Latest AI and machine learning research in oncology/hematology for healthcare professionals.
Accurate brain tumor segmentation from magnetic resonance imaging (MRI) remains a challenging task because supervised deep learning models require large quantities of annotated data, which are expensive and time-consuming to obtain. This study investigates whether synthetic MRI images generated using a Deep Convolutional Generative Adversarial Network (DCGAN) can improve U-Net-based brain tumor se...
Ovarian cancer is recognized as the deadliest gynecological malignancy. Diagnosis at advanced stages and the lack of effective screening program lead to poor survival rates, dropping to 17-39 % in stage III-IV diseases. Ultrasound (US) is the primary imaging modality for ovarian structures evaluation, but it is strongly affected by the operator expertise due to the complexity of adnexal masses and...
In clinical oncology studies, metastatic cancer is commonly evaluated using "Response Evaluation Criteria in Solid Tumors" (RECIST), in which the diam...
Background. Pediatric musculoskeletal trauma represents up to 18% of pediatric ED visits, yet diagnosis still depends on ionizing radiography. Cumulat...
Radiomic biomarkers derived from magnetic resonance imaging (MRI) have been widely investigated as non-invasive tools for tumor characterization and p...
Machine learning models for drug response prediction in cancer cell lines carry the potential to advance precision oncology by tailoring treatments to...
Tumor cellular composition, including malignant cell states, immune populations, and stromal populations, is increasingly recognized as a determinant ...
18F-FDG PET/CT plays a central role in staging, treatment planning, and response assessment for head and neck cancer by providing functional informati...
Accurate grading of cervical biopsies on Hematoxylin and Eosin (H&E) stained whole slide images (WSIs) is essential for distinguishing high grade lesi...
CD19 targeted chimeric antigen receptor (CAR) T cell therapy achieves high initial response rates in B cell acute lymphoblastic leukemia (B ALL), yet ...
Background: Ductal carcinoma in situ (DCIS) is a noninvasive breast lesion with variable risk of progression to invasive breast cancer (IBC). Current ...
H&E whole-slide images capture prognostic information encoded in tumor morphology and the surrounding microenvironment, but these signals remain diffi...
Breast cancer is one of the most widespread types of cancer, affecting approximately 8 million women worldwide. Electronic health records of patients ...
Inferring contrast enhancement from one pre-contrast breast MRI slice is underdetermined: post-contrast appearance contains physiological information ...
BackgroundKRAS mutation status is an important biomarker in rectal cancer, with implications for prognosis and treatment response. MRI-based radiomics...
Adaptive immunity relies on T-cell receptor (TCR) recognition of peptides presented by the major histocompatibility complex (pMHC). Accurate predictio...
The human immune system is composed of [~]30-50 distinct cell types, each of which can exist in different states of activation or differentiation. Ind...
Early and timely screening of laryngeal cancer is crucial for improving clinical outcomes. In recent years, NBI endoscopy has become a standard diagno...
Foundation models have emerged as a driving force in computational pathology, with the potential to transform cancer diagnosis, prognosis, and treatme...
Vision-language models trained with contrastive objectives have shown promise in medical image analysis. However, conventional global image-text align...