AIMC Topic: Humans

Clear Filters Showing 34031 to 34040 of 95995 articles

Artificial intelligence (AI) and machine learning (ML) in precision oncology: a review on enhancing discoverability through multiomics integration.

The British journal of radiology
Multiomics data including imaging radiomics and various types of molecular biomarkers have been increasingly investigated for better diagnosis and therapy in the era of precision oncology. Artificial intelligence (AI) including machine learning (ML) ...

Real-Time Detection of Strawberry Ripeness Using Augmented Reality and Deep Learning.

Sensors (Basel, Switzerland)
Currently, strawberry harvesting relies heavily on human labour and subjective assessments of ripeness, resulting in inconsistent post-harvest quality. Therefore, the aim of this work is to automate this process and provide a more accurate and effici...

DSPose: Dual-Space-Driven Keypoint Topology Modeling for Human Pose Estimation.

Sensors (Basel, Switzerland)
Human pose estimation is the basis of many downstream tasks, such as motor intervention, behavior understanding, and human-computer interaction. The existing human pose estimation methods rely too much on the similarity of keypoints at the image feat...

PSMA-PET improves deep learning-based automated CT kidney segmentation.

Zeitschrift fur medizinische Physik
UNLABELLED: For dosimetry of radiopharmaceutical therapies, it is essential to determine the volume of relevant structures exposed to therapeutic radiation. For many radiopharmaceuticals, the kidneys represent an important organ-at-risk. To reduce th...

Barriers and facilitators of artificial intelligence conception and implementation for breast imaging diagnosis in clinical practice: a scoping review.

European radiology
OBJECTIVE: Although artificial intelligence (AI) has demonstrated promise in enhancing breast cancer diagnosis, the implementation of AI algorithms in clinical practice encounters various barriers. This scoping review aims to identify these barriers ...

Deep learning-based segmentation of whole-body fetal MRI and fetal weight estimation: assessing performance, repeatability, and reproducibility.

European radiology
OBJECTIVES: To develop a deep-learning method for whole-body fetal segmentation based on MRI; to assess the method's repeatability, reproducibility, and accuracy; to create an MRI-based normal fetal weight growth chart; and to assess the sensitivity ...

A novel image deep learning-based sub-centimeter pulmonary nodule management algorithm to expedite resection of the malignant and avoid over-diagnosis of the benign.

European radiology
OBJECTIVES: With the popularization of chest computed tomography (CT) screening, there are more sub-centimeter (≤ 1 cm) pulmonary nodules (SCPNs) requiring further diagnostic workup. This area represents an important opportunity to optimize the SCPN ...

Distilling Knowledge From an Ensemble of Vision Transformers for Improved Classification of Breast Ultrasound.

Academic radiology
RATIONALE AND OBJECTIVES: To develop a deep learning model for the automated classification of breast ultrasound images as benign or malignant. More specifically, the application of vision transformers, ensemble learning, and knowledge distillation i...

Artificial Intelligence Governance and Otolaryngology-Head and Neck Surgery.

The Laryngoscope
This rapid communication highlights components of artificial intelligence governance in healthcare and suggests adopting key governance approaches in otolaryngology – head and neck surgery.