AIMC Topic: Humans

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Deep Learning With an Attention Mechanism for Differentiating the Origin of Brain Metastasis Using MR images.

Journal of magnetic resonance imaging : JMRI
BACKGROUND: Brain metastasis (BM) is a serious neurological complication of cancer of different origins. The value of deep learning (DL) to identify multiple types of primary origins remains unclear.

Automatic segmentation of neurovascular bundle on mri using deep learning based topological modulated network.

Medical physics
PURPOSE: Radiation damage on neurovascular bundles (NVBs) may be the cause of sexual dysfunction after radiotherapy for prostate cancer. However, it is challenging to delineate NVBs as organ-at-risks from planning CTs during radiotherapy. Recently, t...

Development and validation of a deep learning model using convolutional neural networks to identify femoral internal fixation device in radiographs.

Skeletal radiology
OBJECTIVE: The purpose of this study is to develop and validate a deep convolutional neural network (DCNN) model to automatically identify the manufacturer and model of hip internal fixation devices from anteroposterior (AP) radiographs.

Emerging MXene-Based Flexible Tactile Sensors for Health Monitoring and Haptic Perception.

Small (Weinheim an der Bergstrasse, Germany)
Due to their potential applications in physiological monitoring, diagnosis, human prosthetics, haptic perception, and human-machine interaction, flexible tactile sensors have attracted wide research interest in recent years. Thanks to the advances in...

The PD-ROBOSCORE: A difficulty score for robotic pancreatoduodenectomy.

Surgery
BACKGROUND: Difficulty scoring systems are important for the safe, stepwise implementation of new procedures. We designed a retrospective observational study for building a difficulty score for robotic pancreatoduodenectomy.

Artificial intelligence and the doctor-patient relationship expanding the paradigm of shared decision making.

Bioethics
Artificial intelligence (AI) based clinical decision support systems (CDSS) are becoming ever more widespread in healthcare and could play an important role in diagnostic and treatment processes. For this reason, AI-based CDSS has an impact on the do...

Visual deep learning of unprocessed neuroimaging characterises dementia subtypes and generalises across non-stereotypic samples.

EBioMedicine
BACKGROUND: Dementia's diagnostic protocols are mostly based on standardised neuroimaging data collected in the Global North from homogeneous samples. In other non-stereotypical samples (participants with diverse admixture, genetics, demographics, MR...

Deep learning-based automatic sella turcica segmentation and morphology measurement in X-ray images.

BMC medical imaging
BACKGROUND: Although the morphological changes of sella turcica have been drawing increasing attention, the acquirement of linear parameters of sella turcica relies on manual measurement. Manual measurement is laborious, time-consuming, and may intro...