Latest AI and machine learning research in lung cancer for healthcare professionals.
Recent work on computer vision and image processing has relied substantially on open datasets, which allow for an objective comparison of techniques and methodologies. In the area of computational pathology and, more specifically, on colorectal cancer, the dataset NCT-CRC-HE-100K, which consists of 100,000 patches of human tissue stained with Haematoxylin and Eosin has been widely used as a traini...
This study introduces a fusion-based multiomics approach to identifying non-small cell lung cancer (NSCLC)-relevant genes. We evaluated the NSCLC-subtype classification performance of various state-of-the-art machine learning models using single omics and fused multiomics approaches. The models were trained separately on individual omics data sets. Subsequently, a weighted-average-based decision-l...
Late radiation-associated dysphagia after head and neck cancer (HNC) significantly impacts patient’s health and quality of life. Conventional normal t...
Glaucoma is increasingly recognized as a neurodegenerative condition involving both retinal and central nervous system structures. Here, we present an...
The Janus kinase-signal transducer and activator of transcription (JAK-STAT) signaling pathway is a critical mediator of immune regulation, inflammati...
Cytopathology plays a central role in the early detection of cancers such as cervical, lung, and bladder cancer due to its speed, simplicity, and mini...
Large language models are increasingly used to generate patient information in healthcare. However, their ability to communicate complex topics, such ...
Pancreatic cystic lesions (PCLs) are often discovered incidentally on imaging and may progress to pancreatic ductal adenocarcinoma (PDAC). PCLs have a...
Spatial transcriptomics technology remains resource-intensive and unlikely to be routinely adopted for patient care soon. This hinders the development...
Hepatic steatosis (HS) is a common cardiometabolic risk factor frequently present but under-diagnosed in patients with suspected or known coronary art...
Cancer is one of the leading lethal causes worldwide, with enormous impact on healthcare, economy and society. One of the main challenges of clinical ...
Tertiary lymphoid structures (TLSs) within the tumor microenvironment have emerged as potential indicators of treatment response to immune checkpoint ...
Pre-procedural risk prediction of 30-day all-cause mortality after percutaneous coronary intervention (PCI) aids in clinical decision-making and bench...
Accurate estimation of Overall Survival (OS) in Non-Small Cell Lung Cancer (NSCLC) patients provides critical insights for treatment planning. While p...
In medical documentation, vast amounts of unstructured text are generated that are still underutilized in current prognostic models. We investigate th...
Head and neck cancer (HNC) patients face an increased risk of malnutrition due to lifestyle, tumor localization, and treatment effects. While skeletal...
The health consequences of ionizing radiation have long been studied, yet significant uncertainties remain, particularly at low doses. In particular, ...
Microsatellite instability (MSI) is a key biomarker for immunotherapy response and prognosis across multiple cancers, yet its identification from rout...
The ability of pre-trained large language models (LLMs) to rapidly master novel natural language processing tasks holds transformative potential. Howe...
The heterogeneous course of IgA nephropathy limits risk stratification based on static markers. We sought to identify clinical trajectory subgroups us...