Oncology/Hematology

Latest AI and machine learning research in oncology/hematology for healthcare professionals.

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Showing 14881-14900 of 19,058 articles

Towards Automated Neonatal EEG Analysis: Multi-Center Validation of a Reliable Deep Learning Pipeline

To evaluate the reliability and generalization of NeoNaid, a fully automated software tool for neonatal EEG analysis, based on functional brain age (FBA) estimation and sleep staging. NeoNaid combines a multi-task deep learning model with proposed quality control routines detecting artefacts, out-of-distribution inputs, and uncertain predictions. Based on a raw EEG input, it outputs one global FBA...

Quantitative pathology and APOE genotype reveal dementia risk and progression in Lewy body disease

Dementia in Lewy body diseases (LBD) is common and arises through heterogeneous and incompletely understood pathways. Evidence suggests contributions from genetic factors, including APOE ε4 genotype, co-pathology including concomitant Alzheimer’s disease pathology and hypoperfusion related to orthostatic hypotension. However, the relative impact of these factors remains unclear. To address this, w...

Prospective Evaluation of AI Risk Stratification for Triaging Expedited Screening Mammogram Interpretation

To prospectively evaluate the feasibility and performance of expedited screening mammogram interpretation for women identified as high-risk by a deep ...

Understanding the Relationship Between Germ Layer Origin and Cancer Therapy Response: A Systematic Review

Cancer therapeutic response patterns may be fundamentally influenced by embryonic germ layer origin. Emerging evidence suggests mesoderm-derived malig...

Intraoperative Metabolomic-Guided Precision Surgery for Pediatric Brain Tumors: A Systematic Review of Multi-Modal Molecular Imaging Platforms and Artificial Intelligence Integration

Pediatric brain tumors are the leading cause of cancer death in children, with surgical resection critical for survival and neurodevelopment. Intraope...

Urinary miRNA Profiles with Machine Learning for Noninvasive Detection and Prognosis of Urological Malignancies

The need for biomarkers that can noninvasively determine and stratify cancer risk is emerging. MicroRNAs (miRNAs) are stable in urinary exosomes, allo...

An Explainable Hybrid CNN–Transformer Framework with Aquila Optimization for MRI-Based Brain Tumor Classification

Accurate and interpretable brain tumor classification remains a critical challenge due to the heterogeneity of tumor types and the complexity of MRI d...

Discriminating Inflammation from Malignancy with Short-Dynamic Patlak Parametric 18F-FDG PET/CT

Differentiating malignant from inflammatory uptake on 18F-FDG PET/CT remains a major diagnostic challenge, as standardized uptake value (SUV) lacks sp...

A Glioma Stem Cell–Associated Transcriptomic Program Predicts Survival Across Adult and Pediatric High-Grade Gliomas

High-grade gliomas (HGGs), including adult glioblastoma (GBM) and pediatric diffuse intrinsic pontine gliomas (DIPGs), are sustained by glioma stem ce...

Robust methylome analysis and tumour–normal classification in TCGA–COAD: a reproducible workflow

Colorectal adenocarcinoma is caused in part by widespread epigenetic deregulation, yet the analysis of genome-wide DNA methylation of colorectal adeno...

CanBART: A Generative Foundation Model of Cancer Molecular Alterations for Synthetic Patient Generation and Genomic Profile Completion

Despite the rapid expansion of genomic profiling in oncology, real-world datasets remain limited in size and unevenly distributed, particularly for ra...

Quantum Dot Encoding for In-Solution Single-Molecule Biomarker Counting in Metastatic Prostate Cancer

Digital assays are in wide development for biomarker quantification at the single-molecule level, but the common use of surface-pulldown steps limits ...

Advancing Breast Cancer-AI Diagnostics: An Explainable Deep Learning Model Using 2D Grayscale Ultrasound Imaging

Breast cancer stands as the primary reason for fatality in female patients from cancer worldwide. The diagnostic precision of ultrasound imaging depen...

Utilizing Experimental Cognitive Assessments and Machine Learning to Advance Prediction of Cognitive Impairment in Breast Cancer Survivors: A Preliminary Study

Up to 80% of women breast cancer survivors (BCS), particularly those treated with chemotherapy, report persistent cognitive impairment. Several meta-a...

PANCDetect: Early Detection of Pancreatic Cancer from Multimodal EHR data with LLM Embeddings

Pancreatic cancer (PANC) is often diagnosed at late stages due to the absence of specific early symptoms, resulting in one of the highest cancer morta...

Employing Consensus-Based Reasoning with Locally Deployed LLMs for Enabling Structured Data Extraction from Surgical Pathology Reports

Surgical pathology reports provide essential diagnostic information critical for cancer staging, treatment planning, and cancer registry documentation...

Spatial Structure of Tumor and Immune Cells Shape Outcomes in ER⁺HER2⁻ and Triple-Negative Breast Cancer

Immune infiltration is prognostic in triple-negative breast cancer (TNBC), but its role in ER⁺/HER2⁻ disease remains unclear, and conventional scoring...

CSF Proteomics and Machine Learning Reveal Distinct Stages Across the Alzheimer’s Disease Continuum

Alzheimer’s disease (AD) is a neurodegenerative disorder characterized by heterogeneous pathophysiological changes that begin years before symptoms em...

Radiologic, Pathologic, and Deep Learning Predictors of Response to Immune Checkpoint Blockade in Renal Cell Carcinoma Patients Undergoing Post-Treatment Nephrectomy

Response assessment of primary kidney tumors in the consolidation cytoreductive and neoadjuvant settings offers a unique opportunity to inform postope...

Developing a Fully Automated Imaging Biomarker for HCC Risk Assessment via MRI-Based Tumor Segmentation and EPM

This study investigates the feasibility of using automated tumor segmentation as the region of interest for early detection of hepatocellular carcinom...

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