Cardiovascular

Deep learning-based AI model for signet-ring cell carcinoma diagnosis and chemotherapy response prediction in gastric cancer.

PURPOSE: We aimed to develop a noninvasive artificial intelligence (AI) model to diagnose signet-ring cell carcinoma (SRCC) of gastric cancer (GC) and identify patients with SRCC who could benefit from postoperative chemotherapy based on preoperative contrast-enhanced computed tomography (CT).

Dosimetric impact of deep learning-based CT auto-segmentation on radiation therapy treatment planning for prostate cancer.

BACKGROUND: The evaluation of automatic segmentation algorithms is commonly performed using geometric metrics. An analysis based on dosimetric parameters might be more relevant in clinical practice but is often lacking in the literature. The aim of this study was to investigate the impact of state-of-the-art 3D U-Net-generated organ delineations on dose optimization in radiation therapy (RT) for p...

Low-radiation dose scan protocol for preoperative imaging for dental implant surgery using deep learning-based reconstruction in multidetector CT.

OBJECTIVES: This study aimed to investigate the impact of a deep learning-based reconstruction (DLR) technique on image quality and reduction of radia...

Network biology and artificial intelligence drive the understanding of the multidrug resistance phenotype in cancer.

Globally with over 10 million deaths per year, cancer is the most transversal disease across countries, cultures, and ethnicities, affecting both deve...

Development of a deep learning-based patient-specific target contour prediction model for markerless tumor positioning.

PURPOSE: For pancreatic cancer patients, image guided radiation therapy and real-time tumor tracking (RTTT) techniques can deliver radiation to the ta...

Breast lesions classifications of mammographic images using a deep convolutional neural network-based approach.

Breast cancer is one of the worst illnesses, with a higher fatality rate among women globally. Breast cancer detection needs accurate mammography inte...

Deep learning image reconstruction algorithm for abdominal multidetector CT at different tube voltages: assessment of image quality and radiation dose in a phantom study.

OBJECTIVES: To compare the image quality and radiation dose of a deep learning image reconstruction (DLIR) algorithm compared with iterative reconstru...

High-strength deep learning image reconstruction in coronary CT angiography at 70-kVp tube voltage significantly improves image quality and reduces both radiation and contrast doses.

OBJECTIVES: To explore the use of 70-kVp tube voltage combined with high-strength deep learning image reconstruction (DLIR-H) in reducing radiation an...

Artificial intelligence: A promising frontier in bladder cancer diagnosis and outcome prediction.

Bladder cancer (BCa) is the most common malignancy of the urinary tract and the most expensive malignancy to treat over the patients' lifetime. In rec...

Single-Port Retzius-Sparing Robot-Assisted Radical Prostatectomy: Feasibility and Early Outcomes.

To determine safety and feasibility of single-port Retzius-sparing robot-assisted radical prostatectomy (SP-rsRARP) using the da Vinci SP (Intuitive ...

Magnetic Biohybrid Microrobot Multimers Based on Cells for Enhanced Targeted Drug Delivery.

Magnetic micro-/nanorobots have been regarded as a promising platform for targeted drug delivery, and tremendous strategies have been developed in rec...

Reduced-Dose Deep Learning Reconstruction for Abdominal CT of Liver Metastases.

Background Assessment of liver lesions is constrained as CT radiation doses are lowered; evidence suggests deep learning reconstructions mitigate such...

Prediction of Lung Infection during Palliative Chemotherapy of Lung Cancer Based on Artificial Neural Network.

Lung infection seriously affects the effect of chemotherapy in patients with lung cancer and increases pain. The study is aimed at establishing the pr...

Artificial intelligence for breast cancer analysis: Trends & directions.

Breast cancer is one of the leading causes of death among women. Early detection of breast cancer can significantly improve the lives of millions of w...

Reconstruction of three-dimensional tomographic patient models for radiation dose modulation in CT from two scout views using deep learning.

BACKGROUND: A tomographic patient model is essential for radiation dose modulation in x-ray computed tomography (CT). Currently, two-view scout images...

Improving generalisation capability of artificial intelligence-based solar radiation estimator models using a bio-inspired optimisation algorithm and multi-model approach.

One way of reducing environmental pollution is to reduce our dependence on fossil fuels by replacing them with solar radiation (Rs), which is one of t...

Breast Tumor Detection and Classification in Mammogram Images Using Modified YOLOv5 Network.

Breast cancer incidence has been rising steadily during the past few decades. It is the second leading cause of death in women. If it is diagnosed ear...

Artificial Intelligence-Guided Prediction of Dental Doses Before Planning of Radiation Therapy for Oropharyngeal Cancer: Technical Development and Initial Feasibility of Implementation.

PURPOSE: The aim was to develop a novel artificial intelligence (AI)-guided clinical decision support system, to predict radiation doses to subsites o...

Identifying Cancer Subtypes Using a Residual Graph Convolution Model on a Sample Similarity Network.

Cancer subtype classification helps us to understand the pathogenesis of cancer and develop new cancer drugs, treatment from which patients would bene...

[EMPAIA-ecosystem for pathology diagnostics with AI assistance].

Applications of deep learning and other artificial intelligence techniques play an increasing role in pathological research. In contrast to research, ...