AIMC Topic: Humans

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Study examining the significant role of intellectual property protection in driving radical technological innovation among national research project teams, employing PLS-SEM and ANN modeling.

PloS one
This study examines the role of intellectual property protection (IPP) in enhancing radical technological innovation (RTI) within national research project teams, using an innovation-driven theory and an ability-motivation-opportunity (AMO) perspecti...

"Where No One Has Gone Before": Questions to Ensure the Ethical, Rigorous, and Thoughtful Application of Artificial Intelligence in the Analysis of HIV Research.

The Journal of the Association of Nurses in AIDS Care : JANAC
ChatGPT, an artificial intelligence (AI) system released by OpenAI on November 30th, 2022, has upended scientific and educational paradigms, reshaping the way that we think about teaching, writing, and now research. Since that time, qualitative data ...

Principles of artificial intelligence in radiooncology.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
PURPOSE: In the rapidly expanding field of artificial intelligence (AI) there is a wealth of literature detailing the myriad applications of AI, particularly in the realm of deep learning. However, a review that elucidates the technical principles of...

Deep learning for autosegmentation for radiotherapy treatment planning: State-of-the-art and novel perspectives.

Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al]
The rapid development of artificial intelligence (AI) has gained importance, with many tools already entering our daily lives. The medical field of radiation oncology is also subject to this development, with AI entering all steps of the patient jour...

Phenotypes of Patients with Intracerebral Hemorrhage, Complications, and Outcomes.

Neurocritical care
BACKGROUND: The objective of this study was to define clinically meaningful phenotypes of intracerebral hemorrhage (ICH) using machine learning.

IEA-Net: Internal and External Dual-Attention Medical Segmentation Network with High-Performance Convolutional Blocks.

Journal of imaging informatics in medicine
Currently, deep learning is developing rapidly in the field of image segmentation, and medical image segmentation is one of the key applications in this field. Conventional CNN has achieved great success in general medical image segmentation tasks, b...

Development and Validation of Prediction Models for Incident Reversible Cognitive Frailty Based on Social-Ecological Predictors Using Generalized Linear Mixed Model and Machine Learning Algorithms: A Prospective Cohort Study.

Journal of applied gerontology : the official journal of the Southern Gerontological Society
This study aimed to develop and validate prediction models for incident reversible cognitive frailty (RCF) based on social-ecological predictors. Older adults aged ≥60 years from China Health and Retirement Longitudinal Study (CHARLS) 2011-2013 surve...

Duple-MONDNet: duple deep learning-based mobile net for motor neuron disease identification.

Turkish journal of medical sciences
BACKGROUND/AIM: Motor neuron disease (MND) is a devastating neuron ailment that affects the motor neurons that regulate muscular voluntary actions. It is a rare disorder that gradually destroys aspects of neurological function. In general, MND arises...

Deep learning approaches for the detection of scar presence from cine cardiac magnetic resonance adding derived parametric images.

Medical & biological engineering & computing
This work proposes a convolutional neural network (CNN) that utilizes different combinations of parametric images computed from cine cardiac magnetic resonance (CMR) images, to classify each slice for possible myocardial scar tissue presence. The CNN...

Ethical, legal, and regulatory landscape of artificial intelligence in Australian healthcare and ethical integration in radiography: A narrative review.

Journal of medical imaging and radiation sciences
This narrative review explores the ethical, legal, and regulatory landscape of AI integration in Australian healthcare, focusing on radiography. It examines the current legislative framework, assesses the trust and reliability of AI tools, and propos...