Latest AI and machine learning research in other cancers for healthcare professionals.
Breast tumor images show low intra-class similarity and suffer from distribution shift, posing challenges for recognition tasks. While increasing the number of labeled training data is a common strategy to improve performance, the high cost of expert annotation is another challenge. Semi-supervised learning methods, e.g., Graph Neural Networks (GNNs), which smooth features via graph topology, have...
The treatment of prostate cancer (PCa) continues to pose substantial clinical challenges. The use of large language models (LLMs) to identify the key molecular determinants of PCa progression, followed by experimental biological validation, helps uncover novel therapeutic targets. We developed hierarchical knowledge-guided LLM for risk gene identification (HKLLM-RG), a PCa risk gene identification...
Head and neck squamous cell carcinoma (HNSCC) is the most prevalent histopathological subtype of head and neck malignancies. Owing to the lack of earl...
Skin aging is driven by the progressive exhaustion of stem cell niches, epigenetic drift, and accumulation of senescent cells, which together promote ...
Segmenting glioblastoma in medical imaging remains challenging due to the tumor's irregular shape, heterogeneous texture, and poorly defined boundarie...
BACKGROUND: The incidence of thyroid cancer has increased markedly in recent years, largely driven by well-differentiated thyroid carcinoma (WDTC). WD...
Tumor-specific DNA methylation profiling in plasma cell-free DNA (cfDNA) offers a promising approach for non-invasive tumor detection. Here, we presen...
UNLABELLED: Glioblastomas are incurable primary brain tumors that depend on neural-like cellular processes, tumor microtubes (TM), to invade the brain...
UNLABELLED: Colorectal cancer is a highly lethal gastrointestinal tract malignancy whose pathogenesis and molecular drivers are not fully understood. ...
Posttransplant lymphoproliferative disorder (PTLD) is the second most common malignancy in thoracic transplant recipients and is associated with poor ...
BACKGROUND: Cancer remains a leading global health burden. Artificial intelligence offers new opportunities to address complex physical and psychologi...
STUDY OBJECTIVES: We investigate a Mamba-based deep learning approach for sleep staging on signals from ANNE One (Sibel Health, Chicago, IL), a non-in...
BACKGROUND: Fibroepithelial breast lesions, including fibroadenomas and phyllodes tumors (PTs), can be difficult to classify on needle biopsy. Misclas...
Oral Squamous Cell Carcinoma (OSCC) is a prevalent and aggressive malignancy where deep learning-based computer-aided diagnosis and prognosis can enha...
BACKGROUND: Before surgical resection of lung tumor, intraoperative biopsy is needed for cancer diagnosis, while current techniques that guide biopsy ...
BACKGROUND: There remains a critical need for prognostic biomarkers of treatment response in epithelial ovarian cancer (EOC). The KELIM score, derived...
Early diagnosis of liver cancer is crucial for developing clinical treatment strategies and improving patient survival rates. However, current diagnos...
PURPOSE: Programmed cell death ligand-1 (PD-L1) is a key prognostic and predictive biomarker for immunotherapy in non-small cell lung cancer (NSCLC). ...
Cancer immunotherapies trigger highly variable responses in patients and in genetically identical mouse models. To assess the intrinsic stochasticity ...
Colorectal cancer (CRC) remains a significant global health concern and is among the leading causes of cancer-related mortality. The disease often pro...