AIMC Topic: Humans

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Artificial Intelligence-Based 3D Printing Strategies for Bone Scaffold Fabrication and Its Application in Preclinical and Clinical Investigations.

ACS biomaterials science & engineering
3D printing has become increasingly popular in the field of bone tissue engineering. However, the mechanical properties, biocompatibility, and porosity of the 3D printed bone scaffolds are major requirements for tissue regeneration and implantation a...

[Implementing new interventions and indications: the possible role for real world data].

Nederlands tijdschrift voor geneeskunde
In advising the preferred therapy for the individual patient the expected results of the proposed intervention and possible side effects are the most relevant considerations. However, predicting the results of an intervention is difficult, especially...

Detection of fibrosing interstitial lung disease-suspected chest radiographs using a deep learning-based computer-aided detection system: a retrospective, observational study.

BMJ open
OBJECTIVES: To investigate the effectiveness of BMAX, a deep learning-based computer-aided detection system for detecting fibrosing interstitial lung disease (ILD) on chest radiographs among non-expert and expert physicians in the real-world clinical...

Pneumonia detection based on RSNA dataset and anchor-free deep learning detector.

Scientific reports
Pneumonia is a highly lethal disease, and research on its treatment and early screening tools has received extensive attention from researchers. Due to the maturity and cost reduction of chest X-ray technology, and with the development of artificial ...

Enhancing foveal avascular zone analysis for Alzheimer's diagnosis with AI segmentation and machine learning using multiple radiomic features.

Scientific reports
We propose a hybrid technique that employs artificial intelligence (AI)-based segmentation and machine learning classification using multiple features extracted from the foveal avascular zone (FAZ)-a retinal biomarker for Alzheimer's disease-to impro...

Developing an ontology of non-pharmacological treatment for emotional and mood disturbances in dementia.

Scientific reports
Emotional and mood disturbances are common in people with dementia. Non-pharmacological interventions are beneficial for managing these disturbances. However, effectively applying these interventions, particularly in the person-centred approach, is a...

Uncovering Language Disparity of ChatGPT on Retinal Vascular Disease Classification: Cross-Sectional Study.

Journal of medical Internet research
BACKGROUND: Benefiting from rich knowledge and the exceptional ability to understand text, large language models like ChatGPT have shown great potential in English clinical environments. However, the performance of ChatGPT in non-English clinical set...

Multiple Classification of Brain MRI Autism Spectrum Disorder by Age and Gender Using Deep Learning.

Journal of medical systems
The fact that the rapid and definitive diagnosis of autism cannot be made today and that autism cannot be treated provides an impetus to look into novel technological solutions. To contribute to the resolution of this problem through multiple classif...

Comparing the performance of statistical, machine learning, and deep learning algorithms to predict time-to-event: A simulation study for conversion to mild cognitive impairment.

PloS one
Mild Cognitive Impairment (MCI) is a condition characterized by a decline in cognitive abilities, specifically in memory, language, and attention, that is beyond what is expected due to normal aging. Detection of MCI is crucial for providing appropri...