AIMC Topic: Lung Neoplasms

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Integrating a Multimodal Digital Device for Continuous Perioperative Monitoring in Patients With Lung Cancer Undergoing Thoracic Surgery: Development and Usability Study.

JMIR mHealth and uHealth
BACKGROUND: Minimally invasive thoracic surgery has improved lung cancer outcomes but requires enhanced postoperative care. Traditionally, the episodic care model has limited timely and multidimensional monitoring of patients. Recent technological ad...

Early Detection of Lung Metastases in Breast Cancer Using YOLOv10 and Transfer Learning: A Diagnostic Accuracy Study.

Medical science monitor : international medical journal of experimental and clinical research
BACKGROUND This study used CT imaging analyzed with deep learning techniques to assess the diagnostic accuracy of lung metastasis detection in patients with breast cancer. The aim of the research was to create and verify a system for detecting malign...

Artificial intelligence-based CT histogram parameters differentiating bronchiolar adenoma and lung adenocarcinomas: A two-center study.

PloS one
PURPOSE: Bronchiolar adenoma (BA) is a rare benign pulmonary neoplasm originating from the bronchial mucosal epithelium and mimics lung adenocarcinoma (LAC) both radiographically and microscopically. This study aimed to develop a nomogram for disting...

Dual-model approach for accurate chest disease detection using GViT and swin transformer V2.

Scientific reports
The precise detection and localization of abnormalities in radiological images are very crucial for clinical diagnosis and treatment planning. To build reliable models, large and annotated datasets are required that contain disease labels and abnorma...

A comparative analysis of heterogeneity in lung cancer screening effectiveness in two randomised controlled trials.

Nature communications
Clinical trials demonstrate that screening can reduce lung cancer mortality by over 20%. However, lung cancer screening effectiveness (reduction in lung cancer specific mortality) may vary by personal risk-factors. Here we evaluate heterogeneity in l...

A Deep Learning Approach for Tracking Colorectal Cancer-Derived Extracellular Vesicles in Colon and Lung Models.

ACS biomaterials science & engineering
According to the International Agency for Research on Cancer and the World Health Organization, colorectal cancer (CRC) is the third most common cancer in the world and the main cause of gastrointestinal cancer-related deaths. Despite advances in the...

NLSTseg: A Pixel-level Lung Cancer Dataset Based on NLST LDCT Images.

Scientific data
Low-dose computed tomography (LDCT) is the most effective tools for early detection of lung cancer. With advancements in artificial intelligence, various Computer-Aided Diagnosis (CAD) systems are now supported in clinical practice. For radiologists ...

CT-based machine learning model integrating intra- and peri-tumoral radiomics features for predicting occult lymph node metastasis in peripheral lung cancer.

Cancer imaging : the official publication of the International Cancer Imaging Society
BACKGROUND: Accurate preoperative assessment of occult lymph node metastasis (OLNM) plays a crucial role in informing therapeutic decision-making for lung cancer patients. Computed tomography (CT) is the most widely used imaging modality for preopera...

TG-Mamba: Leveraging text guidance for predicting tumor mutation burden in lung cancer.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Tumor mutation burden (TMB) is a crucial biomarker for predicting the response of lung cancer patients to immunotherapy. Traditionally, TMB is quantified through whole-exome sequencing (WES), but the high costs and time requirements of WES limit its ...

Deep learning and radiomics fusion for predicting the invasiveness of lung adenocarcinoma within ground glass nodules.

Scientific reports
Microinvasive adenocarcinoma (MIA) and invasive adenocarcinoma (IAC) require distinct treatment strategies and are associated with different prognoses, underscoring the importance of accurate differentiation. This study aims to develop a predictive m...