Lung Cancer

Successful Application of Artificial Intelligence-Assisted Analysis of Invasive Pulmonary Adenocarcinoma Less Than 6 mm in Size: A Case Report and Literature Review.

INTRODUCTION: Screening of lung nodules helps on early diagnosis of lung cancer, especially invasive pulmonary adenocarcinoma. Artificial intelligence (AI) has been applied in diagnosis of cancers. We used the AI-assisted lung nodule diagnostic system in the screening of lung nodules and lung cancer.

Development of an automated photolysis rates prediction system based on machine learning.

Based on observed meteorological elements, photolysis rates (J-values) and pollutant concentrations, an automated J-values predicting system by machine learning (J-ML) has been developed to reproduce and predict the J-values of OD, NO, HONO, HO, HCHO, and NO, which are the crucial values for the prediction of the atmospheric oxidation capacity (AOC) and secondary pollutant concentrations such as o...

The Association Between Hepatocellular Carcinoma and Gastrointestinal Adenocarcinoma: Is This a New Syndrome in Patients With Cirrhosis? A Case Series.

AIM: This case series aimed to explore the occurrence of synchronous hepatocellular carcinoma (HCC) and gastrointestinal adenocarcinoma in cirrhotic p...

Artificial intelligence-driven microsatellite instability profiling reveals distinctive genetic features in patients with lung cancer.

BACKGROUND: Microsatellite instability (MSI) has emerged as a predictive biomarker for immunotherapy response in various cancers, but its role in non-...

A Novel Deep Learning-based Pathomics Score for Prognostic Stratification in Pancreatic Ductal Adenocarcinoma.

BACKGROUND AND OBJECTIVES: Accurate survival prediction for pancreatic ductal adenocarcinoma (PDAC) is crucial for personalized treatment strategies. ...

Innovations in artificial intelligence for pet/mr imaging: Application and performance analysis.

BackgroundThe primary challenges in PET/MR imaging include prolonged scan durations for both PET and MR components and radiation exposure associated w...

Assessing Algorithmic Fairness With a Multimodal Artificial Intelligence Model in Men of African and Non-African Origin on NRG Oncology Prostate Cancer Phase III Trials.

PURPOSE: Artificial intelligence (AI) tools could improve clinical decision making or exacerbate inequities because of bias. African American (AA) men...

Radiometer Calibration using Machine Learning

Radiometers are crucial instruments in radio astronomy, forming the primary component of nearly all radio telescopes. They measure the intensity of ...

Novel-view X-ray Projection Synthesis through Geometry-Integrated Deep Learning

X-ray imaging plays a crucial role in the medical field, providing essential insights into the internal anatomy of patients for diagnostics, image-g...

Validation of a Digital Pathology-Based Multimodal Artificial Intelligence Biomarker in a Prospective, Real-World Prostate Cancer Cohort Treated with Prostatectomy.

PURPOSE: A multimodal artificial intelligence (MMAI) biomarker was developed using clinical trial data from North American men with localized prostate...

Artificial Intelligence Augmented Medical Imaging Reconstruction in Radiation Therapy

Efficiently acquired and precisely reconstructed imaging are crucial to the success of modern radiation therapy (RT). Computed tomography (CT) and m...

End2end-ALARA: Approaching the ALARA Law in CT Imaging with End-to-end Learning

Computed tomography (CT) examination poses radiation injury to patient. A consensus performing CT imaging is to make the radiation dose as low as re...

A physics-informed deep learning model for predicting beam dose distribution of intensity-modulated radiation therapy treatment plans.

BACKGROUND AND PURPOSE: We aimed to develop a physics-informed deep learning model for beam dose prediction in intensity-modulated radiation therapy (...

MoLPre: A Machine Learning Model to Predict Metastasis of cT1 Solid Lung Cancer.

Given that more than 20% of patients with cT1 solid NSCLC showed nodal or extrathoracic metastasis, early detection of metastasis is crucial and urgen...

PD-L1 Scoring Models for Non-Small Cell Lung Cancer in China: Current Status, AI-Assisted Solutions and Future Perspectives.

Immunotherapy has revolutionized the diagnosis and treatment model for patients with advanced non-small cell lung cancer (NSCLC). Numerous clinical tr...

Opportunistic Screening for Pancreatic Cancer using Computed Tomography Imaging and Radiology Reports

Pancreatic ductal adenocarcinoma (PDAC) is a highly aggressive cancer, with most cases diagnosed at stage IV and a five-year overall survival rate b...

An Explainable Neural Radiomic Sequence Model with Spatiotemporal Continuity for Quantifying 4DCT-based Pulmonary Ventilation

Accurate evaluation of regional lung ventilation is essential for the management and treatment of lung cancer patients, supporting assessments of pu...

Label-free pathological subtyping of non-small cell lung cancer using deep classification and virtual immunohistochemical staining

The differentiation between pathological subtypes of non-small cell lung cancer (NSCLC) is an essential step in guiding treatment options and progno...

Achieving Dependability of AI Execution with Radiation Hardened Processors

The reliance on radiation-hardened hardware, essential for domains requiring high-dependability such as space, nuclear energy and medical applicatio...

Preferential Multi-Objective Bayesian Optimization for Drug Discovery

Despite decades of advancements in automated ligand screening, large-scale drug discovery remains resource-intensive and requires post-processing hi...