Oncology/Hematology

Tech That Scales: A Practical Framework for Artificial Intelligence-Enabled Cancer Care in Low- and Middle-Income Countries and Underserved US Counties.

Cancer outcomes remain starkly unequal: 5-year survival rates for common malignancies in low- and middle-income countries (LMICs) often lag 20-40 percentage points behind high-income benchmarks, and similar disparities persist between well-resourced metropolitan centers and rural or safety-net settings within high-income countries. The gap is driven less by the absence of effective interventions t...

Prediction of trajectories and outcomes in early-stage metabolic dysfunction-associated steatotic liver disease: a narrative review.

Metabolic dysfunction-associated steatotic liver disease (MASLD) is the most prevalent chronic liver disorder, with manifestations ranging from steatosis to steatohepatitis, advanced fibrosis, cirrhosis, and hepatocellular carcinoma. At all stages, MASLD is also associated with increased risks of cardiovascular disease, type 2 diabetes, and extrahepatic malignancies. Timely and accurate prediction...

Artificial Intelligence in Colonoscopy Surveillance for Lynch Syndrome: Emerging Evidence, Lessons Learned From Average-Risk Populations, and Future Directions.

Lynch syndrome (LS) is the most common hereditary colorectal cancer (CRC) syndrome and is characterized by an accelerated adenoma-carcinoma sequence, ...

Identification of PANoptosis-Related Biomarkers in Head and Neck Squamous Cell Carcinoma.

BACKGROUND: The early detection and diagnosis of head and neck squamous cell carcinoma (HNSCC) pose significant challenges. OBJECTIVES: This study exp...

Toward clinical value, not just accuracy: deep learning segmentation of soft tissue sarcoma.

Artificial intelligence enhances cancer cell selection for HER2 gene amplification assessment in breast carcinoma.

The evaluation of HER2 gene amplification is a time-consuming process that requires quantifying a large number of signals in cancer cells to ensure re...

Metabolomic analysis for diagnosis of oral squamous cell carcinoma using machine learning.

Enhanced ResU-Net for brain tumor segmentation using EfficientNetB0, Channel Attention, and ASPP.

Accurate and efficient segmentation of brain tumors is critical for diagnosis, treatment planning, and monitoring in clinical practice. In this study,...

Deep learning-based multimodal radiopathomics for preoperative prediction of lymph node metastasis in papillary thyroid carcinoma.

Papillary thyroid carcinoma (PTC) exhibits a high incidence and a strong propensity for lymph node metastasis (LNM). Accurate preoperative assessment ...

Hybrid diagnostic framework for bone cancer detection using deep learning and radiomics analysis.

Currently, bone cancer remains a big challenge in healthcare, early and accurate diagnosis is therefore key to achieving the required treatment outcom...

Gene-level gut microbiome signatures as predictive biomarkers for response to immune checkpoint inhibitors across multiple cancer types.

Targeting programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte-associated protein 4 (CTLA-4) with immune checkpoint inhibitors (ICIs) has...

3D vessel reconstruction from sparse-view dynamic DSA images via vessel probability guided attenuation learning.

Digital Subtraction Angiography (DSA) is one of the gold standards for vascular disease diagnosis. With the help of a contrast agent, time-resolved 2D...

Integrating multi-omics data for enhanced prognosis prediction in gastric cancer post-neoadjuvant therapy.

BACKGROUND: Neoadjuvant therapy is crucial for locally advanced gastric cancer (LAGC), yet response varies significantly. Traditional models based on ...

Multidimensional transcriptomic analysis and in vitro experiments dissect the landscape of 2',2',4',4'-Tetrabromodiphenyl ether in bladder cancer progression.

2',2',4',4'-Tetrabromodiphenyl ether (BDE-47), the most widespread congener of polybrominated diphenyl ethers, has attracted considerable attention du...

Development and Validation of an Interpretable Machine Learning Model for Predicting Distant Metastasis in Tongue Squamous Cell Carcinoma: A Multicentre Study.

INTRODUCTION AND AIMS: Distant metastasis (DM) in tongue squamous cell carcinoma is associated with poor prognosis. However, reliable tools for immedi...

MechanoAge, a machine learning platform to identify individuals susceptible to breast cancer based on mechanical properties of single cells.

BACKGROUND: Emerging evidence links cellular ageing and biophysical alterations with cancer susceptibility. Existing breast cancer risk models inadequ...

A structure-based virtual screening approach to identify novel anaplastic lymphoma kinase inhibitors.

CONTEXT: Anaplastic lymphoma kinase (ALK) is a receptor tyrosine kinase that plays a crucial role in cellular signaling and is implicated in several c...

IL11⁺ fibroblasts are implicated in non-response to anti-TNFα via fibrosis in inflammatory bowel disease.

Inflammatory bowel disease (IBD) is frequently accompanied by intestinal fibrosis, with non-response (NR) to long-term anti-tumor necrosis factor α (a...

DNA methylation-based classification of hematolymphoid neoplasms.

Accurate pathological diagnosis of hematolymphoid neoplasms (HLN) is often challenging due to their complexity and heterogeneity. Genome-wide DNA meth...

Fast Occupational Upper-Limb Radiation Dose Prediction Using Machine Learning and Monte Carlo Simulation.

OBJECTIVE: Interventional procedures expose physicians to scattered radiation, particularly to their upper extremities, posing occupational health ris...