetic mellitus: A single-center retrospective cross-sectional study in Taiwan.

Graves disease (GD) and type 2 diabetes mellitus (T2DM) both impair liver function; we therefore explored the possibility of a relationship among diab...

Complex dynamics in a Hopfield neural network under electromagnetic induction and electromagnetic radiation.

Due to the potential difference between two neurons and that between the inner and outer membranes of an individual neuron, the neural network is alwa...

Influence of Robot-Assisted Partial Nephrectomy on Long-Term Renal Function as Assessed Using 99m-Tc DTPA Renal Scintigraphy.

The long-term split renal function after robot-assisted partial nephrectomy (RAPN) is yet to be elucidated. This study aimed to assess long-term rena...

[Two Cases of Robot-Assisted Total Pelvic Exenteration and Intracorporeal Ileal Conduit for Locally Advanced Rectal Cancer].

We describe two cases of locally advanced rectal cancer (LARC) treated with robot-assisted total pelvic exenteration (Ra-TPE) and intracorporeal ileal...

Predictors of Toxicity Among Older Adults with Cancer.

An increasing number of cancer patients are of advanced age as the incidence of cancer increases with age. In this article, the clinical predictors of...

"White bile" as a result of a malignant bile obstruction.

An 87-year-old female was admitted for endoscopic retrograde cholangiopancreatography (ERCP) due to obstructive jaundice. On admission, total bilirubi...

Knowledge distillation circumvents nonlinearity for optical convolutional neural networks.

In recent years, convolutional neural networks (CNNs) have enabled ubiquitous image processing applications. As such, CNNs require fast forward propag...

[Experience of Thoracotomy and Robot-assisted Bronchial Sleeve Resection 
after Neoadjuvant Chemoimmunotherapy for Local Advanced Central Lung Cancer].

BACKGROUND: Immunoneoadjuvant therapy opens a new prospect for local advanced lung cancer. The aim of our study was to explore the safety and feasibil...

Using the da Vinci X® - System for Esophageal Surgery.

Robotic esophageal surgery is becoming more widely adopted. Several publications on the feasibility, short-term outcomes and technical aspects are ava...

Risk of Developing Breast Reconstruction Complications: A Machine-Learning Nomogram for Individualized Risk Estimation with and without Postmastectomy Radiation Therapy.

BACKGROUND: The purpose of this study was to create a nomogram using machine learning models predicting risk of breast reconstruction complications wi...

Predicting pancreatic ductal adenocarcinoma using artificial intelligence analysis of pre-diagnostic computed tomography images.

BACKGROUND: Early stage diagnosis of Pancreatic Ductal Adenocarcinoma (PDAC) is challenging due to the lack of specific diagnostic biomarkers. However...

Machine learning analyses of highly-multiplexed immunofluorescence identifies distinct tumor and stromal cell populations in primary pancreatic tumors.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a formidable challenge for patients and clinicians.

Low-dose CT noise reduction based on local total variation and improved wavelet residual CNN.

BACKGROUND: Low-dose computed tomography (LDCT) is an effective method for reducing radiation exposure. However, reducing radiation dose leads to cons...

Weakly Supervised Learning for Poorly Differentiated Adenocarcinoma Classification in GastricEndoscopic Submucosal Dissection Whole Slide Images.

Endoscopic submucosal dissection (ESD) is the preferred technique for treating early gastric cancers including poorly differentiated adenocarcinoma w...