Breast Cancer

Comparative analysis of CNN-LSTM and CNN-BiLSTM hybrid deep learning models for solar radiation prediction.

Solar radiation forecasting is a complex task since the radiation signal is nonlinear, intermittent and is significantly influenced by meteorological variability, which makes it vital for PV planning, renewable energy planning and stability of the smart grid. In this work, a replicable comparison between CNN-LSTM and CNN-BiLSTM models for one-step ahead solar clearness-index forecasting based on m...

Radiation Resilient Synthetic Antiferromagnets-Based Neuromorphic Device for Sea Surface Temperature Reconstruction.

Reconstruction of sea surface temperature is critical for marine monitoring, yet conventional edge devices based on complementary metal-oxide-semiconductor (CMOS) technology suffer from memory-wall bottlenecks and radiation vulnerability in harsh marine environments. Here, we propose a neuromorphic computing framework based on radiation-tolerant synthetic antiferromagnetic (SAF) synaptic devices t...

Plasma metabolomics combined with machine learning for postoperative prognostic stratification in hormone receptor-positive/human epidermal growth factor receptor 2-negative early breast cancer.

BACKGROUND AND AIMS: Hormone receptor-positive/human epidermal growth factor receptor 2-negative (HR+/HER2-) breast cancer (BC) accounts for the major...

TACE-induced liver injury in hepatocellular carcinoma: mechanisms, prediction, and prevention in the era of gut microbiota and inflammasome research.

Transarterial chemoembolization (TACE) is a cornerstone locoregional therapy for hepatocellular carcinoma (HCC), yet most candidates also have cirrhos...

Phase-only synthesis of cosecant-squared patterns with reduced sidelobes in large planar arrays via physics-informed deep neural networks.

This paper introduces a deep learning-based framework for phase-only synthesis of cosecant-squared (csc²) radiation patterns in planar antenna arrays ...

MRI-based quantification of intratumoral heterogeneity for predicting recurrence risk in ER+/HER2- breast cancer.

OBJECTIVES: The need for a cost-effective, rapid, and increasingly accessible alternative to the 21-gene assay prompted this study, which developed a ...

Radiation scatter at fluoroscopy-guided endoscopic procedures: Building towards further optimization.

INTRODUCTION: Exposure to ionizing radiation by endoscopy personnel during fluoroscopy-guided procedures remains a health hazard. We aimed to evaluate...

AI-assisted digital breast tomosynthesis as a decision-support tool for post-neoadjuvant surgical planning in breast cancer.

PURPOSE: Accurate assessment of residual disease after neoadjuvant chemotherapy (NAC) is essential for surgical planning and prevention of incomplete ...

Tracer-agnostic diffusion model-based CT-free attenuation correction for brain PET: Comprehensive evaluation across 14 tracers.

OBJECTIVE: Accurate attenuation correction (AC) is critical in quantitative brain PET imaging. Conventional CT-based AC methods increase radiation exp...

Optimising chest computed tomography (CT) scan ranges in paediatric patients to reduce radiation exposure.

AIM: The aim of this study was to accurately position the scan range of unenhanced chest computed tomography (CT) scans for paediatric patients by cla...

Machine learning and plasma growth differentiation factor-15 (GDF15) for early risk stratification of heart failure progression in a long-latency doxorubicin cardiomyopathy model.

BACKGROUND: Anthracycline-induced cardiotoxicity is a major cause of late heart failure (HF) in cancer survivors. Yet early identification of individu...

Delta radiomics for predicting early radiation-induced lung injury after thoracic radiotherapy: a retrospective paired-CT study.

PURPOSE: Early radiation-induced lung injury remains a clinically relevant complication after thoracic radiotherapy. We compared pretreatment, posttre...

CT in adult patients with Polytrauma: current practices, protocol optimization, structured reporting and future directions.

Computed tomography [CT] is the frontline imaging modality for the assessment of polytrauma patients because of its speed, diagnostic accuracy and inf...

The complementary roles of oversight, education, and collaboration in the responsible integration of artificial intelligence in radiation medicine: White paper of (CADRA).

Artificial intelligence (AI) is poised to fundamentally transform radiation medicine, with growing influence across clinical decision-making, workflow...

Multimodal deep learning-based prediction of radiation-induced temporal lobe injury via anatomical imaging and spatial dose: A multicenter study.

BACKGROUND: To develop and validate a multimodal deep learning model for pre-treatment prediction of radiation-induced temporal lobe injury (RTLI), an...

Cardiac substructure dosimetry in thoracic radiotherapy: moving beyond mean heart dose and toward precision cardiac risk mitigation.

BACKGROUND: Radiation-induced heart disease (RIHD) remains a clinically significant consequence of thoracic radiotherapy (RT). Historically, the mean ...

Counterfactual AI for Dynamic Dose Optimization with Side-Effect Constraints.

We present DoseAI, an online-updateable causal Artificial Intelligence (AI) framework for outcome prediction and dynamic dose optimization in continuo...

Stochastic Expansion of Radionuclide Inhalation Dosimetry for Consequence Management Application: Uncertainty and Sensitivity Analysis in the ICRP 130 Human Respiratory Tract Model.

Releases from nuclear or radiological security events can result in significant internal radiation contamination through inhalation of particulate con...

Machine learning-based integration develops a novel lysosome-related prognostic signature associated with prognosis and immune infiltration landscape in acute myeloid leukemia.

BACKGROUND: Lysosomes are essential for intracellular degradation and recycling, and changes in their function significantly contribute to tumor growt...

AI-Assisted HER2 Scoring in Breast Cancer: Diagnostic Agreement and Understanding Discordance.

PURPOSE: With trastuzumab deruxtecan demonstrating clinical benefit in HER2-low and ultralow breast cancer, precise discrimination at the lowest end o...