AIMC Topic: Humans

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The transferability of the minimal invasive surgeon's skills to open surgery.

Scandinavian journal of urology
BACKGROUND: Robot-assisted laparoscopic surgery has gained popularity, which has contributed to a decrease in the number of open procedures. Hence a growing concern regarding the ability of laparoscopically trained surgeons to perform open surgery (e...

Effect of head motion-induced artefacts on the reliability of deep learning-based whole-brain segmentation.

Scientific reports
Due to their robustness and speed, recently developed deep learning-based methods have the potential to provide a faster and hence more scalable alternative to more conventional neuroimaging analysis pipelines in terms of whole-brain segmentation bas...

Dosimetric impact of deep learning-based CT auto-segmentation on radiation therapy treatment planning for prostate cancer.

Radiation oncology (London, England)
BACKGROUND: The evaluation of automatic segmentation algorithms is commonly performed using geometric metrics. An analysis based on dosimetric parameters might be more relevant in clinical practice but is often lacking in the literature. The aim of t...

Ethical Issues of Digital Twins for Personalized Health Care Service: Preliminary Mapping Study.

Journal of medical Internet research
BACKGROUND: The concept of digital twins has great potential for transforming the existing health care system by making it more personalized. As a convergence of health care, artificial intelligence, and information and communication technologies, pe...

Application of Artificial Intelligence Nuclear Medicine Automated Images Based on Deep Learning in Tumor Diagnosis.

Journal of healthcare engineering
In order to correctly obtain normal tissues and organs and tumor lesions, the research on multimodal medical image segmentation based on deep learning fully automatic segmentation algorithm is more meaningful. This article aims to study the applicati...

Account of Deep Learning-Based Ultrasonic Image Feature in the Diagnosis of Severe Sepsis Complicated with Acute Kidney Injury.

Computational and mathematical methods in medicine
This study was aimed at analyzing the diagnostic value of convolutional neural network models on account of deep learning for severe sepsis complicated with acute kidney injury and providing an effective theoretical reference for the clinical use of ...

Interpretable Model Based on Pyramid Scene Parsing Features for Brain Tumor MRI Image Segmentation.

Computational and mathematical methods in medicine
Due to the black box model nature of convolutional neural networks, computer-aided diagnosis methods based on depth learning are usually poorly interpretable. Therefore, the diagnosis results obtained by these unexplained methods are difficult to gai...

Design of Automated Deep Learning-Based Fusion Model for Copy-Move Image Forgery Detection.

Computational intelligence and neuroscience
Due to the exponential growth of high-quality fake photos on social media and the Internet, it is critical to develop robust forgery detection tools. Traditional picture- and video-editing techniques include copying areas of the image, referred to as...