Latest AI and machine learning research in oncology/hematology for healthcare professionals.
Breast cancer remains a leading cause of cancer-related mortality worldwide, making early detection and accurate treatment response monitoring critical priorities. We present BreastDCEDL, a curated, deep learning-ready dataset comprising pre-treatment 3D Dynamic Contrast-Enhanced MRI (DCE-MRI) scans from 2,070 breast cancer patients drawn from the I-SPY1, I-SPY2, and Duke cohorts, all sourced fr...
In the past, the development of vaccines and immunotherapeutics relied heavily on trial-and-error experimentation and extensive in vivo testing, often requiring years of pre-clinical and clinical trials. Today, artificial intelligence (AI) and deep learning (DL) are actively transforming vaccine and immunotherapeutic design, by (i) offering predictive frameworks that support rapid, data-driven d...
Background: Radiation-induced leukopenia caused by low-dose exposure is frequently associated with Traditional Chinese Medicine (TCM) syndromes like...
AI requires extensive datasets, while medical data is subject to high data protection. Anonymization is essential, but poses a challenge for some re...
High-resolution computed tomography (CT) imaging is essential for medical diagnosis but requires increased radiation exposure, creating a critical t...
Language models (LMs) capabilities have grown with a fast pace over the past decade leading researchers in various disciplines, such as biomedical r...
PURPOSE: Although radiotherapy (RT) is one of the primary treatment modalities used in the treatment of cancer, patients often experience toxicity dur...
PURPOSE: Although the association between cytotoxic T lymphocytes and favorable prognosis in colorectal cancer is well established, the prognostic sig...
Hypoxia and lactate metabolism are both distinctive characteristics of cancerous cells. Head and neck squamous cell carcinoma (HNSCC) is one of the mo...
Single-cell RNA-sequencing (scRNA-seq) coupled with robust computational analysis facilitates the characterization of phenotypic heterogeneity within ...
T cells targeting epitopes in infectious diseases or cancer play a central role in spontaneous and therapy-induced immune responses. Epitope recogniti...
We design an efficient algorithm that outputs a linear classifier for identifying homogeneous subsets (equivalently subcohorts) from large inhomogen...
Cardiac substructures are essential in thoracic radiation therapy planning to minimize risk of radiation-induced heart disease. Deep learning (DL) o...
BACKGROUND: Breast cancer (BC) is the most prevalent cancer among women worldwide, and patients with metastasis to axillary lymph nodes (ALN) experien...
Oral squamous cell carcinoma OSCC is a major global health burden, particularly in several regions across Asia, Africa, and South America, where it ...
Intervertebral discs are avascular and maintain immune privilege. However, during intervertebral disc degeneration (IDD), this barrier is disrupted,...
Despite advances in deep learning for automatic sleep staging, clinical adoption remains limited due to challenges in fair model evaluation, general...
Raman spectroscopy provides intrinsic biochemical profiles of all cellular biomolecules in a segmented manner, promising nondestructive and label-free...
Drug repositioning, which identifies novel therapeutic applications for existing drugs, offers a cost-effective alternative to traditional drug develo...
Brain tumors, regardless of being benign or malignant, pose considerable health risks, with malignant tumors being more perilous due to their swift ...