Oncology/Hematology

XtraLight-MedMamba for Classification of Neoplastic Tubular Adenomas

Accurate risk stratification of precancerous polyps during routine colonoscopy screenings is essential for lowering the risk of developing colorectal cancer (CRC). However, assessment of low-grade dysplasia remains limited by subjective histopathologic interpretation. Advancements in digital pathology and deep learning provide new opportunities to identify subtle and fine morphologic patterns asso...

Do Large Language Models Read or Remember? Analyzing LLM Performance in Biomedical Text Mining With Progressive Content Removal and Counterfactual Results

Purpose: Large language models (LLMs) can classify biomedical documents accurately, but strong performance does not prove they are using the supplied text rather than identifier-triggered parametric knowledge. We tested whether oncology trial-success classification reflects "reading" of abstract evidence or "remembering" of known trials. Methods: We used a corpus of 250 two-arm oncology randomized...

Prediction of Mutations and Outcome in Gastrointestinal Stromal Tumors with Deep Learning: A Multicenter, Multinational Study

Background: Gastrointestinal stromal tumor (GIST) is the most common gastrointestinal mesenchymal tumor, driven by tyrosine-protein kinase KIT and pla...

Can ChatGPT give holistic and accurate patient-centred information to oncology patients? A mixed-methods evaluation with stakeholders

Abstract Objective More people than ever before are living with cancer. Patient education is a core component of cancer care, and patients are increas...

Development and internal validation of risk scores to predict survival in the pediatric population following in-hospital cardiac arrest.

Introduction In-hospital cardiac arrest (IHCA) in the pediatric population is associated with poor survival and neurological outcomes. We aimed to dev...

Improving mortality prediction in critically ill cancer patients with a multidimensional machine learning model

Background: Prognostic assessment in critically ill patients with cancer remains challenging, as conventional ICU severity scores often perform subopt...

Weighted Sum-of-Trees Model for Clustered Data

Clustered data, which arise when observations are nested within groups, are incredibly common in clinical, education, and social science research. Tra...

hSNMF: Hybrid Spatially Regularized NMF for Image-Derived Spatial Transcriptomics

High-resolution spatial transcriptomics platforms, such as Xenium, generate single-cell images that capture both molecular and spatial context, but th...

Transcriptomics-based modeling of methionine metabolism effectively estimates sample-wise DNA methylation activity and epigenetic aging

DNA methylation is a central epigenetic modification that regulates gene expression, maintains genomic stability, and guides cellular differentiation....

NetPolicy-RL: Network-Informed Offline Reinforcement Learning for Pharmacogenomic Drug Prioritization

Large-scale pharmacogenomic screens provide extensive measurements of drug response across diverse cancer cell lines; however, most computational appr...

Data Augmentation for High-Fidelity Generation of CAR-T/NK Immunological Synapse Images

Chimeric antigen receptor (CAR)-T and NK cell immunotherapies have transformed cancer treatment, and recent studies suggest that the quality of the CA...

LLM-Based Annotation and Token-Augmented Modeling for Emotional Tone Classification in Online Cancer Peer-Support Posts

Online cancer peer-support communities generate large volumes of patient-authored and caregiver-authored text that may reflect distress, coping, and i...

Real-World Data for Predicting Rapid Relapse Triple Negative Cancer: A Study Using NCDB and EHR Data

Background: Many patients with triple-negative breast cancer (TNBC), particularly those who are older, Black, or insured by Medicaid, do not receive g...

AI quantification of inflammatory and architectural features in ulcerative colitis distinguishes active disease from remission

Background and Aims: Artificial intelligence (AI) is increasingly applied to histological assessment in inflammatory bowel disease (IBD), but most app...

Predicting Rectal Cancer Patient Survival with Dutch Radiology Reports using Natural Language Processing (NLP): The Role of Pretrained Language Models

The use of Electronic Health Records (EHRs) has increased significantly in recent years. However, a substantial portion of the clinical data remains i...

AcceleRest: A Physiology-Aware Masked Autoencoder for Wrist Accelerometer-based Sleep Staging and Apnea Evaluation

Sleep is essential for physical and mental health, yet large-scale assessment of sleep stages and sleep apnea is limited by the cost and burden of cli...

A multimodal AI biomarker PATH-ORACLE improves prediction of recurrence in stage I lung adenocarcinoma

The standard treatment for stage I lung adenocarcinoma is surgical resection, in most cases without additional systemic adjuvant treatment. A signific...

clinTALL: machine learning-driven multimodal subtypeclassification and treatment outcome prediction in pediatric T-ALL

Background: Childhood T-lineage acute lymphoblastic leukemia (T-ALL) is an aggressive hematologic malignancy with poor prognosis. Differently from B-c...

DVPNet: A New XAI-Based Interpretable Genetic Profiling Framework Using Nucleotide Transformer and Probabilistic Circuits

This research provides an XAI-driven genetic profiling approach that may contribute to scientific discoveries in genetic research. We propose a new ex...

Nab-paclitaxel fused with the de novo designed receptor binder exhibits enhanced tumor targeting and therapeutic efficacy

Chemotherapy has been widely used in cancer treatment, but most of the chemotherapeutic drugs rely mainly on passive accumulation due to lack of targe...