Cardiovascular

Innovative deep learning classifiers for breast cancer detection through hybrid feature extraction techniques.

Breast cancer remains a major cause of mortality among women, where early and accurate detection is critical to improving survival rates. This study presents a hybrid classification approach for mammogram analysis by combining handcrafted statistical features and deep learning techniques. The methodology involves preprocessing with the Shearlet Transform, segmentation using Improved Otsu threshold...

Deep learning for automated segmentation of radiation-induced changes in cerebral arteriovenous malformations following radiosurgery.

BACKGROUND: Despite the widespread use of stereotactic radiosurgery (SRS) to treat cerebral arteriovenous malformations (AVMs), this procedure can lead to radiation-induced changes (RICs) in the surrounding brain tissue. Volumetric assessment of RICs is crucial for therapy planning and monitoring. RICs that appear as hyper-dense areas in magnetic resonance T2-weighted (T2w) images are clearly iden...

Radiation Dose Reduction and Image Quality Improvement of UHR CT of the Neck by Novel Deep-learning Image Reconstruction.

PURPOSE: We evaluated a dedicated dose-reduced UHR-CT for head and neck imaging, combined with a novel deep learning reconstruction algorithm to asses...

MRI's evolving role in rectal cancer in the era of personalized medicine.

Recent decades have seen great advances in the diagnosis and management of rectal cancer, and magnetic resonance imaging (MRI) has become pivotal for ...

Advances in Breast Cancer Detection: Biomarkers, Mechanisms, and Biosensor Technologies.

Breast cancer (BC), the most common cancer in women, remains a global health concern. According to the World Health Organization, in the year 2022, BC...

3Mont: A multi-omics integrative tool for breast cancer subtype stratification.

Breast Cancer (BRCA) is a heterogeneous disease, and it is one of the most prevalent cancer types among women. Developing effective treatment strategi...

Aptamer-directed siRNA delivery systems for triple-negative breast cancer therapy.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer characterized by the absence of estrogen, progesterone, and HER2 recept...

Intra-tumor microbiome-based tumor survival indices predict immune interaction and drug sensitivity on pan-cancer scale.

UNLABELLED: Growing research evidence indicates a substantial influence of the intra-tumor microbiome on tumor outcome. However, there is currently no...

Mapping breast cancer research on monoclonal antibodies: a data-driven approach using VOSviewer, Bibliometrix, and CiteSpace.

Monoclonal Antibodies and Breast Cancer Research (MABCR) has progressed substantially, particularly in the areas of HER2-positive and triple-negative ...

Axial Skeletal Assessment in Osteoporosis Using Radiofrequency Echographic Multi-spectrometry: Diagnostic Performance, Clinical Utility, and Future Directions.

Osteoporosis, a prevalent skeletal disorder, necessitates accurate and accessible diagnostic tools for effective disease management and fracture preve...

Artificial intelligence in imaging diagnosis of liver tumors: current status and future prospects.

Liver cancer remains a significant global health concern, ranking as the sixth most common malignancy and the third leading cause of cancer-related de...

Machine learning-based forest fire susceptibility mapping of Southern Mizoram, a part of Indo-Burma Biodiversity Hotspot.

Forest fires are a significant global environmental hazard, causing widespread economic losses and ecological damage to natural habitats. Biodiversity...

Innovative technologies and their clinical prospects for early lung cancer screening.

BACKGROUND: Lung cancer remains the leading cause of cancer-related mortality worldwide, due to lacking effective early-stage screening approaches. Im...

A multi-gene predictive model for the radiation sensitivity of nasopharyngeal carcinoma based on machine learning.

Radiotherapy resistance in nasopharyngeal carcinoma (NPC) is a major cause of recurrence and metastasis. Identifying radiotherapy-related biomarkers i...

Machine learning model for predicting recurrence following intensity-modulated radiation therapy in nasopharyngeal carcinoma.

BACKGROUND: Nasopharyngeal carcinoma (NPC) exhibits unique histopathological characteristics compared to other head and neck cancers. The prognosis of...

Quasi-supervised MR-CT image conversion based on unpaired data.

. In radiotherapy planning, acquiring both magnetic resonance (MR) and computed tomography (CT) images is crucial for comprehensive evaluation and tre...

Next-generation cancer therapeutics: unveiling the potential of liposome-based nanoparticles through bioinformatics.

Cancer remains one of the most deadly diseases in the world, requiring constant growth and improvements in therapeutic strategies. Traditional cancer ...

The role of tumor microenvironment and immune cell crosstalk in triple-negative breast cancer (TNBC): Emerging therapeutic opportunities.

Triple-negative breast cancer (TNBC) is an aggressive subtype characterized by its lack of estrogen, progesterone, and HER2 receptors, leading to limi...

Machine learning-based models for outcome prediction in skull base and spinal chordomas: a systematic review and meta-analysis.

BACKGROUND: Chordomas are primary bone lesions originating from embryonic notochord remnants, most commonly developing along the skull base and spine....

Comparative analysis of pre-transcatheter aortic valve implantation CTA protocols: Optimizing radiation dose and contrast volume.

BACKGROUND: To establish the most effective and safe pre-transcatheter aortic valve implantation (TAVI) CT angiography (CTA) protocol by comparing two...