Lung Cancer

Establishment of a pathomic-based machine learning model to predict CD276 (B7-H3) expression in colon cancer.

CD276 is a promising prognostic indicator and an attractive therapeutic target in various malignancies. However, current methods for CD276 detection are time-consuming and expensive, limiting extensive studies and applications of CD276. We aimed to develop a pathomic model for CD276 prediction from H&E-stained pathological images, and explore the underlying mechanism of the pathomic features by as...

Management and outcomes of brain metastases from pancreatic adenocarcinoma: a pooled analysis and literature review.

BACKGROUND: Brain metastases (BM) are rare in pancreatic ductal adenocarcinoma (PDAC) and little data exists concerning these patients and their outcomes.

The role of artificial intelligence in informed patient consent for radiotherapy treatments-a case report.

Recent advancements in large language models (LMM; e.g., ChatGPT (OpenAI, San Francisco, California, USA)) have seen widespread use in various fields,...

CT-Based Super-Resolution Deep Learning Models with Attention Mechanisms for Predicting Spread Through Air Spaces of Solid or Part-Solid Lung Adenocarcinoma.

RATIONALE AND OBJECTIVES: Spread through air space (STAS) is a novel invasive pattern of lung adenocarcinoma (LUAD), and preoperative knowledge of STA...

A personalized prediction model for urinary tract infections in type 2 diabetes mellitus using machine learning.

Patients with type 2 diabetes mellitus (T2DM) are at higher risk for urinary tract infections (UTIs), which greatly impacts their quality of life. Dev...

T6496 targeting EGFR mediated by T790M or C797S mutant: machine learning, virtual screening and bioactivity evaluation study.

Acquired resistance to EGFR is a major impediment in lung cancer treatment, highlighting the urgent need to discover novel compounds to overcome EGFR ...

Immune, metabolic landscapes of prognostic signatures for lung adenocarcinoma based on a novel deep learning framework.

Lung adenocarcinoma (LUAD) is a malignant tumor with high lethality, and the aim of this study was to identify promising biomarkers for LUAD. Using th...

Prospective deployment of an automated implementation solution for artificial intelligence translation to clinical radiation oncology.

INTRODUCTION: Artificial intelligence (AI)-based technologies embody countless solutions in radiation oncology, yet translation of AI-assisted softwar...

Enhancing brain metastasis prediction in non-small cell lung cancer: a deep learning-based segmentation and CT radiomics-based ensemble learning model.

BACKGROUND: Brain metastasis (BM) is most common in non-small cell lung cancer (NSCLC) patients. This study aims to enhance BM risk prediction within ...

A deep learning model integrating multisequence MRI to predict EGFR mutation subtype in brain metastases from non-small cell lung cancer.

BACKGROUND: To establish a predictive model based on multisequence magnetic resonance imaging (MRI) using deep learning to identify wild-type (WT) epi...

Ct-based subregional radiomics using hand-crafted and deep learning features for prediction of therapeutic response to anti-PD1 therapy in NSCLC.

PURPOSE: To develop and externally validate subregional radiomics for predicting therapeutic response to anti-PD1 therapy in non-small-cell lung cance...

AS-NeSt: A Novel 3D Deep Learning Model for Radiation Therapy Dose Distribution Prediction in Esophageal Cancer Treatment With Multiple Prescriptions.

PURPOSE: Implementing artificial intelligence technologies allows for the accurate prediction of radiation therapy dose distributions, enhancing treat...

Hydrogel spacer injection to the meso-sigmoid to protect the sigmoid colon in cervical cancer brachytherapy: A technical report.

PURPOSE: The use of a hydrogel spacer inserted into recto-vaginal fossa is a valuable strategy to mitigate radiation exposure to the rectum during rad...

Deep Learning Prediction Boosts Phosphoproteomics-Based Discoveries Through Improved Phosphopeptide Identification.

Shotgun phosphoproteomics enables high-throughput analysis of phosphopeptides in biological samples. One of the primary challenges associated with thi...

Machine Learning Insights Into Uric Acid Elevation With Thiazide Therapy Commencement and Intensification.

Background Elevated serum uric acid, associated with cardiovascular conditions such as atherosclerotic heart disease, hypertension, and heart failure,...

Synergizing photon-counting CT with deep learning: potential enhancements in medical imaging.

This review article highlights the potential of integrating photon-counting computed tomography (CT) and deep learning algorithms in medical imaging t...

Which dose of apixaban is suitable for Asian patients with atrial fibrillation who have a serum creatinine < 1.5 mg/dL but an estimated glomerular filtration rate < 50 mL/min?

INTRODUCTION: Reduced-dose (Low-dose [LD]) apixaban is recommended in patients with atrial fibrillation (AF) who fulfill 2 of 3 criteria: age ≥ 80 yea...

Increased Peripheral Blood DNA Damage and Elevated Serum Levels of Melanoma Inhibitory Activity Protein: Clues to Excess Skin Cancer Risk in Airline Pilots?

Background and objective The risk of malignant melanoma (MM) and other forms of skin cancer appears to be higher in airline pilots (APs), potentially ...

Albumin-Bilirubin (ALBI) Score and Systemic Immune-Inflammation Indexes Used As Pretreatment Outcome Predictors in Patients With Pancreatic Ductal Adenocarcinoma Undergoing Robotic or Open Whipple Procedures: A Logistic Regression Analysis.

Background Pancreatic ductal adenocarcinoma (PDAC) is the most common type of pancreatic cancer (PC) in the United States. In patients with resectable...

Deep learning-based automatic segmentation of cardiac substructures for lung cancers.

PURPOSE: Accurate and comprehensive segmentation of cardiac substructures is crucial for minimizing the risk of radiation-induced heart disease in lun...