Oncology/Hematology

A weakly supervised deep learning-based recurrence prediction and risk stratification of lung adenocarcinoma from pathology whole-slide images.

BACKGROUND: Accurate prediction of postoperative recurrence in lung adenocarcinoma (LUAD) is essential for guiding clinical decision-making and improving patient outcomes. Although various predictive models have been developed, most rely on complex genomic analyses and high-dimensional clinical data. The complexity of these approaches substantially limits their feasibility for routine clinical use...

Machine Learning-Optimized Single-Atom Catalysts Enable Microenvironment-Adaptive Chemodynamic-Bioorthogonal Cancer Therapy.

Chemodynamic therapy (CDT), which harnesses endogenous chemical energy within the tumor microenvironment (TME), has shown high potential for precise cancer treatment. However, its efficacy is often limited by the mildly acidic and reductive nature of the TME that compromises catalyst stability and activity. Developing catalysts capable of maintaining robust performance under such physiological con...

Cell-specific multi-target mechanisms of cotinine in cervical cancer oncogenesis and progression.

BACKGROUND: Cervical cancer is the fourth most common malignant tumor in women globally, with tobacco smoke being a major environmental risk factor. T...

Machine learning-assisted screening of natural product database for the identification of novel chalcone-based derivative as a potent DHODH inhibitor in cancer therapy.

BACKGROUND: Dihydroorotate dehydrogenase (DHODH), an important enzyme in de-novo pyrimidine synthesis, and its dysregulation has been frequently assoc...

Identification of Early Signs of Mental Health Disorders in Older Survivors of Cancer Using Patient-Generated Health Data: Observational Study.

BACKGROUND: Older survivors of cancer face heightened risk of depression and anxiety related to cancer experiences, fear of recurrence, and aging-rela...

Comprehensive framework for evaluation of deep neural networks in detection and quantification of lymphoma from PET/CT images: Clinical insights, pitfalls, and observer agreement analyses.

PURPOSE: This study addresses critical gaps in automated lymphoma segmentation from PET/CT imaging, often overlooked in prior work. While deep learnin...

Application Value of Radiomics-Based Machine Learning for Preoperative Risk Stratification of Bladder Cancer: Systematic Review and Meta-Analysis.

BACKGROUND: Some researchers have explored the application of radiomics-based machine learning to detect preoperative muscle invasion, high-grade tumo...

Toward generalizable prediction of cancer signal using a cell-free DNA language model.

Cell-free DNA can be used for early cancer detection, minimal residual disease monitoring, and post-treatment risk stratification. However, current as...

Plasma metabolomics enhances risk prediction for lung cancer: a population-based validation study.

Metabolic biomarkers offer promising opportunities for lung cancer risk assessment and early detection. This study aimed to identify metabolites with ...

Molecular Landscape and Advanced Diagnostic Technologies for BRAF Mutations in Cancer: From Quantitative PCR and ddPCR to CRISPR-Based Platforms.

BRAF mutations are key oncogenic alterations across multiple malignancies, including melanoma, thyroid carcinoma, colorectal cancer, non-small cell lu...

Matrix-assisted laser desorption/ionization mass spectrometry imaging for spatial clinical oncopathology: diagnosis, margins and therapy.

Clinical oncology increasingly depends on molecular information, but many assays still detach analytes from the histological coordinates in which diag...

RRBP1 promotes osimertinib resistance by activating fatty acid oxidation-dependent metabolic and immune reprogramming in EGFR-Mutant lung adenocarcinoma.

Osimertinib is a third-generation epidermal growth factor receptor (EGFR) tyrosine kinase inhibitor that improves clinical outcomes in patients with E...

New Frontiers of Skin Ultrasound in Precision Medicine.

Ultrasound has emerged as a versatile, non-invasive imaging technique in dermatology, offering real-time, high-resolution visualization of cutaneous s...

Novel method for risk stratification of radiation-induced breast fibrosis: subgroup hypothesis verified by machine learning.

Breast fibrosis (BF) after radiotherapy remains one of the most dreaded late toxicities in breast cancer care, yet multiple additive predictors strugg...

A multidimensional risk prediction framework for malignant intestinal obstruction based on machine learning: computational model development and clinical validation.

Malignant intestinal obstruction (MIO) is a severe complication of advanced cancer. Traditional static assessment models struggle to capture its dynam...

An exploratory multimodal pipeline for recurrence prediction in CRC with XELOX therapy.

Colorectal cancer(CRC) recurrence remains a challenge despite curative surgery and adjuvant therapy. Integrating clinicopathological and liquid biopsy...

Performance of GPT-based large language models in hepatocellular carcinoma stratification: liver function assessment, BCLC staging, and treatment recommendations.

Large language models (LLMs) like GPT have been proposed to support complex clinical decision-making. This study evaluated the performance of GPT-base...

Integrated proteogenomic and metabolomic profiling of acute myeloid leukemias to identify molecular subtypes and associated therapy targets.

Acute myeloid leukemia (AML) is a genetically and phenotypically heterogeneous hematological malignancy. Here, to better define this clinically taxing...

Interpretable machine learning distinguishes skip from continuous metastasis in N1b papillary thyroid carcinoma.

Skip metastasis-defined as lateral lymph node metastasis(N1b) in the absence of central lymph node involvement-represents a distinct yet underrecogniz...

Innovative strategies to overcome cancer drug resistance: from nanodelivery systems to targeted therapeutics.

Cancer drug resistance, driven by complex genetic mutations, epigenetic plasticity, and tumor microenvironment interactions, remains the primary cause...