Breast Cancer

Identifying breast cancer subtypes and exploring spatial expression patterns of the key subtype-specific gene based on pathological images, single-cell sequencing, and spatial transcriptomic data.

BACKGROUND: Breast cancer (BRCA) is a heterogeneous disease. Accurate prognosis and molecular subtypes are critical for personalized treatment in BRCA. This study aimed to identify prognostic subtypes of BRCA based on features derived from pathological images and to explore their potential molecular and cellular mechanisms using spatial transcriptomics (ST) and single-cell RNA sequencing (scRNA-se...

Integrating artificial intelligence into cancers of unknown primary diagnosis and treatment.

Cancers of unknown primary (CUP) refer to a highly heterogeneous group of metastatic tumors whose primary site remains undetectable despite comprehensive conventional evaluations. Characterized by obscure primary origins and extremely poor prognosis, the pathogenesis of CUP remains incompletely elucidated. Empirical chemotherapy, the traditional mainstay of treatment, yields limited efficacy, whil...

Predicting PPOI secondary to laparoscopic radical resection of rectal cancer combined with lobaplatin hyperthermic intraperitoneal chemotherapy: a multi-center study.

PURPOSE: PPOI is one of the common complications of intraperitoneal hyperthermic chemotherapy during laparoscopic radical resection of rectal cancer, ...

Postoperative Inflammatory and Nutritional Biomarkers for Predicting Anastomotic Leakage After Ovarian Cancer Surgery: A Multicenter Study.

BackgroundUltra-radical cytoreductive surgery is frequently performed for patients with advanced ovarian cancer (OC). However, anastomotic leakage (AL...

Deep learning based time series analysis for breathing phase prediction in phase-gated proton therapy.

OBJECTIVE: Phase gating is a critical technique to mitigate tumor motion during radiotherapy, particularly in spot-scanned particle therapy (SSPT) whe...

Fatty acid synthesis therapy-induced senescence (FASTIS) in cancer cells.

Therapy-induced senescence (TIS) in cancer cells can be triggered by radiotherapy, chemotherapy, and certain targeted therapeutics. Here, we demonstra...

Predicting early-stage breast cancer disease-free survival and adjuvant therapy benefit from multimodal information using deep learning.

Accurate prediction of disease-free survival (DFS) is essential for tailoring adjuvant regimens and improving clinical outcomes in early-stage breast ...

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 (NAC) response in locally advanced laryngeal cancer ...

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 from both the disease and chemotherapy, along with t...

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

BACKGROUND: Adolescent idiopathic scoliosis (AIS) affects 2-3% of adolescents. Current screening relies on X-rays, which limits large-scale applicatio...

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 aberrations per peripheral blood lymphocytes. This analy...

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 (radiation and contrast volume) upper abdominal dual...

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 increase, it has become prudent to consider viable a...

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

Continued progress in inertial confinement fusion (ICF) requires solving inverse problems relating experimental observations to simulation input param...

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 modification in regulating tumorigenesis and cancer prog...

Nanorobotics at a crossroads: an overview of design, propulsion, and applications.

Nanobots are small nanoscale devices designed to perform highly specific tasks in precisely targeted areas, representing a promising approach in the d...

An Aptamer-Engineered Phenotyping System for Extracellular Vesicles Based on Honeycomb-like Melamine-Formaldehyde Microspheres and Carbon Dot Nanozymes.

Molecular phenotyping of extracellular vesicles (EVs) holds promise for noninvasive cancer diagnosis; however, current methodologies encounter limitat...

Unlocking precision diagnostics: A multimodal framework integrating metabolomics with advanced machine learning techniques.

Integrating multiple omics modalities is a crucial strategy in cancer research, particularly in metabolomics, enabling early detection and detailed ex...

Oncotype DX: Clinical Utility, Evidence, and Future Trends in Personalized Breast Cancer Management.

The Oncotype DX assay has revolutionized the management of early-stage, hormone receptor-positive, HER2-negative breast cancer. Developed in 2004, it ...

A Review of the Australian MRI Linac Program: From Pie in the Sky to Research Milestone.

The Australian Magnetic Resonance Imaging (MRI) Linear Accelerator program (MRI linac) was a major research project that aimed to build and test a uni...