AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Automation

Showing 101 to 110 of 898 articles

Clear Filters

Automated Tomographic Assessment of Structural Defects of Freeze-Dried Pharmaceuticals.

AAPS PharmSciTech
The topology and surface characteristics of lyophilisates significantly impact the stability and reconstitutability of freeze-dried pharmaceuticals. Consequently, visual quality control of the product is imperative. However, this procedure is not onl...

Multi-modal segmentation with missing image data for automatic delineation of gross tumor volumes in head and neck cancers.

Medical physics
BACKGROUND: Head and neck (HN) gross tumor volume (GTV) auto-segmentation is challenging due to the morphological complexity and low image contrast of targets. Multi-modality images, including computed tomography (CT) and positron emission tomography...

Automated diagnosis of schizophrenia based on spatial-temporal residual graph convolutional network.

Biomedical engineering online
BACKGROUND: Schizophrenia (SZ), a psychiatric disorder for which there is no precise diagnosis, has had a serious impact on the quality of human life and social activities for many years. Therefore, an advanced approach for accurate treatment is requ...

Artificial intelligence, robotics, and automation viewed through the context of the previous four decades.

Healthcare management forum
Computers and applications of computers into our world have changed dramatically during the past five decades, from early days of minimal central processing unit capacity, limited memory and without advantage of global networking. In this article, th...

Towards more precise automatic analysis: a systematic review of deep learning-based multi-organ segmentation.

Biomedical engineering online
Accurate segmentation of multiple organs in the head, neck, chest, and abdomen from medical images is an essential step in computer-aided diagnosis, surgical navigation, and radiation therapy. In the past few years, with a data-driven feature extract...

Automated identification of toxigenic cyanobacterial genera for water quality control purposes.

Journal of environmental management
Cyanobacteria are the dominating microorganisms in aquatic environments, posing significant risks to public health due to toxin production in drinking water reservoirs. Traditional water quality assessments for abundance of the toxigenic genera in wa...

Automatic detection of epilepsy from EEGs using a temporal convolutional network with a self-attention layer.

Biomedical engineering online
BACKGROUND: Over 60% of epilepsy patients globally are children, whose early diagnosis and treatment are critical for their development and can substantially reduce the disease's burden on both families and society. Numerous algorithms for automated ...

Fully Automatic Quantitative Measurement of Equilibrium Radionuclide Angiocardiography Using a Convolutional Neural Network.

Clinical nuclear medicine
PURPOSE: The aim of this study was to generate deep learning-based regions of interest (ROIs) from equilibrium radionuclide angiography datasets for left ventricular ejection fraction (LVEF) measurement.

Deep learning-based automatic measurement system for patellar height: a multicenter retrospective study.

Journal of orthopaedic surgery and research
BACKGROUND: The patellar height index is important; however, the measurement procedures are time-consuming and prone to significant variability among and within observers. We developed a deep learning-based automatic measurement system for the patell...