Oncology/Hematology

Radiomics-based unsupervised clustering and deep learning nomogram for response prediction after neoadjuvant chemotherapy in locally advanced laryngeal cancer.

OBJECTIVES: To develop a nomogram model for individualized prediction of neoadjuvant chemotherapy (N...

Machine learning model based on clinical and imaging features for predicting fungal infections in children with leukemia.

BACKGROUND: Due to immunosuppression, mucosal barrier injury, and prolonged neutropenia resulting fr...

EDRNet-based adolescent idiopathic scoliosis screening method using bare-back images.

BACKGROUND: Adolescent idiopathic scoliosis (AIS) affects 2-3% of adolescents. Current screening rel...

Single-cell multi-omics dissection of RevitalAge Markers uncovers age-dependent immunotherapy resistance and druggable targets in melanoma.

Aging-related molecular reprogramming profoundly influences melanoma progression and therapeutic sen...

Integrative spatiotemporal transcriptomics identifies a liver metastasis-related initial cell population associated with the SEMA3A-NRP1 axis in pancreatic ductal adenocarcinoma.

BACKGROUND: Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal malignancy in which liver met...

Application of Hi-C sequencing to detect oncogene rearrangements for diagnosis and treatment of large B-cell lymphoma.

Diffuse large B-cell lymphoma (DLBCL), the most common type of lymphoma, arises from various pathoge...

Ensembling Unets for Rare Chromosomal Aberration Detection in Metaphase Images, Uncertainty Quantification, and Ionizing Radiation Dose Estimation.

In biological dosimetry a radiation dose is estimated using the average number of chromosomal aberra...

Utility of Single-Shot Fast Spin-Echo T2-Weighted MRI With Deep Learning Reconstruction for Assessing Myometrial Invasion in Endometrial Cancer.

OBJECTIVE: To evaluate the clinical feasibility of single-shot fast spin-echo T2-weighted MRI with d...

AI-Driven Preoperative Chest Radiograph Analysis for Prognostic Stratification in Surgically Resected Pathological Stage 1 Non-Small Cell Lung Cancer.

The purpose of the study is to investigate the potential of artificial intelligence (AI)-driven anal...

Abdominal Dual-Energy CT with Deep Learning Reconstruction: Preserving Image Quality and Hepatic Lesion Conspicuity with Reduced Radiation and Contrast.

The objective was to evaluate the image quality and hepatic lesion conspicuity in a dual-low-dose (r...

The potential utility of in-silico approach in identifying phytochemicals against various targets for the management of lung cancer.

Research on novel treatment approaches is crucial for lung cancer, because it is one of the most com...

CORR Insights®: Development and Internal Evaluation of EAST-BMS (East Asian Survival Tool for Bone Metastasis Surgery): A Multinational Machine-learning Survival Prediction Model for Patients Undergoing Surgery for Nonspinal Bone Metastasis in East Asia.

Deep-Learning Solution Providing Molecular Marker Subtyping of Breast Cancer Whole Slide Images: Protocol for a UK Clinical Service Evaluation Study.

BACKGROUND: As the histopathology workforce continues to struggle and service demand continues to in...

Online Intervention on Lung Cancer Screening Among High-Risk Individuals: Pilot Intervention Study.

BACKGROUND: Lung cancer remains the leading cause of cancer deaths in the United States; however, up...

Cellular architecture and neighborhood-informed virtual spatial tumor profiling from histopathology.

The tumor microenvironment (TME) critically shapes disease progression and therapeutic resistance. H...

Integration of multi-omics for precision therapy in breast cancer.

Breast cancer therapy is limited by heterogeneous tumor states and adaptive resistance that may be m...

A preoperative Artificial Intelligence model to estimate cancer-specific mortality in nonmetastatic kidney cancer patients.

Surgical resection is the standard treatment for nonmetastatic renal cell carcinoma, yet survival ou...

Early and late mortality among patients with T1-T3 head and neck squamous cell carcinoma: a machine learning analysis using a SEER population-based cohort study.

Despite advances in the management of head and neck squamous cell carcinoma (HNSCC), mortality withi...

Construction of a diagnostic model for nasopharyngeal carcinoma using a consensus machine learning approach and study of immune infiltration characteristics.

BACKGROUND: Nasopharyngeal carcinoma requires reliable diagnostic biomarkers due to its occult locat...

Causal multi-fidelity surrogate forward and inverse models for ICF implosions.

Continued progress in inertial confinement fusion (ICF) requires solving inverse problems relating e...

A 5mC-related gene signature predicts prognosis and therapy response in hepatocellular carcinoma.

Increasing evidence has highlighted the biological significance of 5-methylcytosine (5mC) DNA modifi...