Lung Cancer

A lightweight CNN for enhanced non-small cell lung cancer classification using CT scan image.

Lung cancer is a leading cause of cancer-related mortality worldwide, and its early and accurate detection is critical for improving patient outcomes. Computed tomography (CT) scans are widely used to diagnose lung cancer; however, the accuracy of diagnosis often depends on the expertise of radiologists. Recently, deep learning-based clinical decision support systems have shown promise in assistin...

Pathology Public Datasets for Artificial Intelligence: A Systematic Review.

Histopathology plays a crucial role in the diagnosis of many diseases, especially cancers, for which the correct classification of tissue samples significantly influences treatments for patients. The growing use of artificial intelligence (AI) in digital pathology offers opportunities for improving diagnostic process speed, accuracy, and scalability. The availability of well-structured, annotated ...

CT radiomics of adenocarcinoma of the esophagogastric junction: machine learning-based prediction of perineural invasion status.

SMC4/SMAD3/NF-κB axis drives cervical cancer progression and radioresistance via DNA damage repair and immune modulation.

OBJECTIVE: Cervical cancer remains a significant global health burden, with the molecular determinants of its progression and therapeutic resistance n...

Prescription‑dose stratification improves deep learning‑based VMAT dose prediction in locally advanced NSCLC.

Volumetric-modulated arc therapy (VMAT) planning for locally advanced non-small cell lung cancer (NSCLC) is an iterative and planner-dependent process...

Effect of a Computer-Aided Device for Detecting Gastric Neoplasms: A Multicenter, Randomized Controlled Trial.

BACKGROUND & AIMS: Evidence about the effect of artificial intelligence (AI) on upper endoscopy in multicenter, randomized controlled trials is lackin...

Integrating spatial lymph node patterns and multimodal clinicopathological features to predict post-neoadjuvant recurrence in gastric adenocarcinoma: a machine learning nomogram.

Multimodal Deep Learning-Based Screening of Degenerative Temporomandibular Joint Disease Using 2D Radiography: A Cost-Effective and Low-Radiation Approach.

OBJECTIVES: This study aimed to develop and preliminarily validate a multimodal deep learning model based on two-dimensional maxillofacial imaging for...

Artificial intelligence for accurate tumor size assessment and non-invasive adenocarcinoma prediction in small-sized lung cancer.

INTRODUCTION: Accurate preoperative imaging is essential for improving the treatment of small lung cancers. Precise identification of non-invasive ade...

Nitenpyram promotes breast cancer progression via PARP1: Integration of multi-omics analyses with experimental validation.

Nitenpyram (NIT) is an insecticide used primarily for flea control in pets, especially cats and dogs. Some studies suggest that NIT is associated with...

A confidence-based, artificial intelligence pathology model for diagnosis of intrahepatic cholangiocarcinoma.

BACKGROUND: Intrahepatic cholangiocarcinoma (ICCA) is a rare but highly lethal adenocarcinoma arising within the hepatic parenchyma. Diagnosis present...

CLWD: a Chinese histopathology dataset for lung adenocarcinoma subtype classification.

Effective diagnosis and treatment of lung adenocarcinoma depends on accurate typing, subtyping, and grading. Herein, we present the CLWD dataset, a va...

Automatic Hepatic Steatosis Quantification using Low-Dose CT with deep learning-based noise reduction and CT Fat Fraction Analysis Software.

OBJECTIVES: To evaluate the accuracy of CT-derived fat fraction (CDFF) software for quantifying hepatic steatosis at various radiation doses, using MR...

Intelligent model for stratification of acute radiation syndrome severity in humans.

PURPOSE: The aim of this study was to develop and compare two intelligent model for stratifying the severity of acute radiation syndrome (ARS) in huma...

An advanced diagnostic framework for discriminating lung cancer tissue subtypes via the synergy of fourier transform infrared spectroscopy and random forest.

Accurate subtyping of lung cancer is essential for improving patient prognosis and enabling personalized treatment. However, current clinical techniqu...

Systemic Proteome Profiling to Differentiate Primary Glomerular Diseases.

BACKGROUND: Primary glomerulonephritis (GN) is a heterogeneous group of kidney disorders where understanding their pathophysiology remains incomplete....

Machine Learning-Based Preoperative Predicting TERT Promoter Mutation and EGFR Gene Amplification Phenotype in IDH Wild-Type Glioblastoma Using Advanced MR Habitat Imaging.

BACKGROUND AND PURPOSE: The telomerase reverse transcriptase (TERT) gene promoter mutation is a crucial factor for identifying an isocitrate dehydroge...

Ensemble learning on serum metabolic fingerprints for early detection of lung adenocarcinoma.

Lung adenocarcinoma (LUAD) remains a leading cause of cancer-related mortality worldwide, highlighting the urgent need for non-invasive strategies for...

A scoping review of radiation dose and image quality in paediatric CT: Towards safe imaging protocols and diagnostic reference levels in Jordan.

BACKGROUND: Computed tomography (CT) is an essential diagnostic tool, but its associated radiation exposure raises significant concerns, especially fo...

Characterization of Kidney and Liver Cystic Phenotype Associated with GANAB Using Advanced Imaging Biomarkers.

UNLABELLED: : Background and Hypothesis: Monoallelic pathogenic variants in GANAB cause autosomal dominant cystic kidney and liver disease, but quanti...