Lung Cancer

Towards safer imaging: A comparative study of deep learning-based denoising and iterative reconstruction in intraindividual low-dose CT scans using an in-vivo large animal model.

PURPOSE: Computed tomography (CT) scans are a significant source of medically induced radiation exposure. Novel deep learning-based denoising (DLD) algorithms have been shown to enable diagnostic image quality at lower radiation doses than iterative reconstruction (IR) methods. However, most comparative studies employ low-dose simulations due to ethical constraints. We used real intraindividual an...

Empagliflozin and Rapid Kidney Function Decline Incidence in Type 2 Diabetes: An Exploratory Analysis From the EMPA-REG OUTCOME Trial.

RATIONALE & OBJECTIVE: Kidney function progressively declines in most patients with type 2 diabetes (T2DM). Many develop progressive chronic kidney disease (CKD), but some experience a more rapid decline, with a greater risk of kidney failure and cardiovascular disease. In EMPA-REG OUTCOME, empagliflozin was associated with slower kidney disease progression. This post hoc analysis evaluated the ef...

Comparison Results of Three-Port Robot-Assisted and Uniportal Video-Assisted Lobectomy for Functional Recovery Index in the Treatment of Early Stage Non-small Cell Lung Cancer: A Propensity Score-Matched Analysis.

BACKGROUND: Minimally invasive lobectomy is the standard treatment for early stage non-small cell lung cancer (NSCLC). The aim of this study is to inv...

Deep learning of cell spatial organizations identifies clinically relevant insights in tissue images.

Recent advancements in tissue imaging techniques have facilitated the visualization and identification of various cell types within physiological and ...

AI/ML advances in non-small cell lung cancer biomarker discovery.

Lung cancer is the leading cause of cancer deaths among both men and women, representing approximately 25% of cancer fatalities each year. The treatme...

Robotic Versus Thoracoscopic Sub-lobar Resection for Octogenarians with Clinical Stage IA Non-small Cell Lung Cancer: A Propensity Score-Matched Real-World Study.

BACKGROUND: Minimally invasive sub-lobectomy is sufficient in treating small early-stage non-small cell lung cancer (NSCLC). However, comparison of th...

Advancement of artificial intelligence systems for surveillance endoscopy of Barrett's esophagus.

Barrett's esophagus (BE) is a precursor disease for esophageal adenocarcinoma. Timely detection and treatment has significant influence on patient out...

Secret learning for lung cancer diagnosis-a study with homomorphic encryption, texture analysis and deep learning.

Advanced lung cancer diagnoses from radiographic images include automated detection of lung cancer from CT-Scan images of the lungs. Deep learning is ...

Artificial Intelligence-Powered Assessment of Pathologic Response to Neoadjuvant Atezolizumab in Patients With NSCLC: Results From the LCMC3 Study.

INTRODUCTION: Pathologic response (PathR) by histopathologic assessment of resected specimens may be an early clinical end point associated with long-...

Single-Cell Radiation Response Scoring with the Deep Learning Algorithm CeCILE 2.0.

External stressors, such as ionizing radiation, have massive effects on life, survival, and the ability of mammalian cells to divide. Different types ...

ARCHERY: a prospective observational study of artificial intelligence-based radiotherapy treatment planning for cervical, head and neck and prostate cancer - study protocol.

INTRODUCTION: Fifty per cent of patients with cancer require radiotherapy during their disease course, however, only 10%-40% of patients in low-income...

Clinical evaluation of deep learning and atlas-based auto-segmentation for organs at risk delineation.

Manual delineation of organs at risk and clinical target volumes is essential in radiotherapy planning. Atlas-based auto-segmentation (ABAS) algorithm...

Deep Learning-Guided Dosimetry for Mitigating Local Failure of Patients With Non-Small Cell Lung Cancer Receiving Stereotactic Body Radiation Therapy.

PURPOSE: Non-small cell lung cancer (NSCLC) stereotactic body radiation therapy with 50 Gy/5 fractions is sometimes considered controversial, as the n...

Risk Factors for Developing Low Estimated Glomerular Filtration Rate and Albuminuria in Living Kidney Donors.

RATIONALE & OBJECTIVE: Chronic kidney disease is associated with significant morbidity and mortality in the general population, but little is known ab...

Energy controls wave propagation in a neural network with spatial stimuli.

Nervous system has distinct anisotropy and some intrinsic biophysical properties enable neurons present various firing modes in neural activities. In ...

Examination of alternative eGFR definitions on the performance of deep learning models for detection of chronic kidney disease from fundus photographs.

Deep learning (DL) models have shown promise in detecting chronic kidney disease (CKD) from fundus photographs. However, previous studies have utilize...

Effect of da Vinci robot versus thoracoscopic surgery on lung function and oxidative stress levels in NSCLC patients: a propensity score-matched study.

BACKGROUND: To evaluate the short-term efficacy, lung function, and oxidative stress levels between the robotic-assisted thoracoscopic surgery (RATS) ...

Radiation-induced acoustic signal denoising using a supervised deep learning framework for imaging and therapy monitoring.

Radiation-induced acoustic (RA) imaging is a promising technique for visualizing the invisible radiation energy deposition in tissues, enabling new im...

Clinical and Dosimetric Impact of 2D kV Motion Monitoring and Intervention in Liver Stereotactic Body Radiation Therapy.

PURPOSE: Positional errors resulting from motion are a principal challenge across all disease sites in radiation therapy. This is particularly pertine...

Comparison between vision transformers and convolutional neural networks to predict non-small lung cancer recurrence.

Non-Small cell lung cancer (NSCLC) is one of the most dangerous cancers, with 85% of all new lung cancer diagnoses and a 30-55% of recurrence rate aft...