Oncology/Hematology

Deep learning dosiomics for the pretreatment prediction of radiation dermatitis in nasopharyngeal carcinoma patients treated with radiotherapy.

PURPOSE: To develop a combined dosiomics and deep learning (DL) model for predicting radiation dermatitis (RD) of grade ≥ 2 in patients with nasopharyngeal carcinoma (NPC) after radiation therapy (RT) based on radiation dose distribution.

Random field image representations speed up binary discrimination of brain scans and estimate a phenotype glioblastoma cancer cell model.

MRI brain scans alone are not a definitive measure of dementia. Deep-learning algorithms (DLA) and professional human opinion are necessary for diagnosis. Yet, sample sizes are prohibitively large to train a typical DLA, which itself takes considerable computation time to produce diagnostically useful information from contrasting image features. We introduce analytic simplifications to this proces...

Deep-learning-enabled multi-omics analyses for prediction of future metastasis in cancer.

Metastasis remains the leading cause of cancer-related mortality, yet predicting future metastasis is a major clinical challenge due to the lack of va...

AttentionAML: An Attention-based Deep Learning Framework for Accurate Molecular Categorization of Acute Myeloid Leukemia.

Acute myeloid leukemia (AML) is an aggressive hematopoietic malignancy defined by aberrant clonal expansion of abnormal myeloid progenitor cells. Char...

Explainable AI Model Reveals Informative Mutational Signatures for Cancer-Type Classification.

: The prediction of cancer types is primarily reliant on driver genes and their specific mutations. The advancement in novel omics technologies has le...

Deep-Learning-Based Prediction of t(11;14) in Multiple Myeloma H&E-Stained Samples.

BACKGROUND: Translocation of chromosomes 11 and 14 [t(11;14)(q13;32)] is the most common primary translocation in multiple myeloma (MM). Patients harb...

Plasma and Urine Circulating Tumor DNA Methylation Profiles for Non-Invasive Pancreatic Ductal Adenocarcinoma Detection: Significant Findings in Plasma Only.

Pancreatic ductal adenocarcinoma (PDAC) is a lethal malignancy with limited treatment options, and early detection remains challenging due to the lack...

Development of Explainable Machine Learning Models to Identify Patients at Risk for 1-Year Mortality and New Distant Metastases Postendoprosthetic Reconstruction for Lower Extremity Bone Tumors: A Secondary Analysis of the PARITY Trial.

BACKGROUND: Accurate prediction of postoperative metastasis and mortality risks in patients undergoing lower-limb oncological resection and endoprosth...

Multi-omics and single-cell approaches reveal molecular subtypes and key cell interactions in hepatocellular carcinoma.

INTRODUCTION: Hepatocellular carcinoma is a highly aggressive and heterogeneous malignancy with limited understanding of its heterogeneity.

Single-cell and bulk transcriptome analyses reveal elevated amino acid metabolism promoting tumor-directed immune evasion in colorectal cancer.

INTRODUCTION: Colorectal cancer (CRC), the third most common cancer worldwide, often shows limited responsiveness to immunotherapy due to its predomin...

Metabolic profiles in laryngeal cancer defined two distinct molecular subtypes with divergent prognoses.

BACKGROUND: Laryngeal cancer (LCA) is the second most common type of head and neck malignancy, characterized by high recurrence rates and poor overall...

Quantum machine learning-based electrokinetic mining for the identification of nanoparticles and exosomes with minimal training data.

Synthetic and naturally occurring particles, such as nanoparticles (NPs) and exosomes; a type of extracellular vesicles (EVs), have garnered widesprea...

Immunopeptidomics-guided discovery and characterization of neoantigens for personalized cancer immunotherapy.

Neoantigens have emerged as ideal targets for personalized cancer immunotherapy. We depict the pan-cancer peptide atlas by comprehensively collecting ...

Proteomic analysis reveals modulation of key proteins in follicular thyroid cancer progression.

BACKGROUND: Cytopathology cannot be used to reliably distinguish follicular thyroid adenoma (FTA) from follicular thyroid carcinoma (FTC), the second ...

Exploring the exportin-1 inhibitors for COVID-19 and anticancer treatment.

Nuclear export protein 1, also known as XPO1, plays a crucial role in cellular homeostasis and assists in the nucleocytoplasmic transfer of ribonuclei...

Computational analysis of DEHP's oncogenic role in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) remains a leading cause of cancer-related mortality globally, with many patients diagnosed at advanced stages. Cur...

Metabolic reprogramming and immune microenvironment profiling in clear cell renal cell carcinoma: implications for prognosis, targeted therapy, and drug resistance.

Clear cell renal cell carcinoma (ccRCC) is the most prevalent form of kidney cancer, distinguished by intricate interactions between metabolic reprogr...

DeepCCDS: Interpretable Deep Learning Framework for Predicting Cancer Cell Drug Sensitivity through Characterizing Cancer Driver Signals.

Accurate characterization of cellular states is the foundation for precise prediction of drug sensitivity in cancer cell lines, which in turn is funda...

Lung MRI: Indications, Capabilities, and Techniques- Expert Panel Narrative Review.

Lung MRI provides both structural and functional information across a spectrum of parenchymal and airway pathologies. MRI, using current widely availa...

Deciphering the history of ERK activity from fixed-cell immunofluorescence measurements.

The RAS/ERK pathway plays a central role in diagnosis and therapy for many cancers. ERK activity is highly dynamic within individual cells and drives ...