Cardiovascular

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 epidermal growth factor receptor 2 (HER2) expression in bladder cancer (BCa). METHODS: A total of 113 BCa patients with preoperative pelvic mpMRI were retrospectively enrolled. Radiomic features were extracted from T2WI, DWI, DCE and their combinations...

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 multidisciplinary and multiprofessional collaboration. However, diverse disciplinary educational backgrounds, varying languages, and cultural or geographic differences can lead to misunderstandings. To bridge this gap, a structured approach to AI requir...

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...

Early Prediction of Pathological Complete Response to Neoadjuvant Chemotherapy in Breast Cancer using a Longitudinal US-based Stack-model.

RATIONALE AND OBJECTIVES: To evaluate the diagnostic performance of a longitudinal ultrasound (US)-based stack-model for early prediction of pathologi...

Geometric-structural multi-label learning for non-invasive prediction of breast cancer biomarkers.

Accurate profiling of molecular biomarkers, including ER, PR, HER2, and Ki-67, is pivotal for tailoring therapeutic strategies in breast cancer manage...

ADC Target Profiling in NSCLC: Generalizable AI Separates TROP-2 and cMET Phenotypes.

PURPOSE: Antibody-drug conjugates (ADC) targeting trophoblast cell surface antigen 2 (TROP-2) and cMET are entering clinical trials in non-small cell ...

Explanation-Guided Reconstruction of Missing Clinical Features for Survival Prediction in Pancreatic Cancer.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the most lethal cancers, with survival rates influenced by a variety of factors, including earl...

Optimisation of radiation dose and image quality in paediatric chest and abdominal CT examinations: A systematic review.

INTRODUCTION: Computed tomography (CT) is indispensable for the rapid evaluation of paediatric chest and abdominal pathology, yet it delivers relative...

The Big Data Science Center at the Shanghai Synchrotron Radiation Facility: the architecture of the superfacility.

In the context of the global big data deluge, concerted efforts are being made to address the challenges faced by large scientific facilities. These e...

Uncertainty quantification of U-Net based segmentation tool using conformal prediction.

BACKGROUND: The radiation therapy treatment process is very labour intensive, and artificial intelligence (AI) based auto contouring tools are increas...

Deep Unsupervised Domain Adaptation for Translating Cancer Dependency Maps From Cell Lines to Breast Cancer Tumor Genomics.

The Cancer dependency maps (DepMap) identify genetic dependencies in cancer cells using large-scale loss-of-function screens, providing a foundation f...

Machine Learning-based Prediction of Unplanned Acute Care in Outpatients Receiving S-1 Chemotherapy.

BACKGROUND/AIM: The increasing use of oral anticancer agents in outpatient settings has led to a growing need for unplanned acute care (UAC) due to tr...

Evidence-Based Strategies for Addressing Cancer- and Treatment-Related Cognitive Impairment: A Review.

Cancer-related cognitive impairment (CRCI) has become a notable long-term consequence for cancer survivors, especially among those receiving chemother...

Radiomics-based causal machine learning for exploratory treatment-effect estimation of neoadjuvant chemotherapy cycle intensity in osteosarcoma: a proof-of-concept study.

BACKGROUND: Radiomics-based modeling has shown promise for characterizing tumor heterogeneity, but its integration with causal machine learning for tr...

Trajectory analysis of sleep disorders and anxiety-depression in female breast cancer patients undergoing chemotherapy: based on group-based Multi-Trajectory Model and machine learning.

BACKGROUND: Sleep disorders and anxiety-depression symptoms can significantly impair the quality of life and treatment adherence among breast cancer p...

Multi-omics Signature Predicts Anti-EGFR Therapy Benefit in Colorectal Cancer Liver Metastases: A Multi-center Cohort Study.

INTRODUCTION: Clinical management of RAS wild-type colorectal cancer liver metastases (CRLM) remains challenging because many patients exhibit primary...