AIMC Topic: Humans

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Positron emission tomography imaging in cardiovascular disease.

Heart (British Cardiac Society)
Positron emission tomography (PET) imaging is useful in cardiovascular disease across several areas, from assessment of myocardial perfusion and viability, to highlighting atherosclerotic plaque activity and measuring the extent of cardiac innervatio...

Perioperative outcomes of robot-assisted vs video-assisted and traditional open thoracic surgery for lung cancer: A systematic review and network meta-analysis.

The international journal of medical robotics + computer assisted surgery : MRCAS
BACKGROUND: The superiority of robot-assisted thoracic surgery (RATS) over video-assisted thoracic surgery (VATS) and thoracotomy remains controversial for lung cancer.

Fast generalization error bound of deep learning without scale invariance of activation functions.

Neural networks : the official journal of the International Neural Network Society
In the theoretical analysis of deep learning, discovering which features of deep learning lead to good performance is an important task. Using the framework for analyzing the generalization error developed by Suzuki (2018), we derive a fast learning ...

Machine learning-based lifetime breast cancer risk reclassification compared with the BOADICEA model: impact on screening recommendations.

British journal of cancer
BACKGROUND: The clinical utility of machine-learning (ML) algorithms for breast cancer risk prediction and screening practices is unknown. We compared classification of lifetime breast cancer risk based on ML and the BOADICEA model. We explored the d...

Human-computer collaboration for skin cancer recognition.

Nature medicine
The rapid increase in telemedicine coupled with recent advances in diagnostic artificial intelligence (AI) create the imperative to consider the opportunities and risks of inserting AI-based support into new paradigms of care. Here we build on recent...

Integrating spatial gene expression and breast tumour morphology via deep learning.

Nature biomedical engineering
Spatial transcriptomics allows for the measurement of RNA abundance at a high spatial resolution, making it possible to systematically link the morphology of cellular neighbourhoods and spatially localized gene expression. Here, we report the develop...

Dense anatomical annotation of slit-lamp images improves the performance of deep learning for the diagnosis of ophthalmic disorders.

Nature biomedical engineering
The development of artificial intelligence algorithms typically demands abundant high-quality data. In medicine, the datasets that are required to train the algorithms are often collected for a single task, such as image-level classification. Here, w...

Automatic segmentation of pelvic organs-at-risk using a fusion network model based on limited training samples.

Acta oncologica (Stockholm, Sweden)
Efficient and accurate methods are needed to automatically segmenting organs-at-risk (OAR) to accelerate the radiotherapy workflow and decrease the treatment wait time. We developed and evaluated the use of a fused model Dense V-Network for its abil...

Decentralized Motion Control for Omnidirectional Wheelchair Tracking Error Elimination Using PD-Fuzzy-P and GA-PID Controllers.

Sensors (Basel, Switzerland)
The last decade observed a significant research effort directed towards maneuverability and safety of mobile robots such as smart wheelchairs. The conventional electric wheelchair can be equipped with motorized omnidirectional wheels and several sens...