Oncology/Hematology

Lung Cancer

Latest AI and machine learning research in lung cancer for healthcare professionals.

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The Rise of the Large Language Models (LLMs): Can They Truly Match Clinical and Data Science Experts in Clinical Trial Data Analysis?

Clinical trials provide evidence of the efficacy and safety of experimental treatment regimens. Anal...

Performance of an artificial intelligence foundation model for prostate radiotherapy segmentation

Artificial intelligence (AI) foundation models such as Segment Anything Model 2 (SAM 2) offer potent...

Pancreatic cancer risk prediction using deep sequential modeling of longitudinal diagnostic and medication records

Pancreatic ductal adenocarcinoma (PDAC) is a rare, aggressive cancer often diagnosed late with low s...

Impact of Iron Deficiency on Clinical Outcomes in Congestive Heart Failure: A Retrospective Analysis of Risk Stratification and Mortality

Iron deficiency frequently coexists with congestive heart failure, thereby increasing morbidity and ...

Computational characterization of lymphocyte topology on whole slide images of glomerular diseases

The complexity of distribution of inflammatory cells in the kidney is not well captured by conventio...

Large language models for extracting histopathologic diagnoses of colorectal cancer and dysplasia from electronic health records

Accurate data resources are essential for impactful medical research, but available structured datas...

Persistent Homology and Gabor Features Reveal Inconsistencies Between Widely Used Colorectal Cancer Training and Testing Datasets

Recent work on computer vision and image processing has relied substantially on open datasets, which...

A Fusion-Based Multiomics Classification Approach for Enhanced Gene Discovery in Non-Small Cell Lung Cancer

This study introduces a fusion-based multiomics approach to identifying non-small cell lung cancer (...

Detecting neurodegenerative changes in glaucoma using deep mean kurtosis-curve–corrected tractometry

Glaucoma is increasingly recognized as a neurodegenerative condition involving both retinal and cent...

Clinical-grade autonomous cytopathology via whole-slide edge tomography

Cytopathology plays a central role in the early detection of cancers such as cervical, lung, and bla...

Evaluation of Large Language Model-Generated Patient Information for Communicating Radiation Risk

Large language models are increasingly used to generate patient information in healthcare. However, ...

DeepSpot: Leveraging Spatial Context for Enhanced Spatial Transcriptomics Prediction from H&E Images

Spatial transcriptomics technology remains resource-intensive and unlikely to be routinely adopted f...

SuReCAN: a suite of user-friendly Galaxy machine learning workflows to predict survival and treatment response of cancer patients

Cancer is one of the leading lethal causes worldwide, with enormous impact on healthcare, economy an...

Predicting overall survival of NSCLC patients with clinical, radiomics and deep learning features

Accurate estimation of Overall Survival (OS) in Non-Small Cell Lung Cancer (NSCLC) patients provides...

Large Language Models Improve Cancer Survival Prediction Using Real-World Clinical Notes

In medical documentation, vast amounts of unstructured text are generated that are still underutiliz...

Deep Learning-Assisted Skeletal Muscle Radiation Attenuation at C3 Predicts Survival in Head and Neck Cancer

Head and neck cancer (HNC) patients face an increased risk of malnutrition due to lifestyle, tumor l...

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