Latest AI and machine learning research in oncology/hematology for healthcare professionals.
In hematology/oncology clinics, molecular diagnostics based on nucleic acid sequencing or hybridization are routinely employed to detect malignancy-associated genetic mutations and are instrumental in therapeutic stratification and prognostication. However, their limited cost-efficiency constrains their use in pre-malignant screening—specifically, the detection of rare circulating mutant blood cel...
Kinases are enzymes that catalyze phosphorylation and play crucial roles in a myriad of cellular regulatory processes and hemostasis. Patient-specific genetic mutations that aberrantly activate kinases can profoundly influence cancer progression and alter drug efficacy. Predicting the impact of such missense mutations across the human kinome on protein function and cellular signaling is therefore ...
Liquid biopsy-derived circulating tumor cells (CTCs) offer a minimally invasive avenue for precision oncology by enabling longitudinal monitoring of a...
Glioblastoma (GBM), the most aggressive primary brain tumor in adults, exhibits profound treatment resistance and poor prognosis. Despite advances in ...
Accurate and timely diagnosis of colorectal cancer (CRC) is essential for effective treatment and better patient outcomes. This study explores the app...
Spot-based spatial transcriptomics (ST) technologies like 10x Visium quantify genome-wide gene expression and preserve spatial tissue organization. Ho...
Adoptive cell therapy with tumor-infiltrating lymphocytes (ACT-TILs) involves autologous TILs that are expanded ex vivo and then reinfused into the pa...
Hematoxylin and Eosin staining (H&E) is widely used in clinical practice, but efficient and versatile image retrieval tools are lacking. We developed ...
Gene regulatory networks (GRNs), involving interactions between large numbers of genes, govern expression levels of mRNA and their resulting proteins ...
Functional genetic screens have uncovered dependencies in many cancers, but experimentally screened models for most cancers are far outnumbered by mol...
Esophageal-gastric cancers (EC) represent a significant global health concern, with esophageal cancer ranking seventh in terms of incidence and mortal...
Integrating transcriptome-wide single-cell gene expression data with spatial context significantly enhances our understanding of tissue biology, cellu...
Spaceflight presents unique environmental stressors, such as microgravity and radiation, that significantly affect biological systems at the molecular...
Despite growing evidence implicating cellular senescence in tumor progression, methodological challenges in objectively quantifying senescent cell bur...
Determining precise drug concentrations to inhibit cancer cell growth is a critical but resource-intensive challenge, especially for combinations requ...
Circulating blood cell clusters (CCCs) containing red blood cells (RBCs), white blood cells (WBCs), and platelets are significant biomarkers linked to...
Understanding the spatiotemporal dynamics of T-cell clones is a critical challenge in immunology and immunotherapy, with direct implications for cance...
Magnetic resonance imaging (MRI) is essential for visualizing the healthy and diseased brain, yet the cellular basis of MRI signal and how it changes ...
Recurrence related to poor prognosis is a leading cause of mortality in patients with breast cancer (BC). The MammaPrint (MP) genomic assay is designe...
Cell death is a dynamic process that unfolds through time. Live-cell time-lapse imaging captures these dynamics in a way that’s impossible for static ...