Lung Cancer

Single-cell and machine learning-based neural regulation signature for prognosis prediction and immunotherapy response in lung adenocarcinoma.

OBJECTIVE: Lung adenocarcinoma (LUAD) molecular heterogeneity limits traditional prognostic models. Given the emerging role of neural regulation (NR) in tumor progression, we aimed to delineate NR-associated cellular phenotypes via single-cell RNA sequencing (scRNA-seq) and develop a robust machine-learning-derived signature (NR.Sig) to precisely assess prognosis and guide personalized immunothera...

Deep Learning for Differentiating Pulmonary Metastasis from Primary Lung Cancer Constructed on Frozen Sections for Intraoperative Diagnosis.

The surgical procedures for primary lung cancer and metastatic lung tumors differ. An intraoperative diagnosis is important for surgical procedure decisions. This study digitized frozen sections for intraoperative diagnosis, developing and evaluating deep learning models to differentiate lung cancer from metastatic tumors. A total of 1,668 slides from 1,458 patients with lung cancer or metastatic ...

ADC Target Profiling in NSCLC: Generalizable AI Separates TROP-2 and cMET Phenotypes.

PURPOSE: Antibody-drug conjugates (ADC) targeting trophoblast cell surface antigen 2 (TROP-2) and cMET are entering clinical trials in non-small cell ...

AI-Powered Deep Visual Proteomics Reveals Critical Molecular Transitions in Pancreatic Cancer Precursors.

UNLABELLED: Pancreatic ductal adenocarcinoma (PDAC) evolves through precursors, yet the protein programs governing early progression remain poorly def...

Developing a machine learning model to predict renal function decline within three years using one-year longitudinal data in patients with type 2 diabetes.

AIMS: The increasing prevalence of type 2 diabetes mellitus (T2DM) has led to an increase in diabetic kidney disease (DKD), which is presently a major...

Optimisation of radiation dose and image quality in paediatric chest and abdominal CT examinations: A systematic review.

INTRODUCTION: Computed tomography (CT) is indispensable for the rapid evaluation of paediatric chest and abdominal pathology, yet it delivers relative...

The Big Data Science Center at the Shanghai Synchrotron Radiation Facility: the architecture of the superfacility.

In the context of the global big data deluge, concerted efforts are being made to address the challenges faced by large scientific facilities. These e...

Uncertainty quantification of U-Net based segmentation tool using conformal prediction.

BACKGROUND: The radiation therapy treatment process is very labour intensive, and artificial intelligence (AI) based auto contouring tools are increas...

Multitask learning of longitudinal circulating biomarkers and clinical outcomes: identification of optimal machine-learning and deep-learning models.

BACKGROUND: Many circulating biomarkers are assessed at different time intervals during clinical studies. Despite of the success of standard joint mod...

Semi-supervised YOLO-DEP for high-resolution X-ray component localization and counting.

Accurate localization and counting of tiny electronic components in high-resolution X-ray images is a critical yet challenging task in nuclear science...

Prognostic models for diabetic kidney disease outcomes: A systematic review.

OBJECTIVE: This systematic review aimed to systematically evaluate the methodological quality and predictive performance of existing prognostic models...

AI-Augmented Fluorescence Imaging of Non-Small Cell Lung Cancer Protease Activity via a Dual-Enzyme Nanoprobe.

Protease activity mapping plays a vital role in understanding tumor microenvironments and developing diagnostic tools. However, simultaneous quantific...

APOBEC mutational signatures predict immune checkpoint inhibitor benefit in TMB-low metastatic NSCLC independent of PD-L1 status.

BACKGROUND: ∼60%-70% of patients with metastatic non-small cell lung cancer (NSCLC) have relatively low tumor mutational burden (TMB), with limited bi...

Lung ultrasound in interstitial lung disease: from bedside screening to prognostic integration and AI-assisted standardization.

Interstitial lung diseases (ILDs) require early recognition and longitudinal assessment, yet repeated high-resolution computed tomography (HRCT) is of...

Deep learning analysis of ECGs detects Cardiovascular-Kidney-Metabolic syndrome burden in people with diabetes: a report from the Silesia Diabetes-Heart Project.

BACKGROUND: Cardiovascular-kidney-metabolic (CKM) syndrome refers to the co-occurrence of obesity, diabetes, chronic kidney disease (CKD), and cardiov...

Comparative study of radiomics features between ASL and DSC perfusion-weighted imaging in distinguishing radiation-induced brain injury from glioma recurrence.

OBJECTIVE: To compare the radiomics features of pseudocontinuous arterial spin labeling (ASL) and dynamic susceptibility contrast (DSC) perfusion-weig...

Effects of Telerehabilitation Based on Motion Recognition Technology on Exercise Endurance of Patients With Non-Small Cell Lung Cancer After Surgery: Single-Center, Prospective, Open-Label, Randomized Controlled Trial.

BACKGROUND: Non-small cell lung cancer (NSCLC) accounts for approximately 85% of primary pulmonary neoplasms. Complete surgical removal remains the co...

Neural Representation Learning for Compact and Efficient Modeling of Monte Carlo Phase Space Data.

PURPOSE: Monte Carlo (MC) simulations provide gold standard dose calculations in radiation therapy but generate large phase space (PHSP) files that li...

Comparative analysis of CNN-LSTM and CNN-BiLSTM hybrid deep learning models for solar radiation prediction.

Solar radiation forecasting is a complex task since the radiation signal is nonlinear, intermittent and is significantly influenced by meteorological ...

Radiation Resilient Synthetic Antiferromagnets-Based Neuromorphic Device for Sea Surface Temperature Reconstruction.

Reconstruction of sea surface temperature is critical for marine monitoring, yet conventional edge devices based on complementary metal-oxide-semicond...