Oncology/Hematology

Lung Cancer

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

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Showing 2261-2280 of 10,186 articles

Development and Validation of Machine Learning Models for Predicting Initiation of Emergency Dialysis in Advanced Chronic Kidney Disease

BackgroundInitiation of emergency dialysis, often requiring temporary catheter owing to unprepared definitive vascular access, is associated with infectious and vascular complications and suggests advanced chronic kidney disease (CKD) care gaps. Previous studies focused on kidney failure or dialysis timing. This study aimed to predict initiation of emergency dialysis using machine learning and bas...

Dissecting and directing pathology foundation models

Foundation models (FMs) are central to digital pathology, encoding histology images into dense embeddings for facilitating diagnostic classification, molecular alteration prediction, and clinical outcome modeling. However, the opacity of these embeddings renders FM-based systems "black boxes," limiting their trustworthiness for clinical translation and utility for scientific discovery. Here, we in...

A Transformer-derived transcriptomic score associates with ex-vivo drug response in AML

Background Drug-tolerant persister (DTP) cell states have been implicated in relapse across multiple cancers, including acute myeloid leukaemia (AML) ...

Probing, Fusion, and Trustworthiness: A Systematic Evaluation of Foundation Model Representations for Multimodal Cancer Analysis

Foundation models (FMs) have emerged as powerful representation extractors for medical data, yet their generalizability to datasets under distribution...

Jun 15 2026 2606.17115v1
Robust integration of weakly anchored spatial multi-omics

Spatial multi-omics holds great promise for dissecting complex biological processes, though inherent technical constraints continue to limit its wides...

Conversational Artificial Intelligence-Enabled Precision Oncology Reveals Context-Specific TGFβ and JAK/STAT Alterations in Pancreatic Cancer

Background: Pancreatic ductal adenocarcinoma (PDAC) is characterized by extensive molecular complexity, profound stromal remodeling, and limited respo...

DyMoTree decodes early cell state transitions and drivers from single-cell transcriptomes using a tree-structured neural network

Inferring early cell fate from single-cell RNA-sequencing data is essential for identifying cellular origins and fate plasticity in development and di...

Augmentation techniques for video surveillance in the visible and thermal spectral range

In intelligent video surveillance, cameras record image sequences during day and night. Commonly, this demands different sensors. To achieve a better ...

Jun 11 2026 2606.13042v1
Time-Conditioned and Multi-Time Survival Prediction from 2D PET/CT Projections in Lung Cancer

Accurate prediction of overall survival (OS) from positron emission tomography/computed tomography (PET/CT) can support personalized treatment and fol...

Jun 10 2026 2606.12140v1
Boundary-Specific Failure Modes and Safety Trade-offs of Large Language Models in ChronicKidney Disease Renoprotective Therapy Review:A Stratified Synthetic Benchmark

Background.Renoprotective therapies - SGLT2 inhibitors, finerenone, and renin-angiotensin system inhibitors (RASi) - remain underutilisedin chronic ki...

Multi-Algorithm Machine Learning Benchmarking for Pan-Cancer Classification from Tumour-Educated Platelet RNA Sequencing

Tumour-educated platelets (TEPs) carry cancer-type-specific RNA signatures accessible through whole-blood RNA sequencing, but systematic multi-algorit...

ChronoMedicalWorld: A Medical World Model for Learning Patient Trajectories from Longitudinal Care Data

Long-horizon clinical simulation -- predicting how a patient's physiology evolves over years under specified interventions -- is central to chronic-di...

May 21 2026 2605.21963v1
A quantitative proteomics dataset for assessment and prediction of low dose X-ray radiation exposure in mice.

Ionizing radiation induces molecular responses that may be used to estimate exposure when physical dosimeters are unavailable. Here we present two lar...

Engineering Endogenous T Cell Receptors to Recognize Cancer Neoantigens Using a Hybrid Physics-AI Approach

T cell receptors (TCRs) are critical for immune surveillance and successful adaptive immune response against foreign antigens. TCRs drive this key arm...

A Multimodal Neural Network Model for Early Recurrence Prediction in Lung Adenocarcinoma

Lung adenocarcinoma (LUAD), a subtype of non-small cell lung cancer (NSCLC), is the most common primary lung cancer worldwide. Despite advancements in...

Overweight status drives early tumor microenvironment reprogramming in pancreatic ductal adenocarcinoma: a cell-type-resolved Bayesian hierarchical modeling and interactome analysis

Background: Obesity significantly increases the risk of prognosis and clinical outcomes in pancreatic ductal adenocarcinoma (PDAC). While research on ...

Kinome profiling allows examination and prediction of kinase inhibitor cardiotoxicity

Background: Despite improved cancer outcomes with kinase inhibitors (KIs), their cardiotoxicity remains a significant clinical challenge. Current appr...

BRICKS: Compositional Neural Markov Kernels for Zero-Shot Radiation-Matter Simulation

We introduce a new strategy for compositional neural surrogates for radiation-matter interactions, a key task spanning domains from particle physics t...

May 7 2026 2605.06591v1
Interpreting Omics Data Analysis with Large Language Models for Disease Target and Drug Discovery

In biomedical scientific discovery, synthesizing prior knowledge from the literature is an essential component of interpreting numerical omics data an...

Virtual Scanning for NSCLC Histology: Investigating the Discriminatory Power of Synthetic PET

Accurate histological differentiation between adenocarcinoma (ADC) and squamous cell carcinoma (SCC) is critical for personalized treatment in non-sma...

May 4 2026 2605.02746v1
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