Latest AI and machine learning research in oncology/hematology for healthcare professionals.
Melanoma outcomes have dramatically improved over the past decade, but some patients still experience disease recurrence, particularly those who present at later stage of disease. Prior studies identified an altered immune microenvironment in the sentinel lymph node (SLN) including the presence of dysfunctional CD8 T cells and CD4 T regulatory cells (Tregs), but the spatial organization of the SLN...
Spatial proteomics (highly multiplexed tissue imaging) provides unprecedented insight into the types, states, and spatial organization of cells within preserved tissue environments. To enable single-cell analysis, high-plex images are typically segmented using algorithms that assign marker signals to individual cells. However, conventional segmentation is often imprecise and susceptible to signal ...
Disseminated (DTCs) and circulating tumor cells (CTCs) are rare but pivotal in understanding cancer metastasis and advancing liquid biopsy-based diagn...
Organisation and dynamics of chromatin play a key role in regulation of cell state and function. In cancer, chromatin plasticity is known to be import...
Acute myeloid leukemia (AML) often enters remission after chemotherapy but frequently relapses due to chemotherapy-resistant leukemic stem cells (LSCs...
Long non-coding RNAs (lncRNAs) regulate gene expression through chromatin remodeling, transcriptional control, and post-transcriptional modulation, in...
The growing number of spot-resolution sequencing based spatial transcriptomic (ST) datasets provides an unprecedented opportunity to study multicellul...
While kinase-substrate associations (KSAs) are fundamental to cancer signaling, their rewiring patterns and functional roles across different cancers ...
Estrogen receptor alpha (ER) is an established oncogenic transcription factor in breast and endometrial cancer; however, more is known about the mecha...
Multiplexed imaging technologies now enable the simultaneous profiling of hundreds to thousands of molecular targets in intact tissues, providing unpr...
To deliver clinically relevant insights from large patient cohorts profiled with single-cell technologies, a key challenge is to relate sample-level a...
Recent advances in deep brain stimulation (DBS) of the subcallosal cingulate (SCC) show promise in mitigating the symptoms of treatment-resistant depr...
Estimating the response of tumor cells to specific perturbations is crucial for identifying effective treatments that selectively target cancer cells ...
Molecular heterogeneity in head and neck squamous cell carcinoma (HNSCC) is well recognized, yet existing subtype frameworks remain largely descriptiv...
Investigating accurate cancer survival prediction models has important clinical value for optimizing therapeutic strategies and improving clinical out...
Cell-free DNA (cfDNA) serves as a non-invasive biomarker for cancer detection, but conventional methods face challenges due to the ultra-low abundance...
In this study, we present a comprehensive radiogenomic analysis of pediatric low-grade gliomas (pLGGs), combining treatment-naïve multiparametric MRI ...
Artificial intelligence (AI)-based imaging analysis has applications for the diagnosis of head and neck malignancies, and serum circulating tumor-asso...
To address the diversity of skin conditions and the low prevalence of skin cancers, we curated a large dataset and collected real-world data, to evalu...
Fatigue is commonly identified by IBD patients as major issue that affects their wellbeing. This presentation, however, is complex, multifactorial and...