Cardiovascular

A D-Shaped Polymer Optical Fiber Surface Plasmon Resonance Biosensor for Breast Cancer Detection Applications.

Fiber-optic biosensors have garnered significant attention and witnessed rapid development in recent years owing to their remarkable attributes such as high sensitivity, immunity to electromagnetic interference, and real-time monitoring. They have emerged as a potential tool in the realm of biomarker detection for low-concentration and small molecules. In this paper, a portable and cost-effective ...

Fusion Radiomics-Based Prediction of Response to Neoadjuvant Chemotherapy for Osteosarcoma.

RATIONALE AND OBJECTIVES: Neoadjuvant chemotherapy (NAC) is the most crucial prognostic factor for osteosarcoma (OS), it significantly prolongs progression-free survival and improves the quality of life. This study aims to develop a deep learning radiomics (DLR) model to accurately predict the response to NAC in patients diagnosed with OS using preoperative MR images.

Synergizing photon-counting CT with deep learning: potential enhancements in medical imaging.

This review article highlights the potential of integrating photon-counting computed tomography (CT) and deep learning algorithms in medical imaging t...

Increased Peripheral Blood DNA Damage and Elevated Serum Levels of Melanoma Inhibitory Activity Protein: Clues to Excess Skin Cancer Risk in Airline Pilots?

Background and objective The risk of malignant melanoma (MM) and other forms of skin cancer appears to be higher in airline pilots (APs), potentially ...

Towards safer imaging: A comparative study of deep learning-based denoising and iterative reconstruction in intraindividual low-dose CT scans using an in-vivo large animal model.

PURPOSE: Computed tomography (CT) scans are a significant source of medically induced radiation exposure. Novel deep learning-based denoising (DLD) al...

The tumor immune microenvironment in pancreatic cancer and its potential in the identification of immunotherapy biomarkers.

INTRODUCTION: Pancreatic cancer (PC) has an extremely poor prognosis, even with surgical resection and triplet chemotherapy treatment. Cancer immunoth...

Single-Cell Radiation Response Scoring with the Deep Learning Algorithm CeCILE 2.0.

External stressors, such as ionizing radiation, have massive effects on life, survival, and the ability of mammalian cells to divide. Different types ...

Smart Sensor Control and Monitoring of an Automated Cell Expansion Process.

Immune therapy for cancer patients is a new and promising area that in the future may complement traditional chemotherapy. The cell expansion phase is...

ARCHERY: a prospective observational study of artificial intelligence-based radiotherapy treatment planning for cervical, head and neck and prostate cancer - study protocol.

INTRODUCTION: Fifty per cent of patients with cancer require radiotherapy during their disease course, however, only 10%-40% of patients in low-income...

Clinical evaluation of deep learning and atlas-based auto-segmentation for organs at risk delineation.

Manual delineation of organs at risk and clinical target volumes is essential in radiotherapy planning. Atlas-based auto-segmentation (ABAS) algorithm...

Deep Learning-Guided Dosimetry for Mitigating Local Failure of Patients With Non-Small Cell Lung Cancer Receiving Stereotactic Body Radiation Therapy.

PURPOSE: Non-small cell lung cancer (NSCLC) stereotactic body radiation therapy with 50 Gy/5 fractions is sometimes considered controversial, as the n...

Diagnostic accuracy of radiomics-based machine learning for neoadjuvant chemotherapy response and survival prediction in gastric cancer patients: A systematic review and meta-analysis.

BACKGROUND: In recent years, researchers have explored the use of radiomics to predict neoadjuvant chemotherapy outcomes in gastric cancer (GC). Yet, ...

Deep learning-enabled breast cancer endocrine response determination from H&E staining based on ESR1 signaling activity.

Estrogen receptor (ER) positivity by immunohistochemistry has long been a main selection criterium for breast cancer patients to be treated with endoc...

Energy controls wave propagation in a neural network with spatial stimuli.

Nervous system has distinct anisotropy and some intrinsic biophysical properties enable neurons present various firing modes in neural activities. In ...

Radiation-induced acoustic signal denoising using a supervised deep learning framework for imaging and therapy monitoring.

Radiation-induced acoustic (RA) imaging is a promising technique for visualizing the invisible radiation energy deposition in tissues, enabling new im...

Artificial intelligence in breast imaging: potentials and challenges.

Breast cancer, which is the most common type of malignant tumor among humans, is a leading cause of death in females. Standard treatment strategies, i...

Noninvasive Computed Tomography-Based Deep Learning Model Predicts In Vitro Chemosensitivity Assay Results in Pancreatic Cancer.

OBJECTIVES: We aimed to predict in vitro chemosensitivity assay results from computed tomography (CT) images by applying deep learning (DL) to optimiz...

Clinical and Dosimetric Impact of 2D kV Motion Monitoring and Intervention in Liver Stereotactic Body Radiation Therapy.

PURPOSE: Positional errors resulting from motion are a principal challenge across all disease sites in radiation therapy. This is particularly pertine...

Predicting intratumoral fluid pressure and liposome accumulation using physics informed deep learning.

Liposome-based anticancer agents take advantage of the increased vascular permeability and transvascular pressure gradients for selective accumulation...

Novel Deep Learning Denoising Enhances Image Quality and Lowers Radiation Exposure in Interventional Bronchial Artery Embolization Cone Beam CT.

OBJECTIVES: In interventional bronchial artery embolization (BAE), periprocedural cone beam CT (CBCT) improves guiding and localization. However, a tr...