Latest AI and machine learning research in oncology/hematology for healthcare professionals.
Quantitative systems pharmacology (QSP) models require calibration data from published literature, yet manual curation produces inconsistent documentation while large language model (LLM) extraction exhibits hallucination and fabrication errors unacceptable for quantitative modeling. We present MAPLE (Model-Aware Parameterization from Literature Evidence), a framework that uses structured validati...
Renal cell carcinoma (RCC) with venous tumor thrombus, termed renal intravascular tumor extension (RITE), is associated with aggressive behavior and poor clinical outcomes. Yet, its underlying molecular determinants remain incompletely defined. We analyzed RNA sequencing data from three independent RCC cohorts comprising 721 samples. Two cohorts included matched samples of index tumor, tumor throm...
Purpose/Objective: Brain tumors result in 20 years of lost life on average. Standard therapies induce complex structural changes in the brain that are...
Triple-negative breast cancer (TNBC) is an aggressive subtype characterized by limited therapeutic options and poor prognosis. To address these challe...
Precise prognostic modeling of glioblastoma (GBM) under varying treatment interventions is essential for optimizing clinical outcomes. While generativ...
Accurate tumor analysis is central to clinical radiology and precision oncology, where early detection, reliable lesion characterization, and patholog...
Predicting tumor evolution during radiotherapy is a clinically critical challenge, particularly when longitudinal changes are driven by both anatomy a...
Accurate detection of cancer tissue regions (CTR) enables deeper analysis of the tumor microenvironment and offers crucial insights into treatment res...
Artificial intelligence-based radiation therapy (RT) planning has the potential to reduce planning time and inter-planner variability, improving effic...
Introduction: Manual data extraction from unstructured clinical notes is labor-intensive and impractical for large-scale clinical and research operati...
Importance: Lung cancer mortality in the United States has fallen substantially in recent decades, yet the relative influence of behavioral, environme...
Thyroid carcinoma is one of the most prevalent endocrine malignancies worldwide, and accurate preoperative differentiation between benign and malignan...
Accurate classification of BRCA1 and BRCA2 variants is essential for cancer risk assessment and therapy selection, yet over one-third remain variants ...
DNA extracted from tissue samples typically derive from of a complex mixture of cell types. Without single cell analysis, it has been generally imposs...
Alternative lengthening of telomeres (ALT) is a telomerase-independent pathway used by aggressive cancers to maintain their replicative immortality. B...
Resistance to systemic therapy is a major unmet challenge in pancreatic cancer. To identify potential mechanisms of resistance, we developed a novel 3...
We present Meta-D, an architecture that explicitly leverages categorical scanner metadata such as MRI sequence and plane orientation to guide feature ...
Prostate cancer being one of the frequently diagnosed malignancy in men, the rising demand for biopsies places a severe workload on pathologists. The ...
Glioblastoma exhibits diverse, infiltrative, and patient-specific growth patterns that are only partially visible on routine MRI, making it difficult ...
Purpose: Large language models (LLMs) are used for biomedical text processing, but individual decisions are often hard to audit. We evaluated whether ...