Breast Cancer

LKCAU-Net: A Large Kernel Coordinated Attention U-Net for Breast Tumors Segmentation in Ultrasound Images.

Breast cancer remains a significant health concern for women worldwide. Ultrasound imaging is widely adopted for screening due to its non-invasive and radiation-free nature. However, challenges such as low image contrast, blurred tumor boundaries, and diverse tumor morphologies severely hinder accurate segmentation. To address these issues, we propose LKCAU-Net, a novel hybrid multi-scale network ...

Image sharpening improves the visibility of reference points on low-dose lateral cephalometric radiographs: a phantom study.

This phantom study aimed to determine whether a novel non-artificial intelligence image-sharpening approach improves the visibility of reference points on low-dose lateral cephalometric radiographs. Lateral cephalometric radiographs were obtained using an adult human bone phantom at 100% of the routine dose. Low-dose imaging was performed using 60, 40, and 20% of the routine dose. Each low-dose im...

Artificial intelligence-based prediction of claudin 18.2 expression and immune phenotype from routine histology to guide treatment decisions in patients with gastric cancer.

BACKGROUND: First-line treatment of gastric cancer is evolving with the integration of immune checkpoint inhibitors (ICIs) and targeted agents, compli...

Optical Spectral Fingerprinting Enables Sensitive Detection of Anthracycline Chemotherapeutics in Synthetic Clinical Biofluids.

Anthracycline chemotherapeutics are common chemotherapeutics that have substantial toxicities. There is substantial interpatient pharmacokinetic varia...

Prediction of pathological complete response to neoadjuvant therapy in breast cancer integrating intratumoral and peritumoral delta radiomics with clinical features: a study based on multiparametric MRI.

BACKGROUND: To develop a combined model integrating intratumoral and peritumoral delta-radiomics from multi-parametric MRI with clinical features for ...

Artificial intelligence-detected HER2 strong-positive tumor proportion predicts FISH positivity and treatment response in breast cancer.

Human epidermal growth factor receptor 2 (HER2)-targeted therapies have revolutionized breast cancer treatment, necessitating standardized HER2 testin...

M3FusionNet: Cross-cohort multimodal prediction of breast cancer biomarkers.

BACKGROUND: Accurate prediction of breast cancer biomarkers - including oestrogen receptor (ER), progesterone receptor (PR), human epidermal growth fa...

Macrophage heterogeneity in breast cancer microenvironment and development of a prognostic model: exploring TFF1 as a novel therapeutic target.

BACKGROUNDS: Breast cancer (BRCA) represents the most prevalent malignancy globally, with projections indicating 3.2 million new cases anticipated by ...

Intraoperative technological advances and new frontiers in precision glioma surgery.

BACKGROUND: Diffuse gliomas remain among the most surgically challenging tumors, characterized by their infiltrative nature, proximity to eloquent bra...

Identification of exosome-related genes signature based on bioinformatics and machine learning for prognostic prediction in colorectal cancer.

BACKGROUND: Colorectal cancer (CRC) is a prevalent malignant tumor with increasing incidence and mortality rates worldwide. Exosomes are secretory ves...

Metabolic phenotypes of doxorubicin-induced cardiotoxicity among patients with breast cancer.

BACKGROUND: Doxorubicin (DOX)-based chemotherapy has improved survival outcomes in breast cancer patients but is often limited by doxorubicin-induced ...

Advances in CT and MRI for Yttrium-90 Radioembolization of Hepatocellular Carcinoma.

RATIONALE AND OBJECTIVES: Transarterial radioembolization (TARE) is increasingly used for patients with hepatocellular carcinoma (HCC) across Barcelon...

Intensity-modulated radiotherapy alone versus concurrent chemoradiotherapy ± induction chemotherapy in older patients with low-risk stage II or T3N0M0 nasopharyngeal carcinoma.

BACKGROUND: The optimal treatment strategy for older patients with low-risk stage II or T3N0M0 nasopharyngeal carcinoma (NPC) remains undefined. This ...

Multiparametric MRI-derived radiomic signatures enable noninvasive prediction of HER2 expression in bladder cancer.

OBJECTIVE: To assess the value of multiparametric MRI (mpMRI)-derived radiomic signatures and a combined model for non-invasive prediction of human ep...

Integrating Participatory Social Innovation Into Requirements Engineering for AI Health Care Solutions: Case Study.

BACKGROUND: The successful design and implementation of artificial intelligence (AI)-driven solutions in health care requires early and continuous mul...

Comment on "Artificial intelligence-driven body composition analysis enhances chemotherapy toxicity prediction in colorectal cancer".

Targeting m6A-SCG2-TAMs axis overcomes 5-FU resistance in colorectal cancer via a multi-omics model.

Chemoresistance to 5-fluorouracil (5-FU) remains a critical barrier in colorectal cancer (CRC) management. This study integrates multi-omics data from...

A predictive model for pathological complete response in neoadjuvant-treated breast cancer: integrating pretreatment clinicopathologic and contrast-enhanced ultrasound characteristics via interpretable machine learning.

BACKGROUND: The ability to predict pathological complete response (pCR) prior to neoadjuvant therapy (NAT) would inform and facilitate tailored therap...

Routine biomarkers map response probability in HER2-positive breast cancer treated with neoadjuvant chemotherapy and dual HER2 blockade.

BACKGROUND: Pathologic complete response (pCR) after neoadjuvant chemotherapy and dual HER2 blockade is associated with improved outcomes in HER2-posi...

ChemoCardioNet: An Explainable Multimodal Transformer for Early Prediction of Chemotherapy-Induced Cardiotoxicity.

Chemotherapy-induced cardiotoxicity (CIC) remains a major cause of morbidity and mortality among cancer survivors, and conventional monitoring often f...