AIMC Topic: Humans

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NVAM-Net: deep learning networks for reconstructing high-quality fiber orientation distributions.

Neuroradiology
PURPOSE: Diffusion magnetic resonance imaging (dMRI) is a widely used non-invasive method for investigating brain anatomical structures. Conventional techniques for estimating fiber orientation distribution (FOD) from dMRI data often neglect voxel-le...

Comprehensive data analysis of white blood cells with classification and segmentation by using deep learning approaches.

Cytometry. Part A : the journal of the International Society for Analytical Cytology
Deep learning approaches have frequently been used in the classification and segmentation of human peripheral blood cells. The common feature of previous studies was that they used more than one dataset, but used them separately. No study has been fo...

SAGL: A self-attention-based graph learning framework for predicting survival of colorectal cancer patients.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: Colorectal cancer (CRC) is one of the most commonly diagnosed cancers worldwide. The accurate survival prediction for CRC patients plays a significant role in the formulation of treatment strategies. Recently, machine learni...

Transcatheter Aortic Valve Replacement and Coronary Protection Guided by Deep Learning and 3-Dimensional Printing.

Surgical innovation
OBJECTIVE: In this case report, the auxiliary role of deep learning and 3-dimensional printing technology in the perioperative period was discussed to guide transcatheter aortic valve replacement and coronary stent implantation simultaneously.

The new era of artificial intelligence in neuroradiology: current research and promising tools.

Arquivos de neuro-psiquiatria
Radiology has a number of characteristics that make it an especially suitable medical discipline for early artificial intelligence (AI) adoption. These include having a well-established digital workflow, standardized protocols for image storage, and ...

H2MaT-Unet:Hierarchical hybrid multi-axis transformer based Unet for medical image segmentation.

Computers in biology and medicine
Accurate segmentation and lesion localization are essential for treating diseases in medical images. Despite deep learning methods enhancing segmentation, they still have limitations due to convolutional neural networks' inability to capture long-ran...

Machine learning model based on RCA-PDCA nursing methods and differentiating factors to predict hypotension during cesarean section surgery.

Computers in biology and medicine
BACKGROUND: Intraoperative hypotension during cesarean section has become a serious complication for maternal and fetal healthy. It is commonly encountered by subarachnoid anesthesia. However, currently used control methods have varying degrees of si...

An Artificial Intelligence-Supported Medicinal Chemistry Project: An Example for Incorporating Artificial Intelligence Within the Pharmacy Curriculum.

American journal of pharmaceutical education
OBJECTIVE: This study aims to integrate and use AI to teach core concepts in a medicinal chemistry course and to increase the familiarity of pharmacy students with AI in pharmacy practice and drug development. Artificial intelligence (AI) is a multid...