AIMC Topic: Algorithms

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Multi-assignment clustering: Machine learning from a biological perspective.

Journal of biotechnology
A common approach for analyzing large-scale molecular data is to cluster objects sharing similar characteristics. This assumes that genes with highly similar expression profiles are likely participating in a common molecular process. Biological syste...

PWD-3DNet: A Deep Learning-Based Fully-Automated Segmentation of Multiple Structures on Temporal Bone CT Scans.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
The temporal bone is a part of the lateral skull surface that contains organs responsible for hearing and balance. Mastering surgery of the temporal bone is challenging because of this complex and microscopic three-dimensional anatomy. Segmentation o...

Iterative Training of Neural Networks for Intra Prediction.

IEEE transactions on image processing : a publication of the IEEE Signal Processing Society
This paper presents an iterative training of neural networks for intra prediction in a block-based image and video codec. First, the neural networks are trained on blocks arising from the codec partitioning of images, each paired with its context. Th...

Revisiting Video Saliency Prediction in the Deep Learning Era.

IEEE transactions on pattern analysis and machine intelligence
Predicting where people look in static scenes, a.k.a visual saliency, has received significant research interest recently. However, relatively less effort has been spent in understanding and modeling visual attention over dynamic scenes. This work ma...

Towards Safe Weakly Supervised Learning.

IEEE transactions on pattern analysis and machine intelligence
In this paper, we study weakly supervised learning where a large amount of data supervision is not accessible. This includes i) incomplete supervision, where only a small subset of labels is given, such as semi-supervised learning and domain adaptati...

Continuous and automatic mortality risk prediction using vital signs in the intensive care unit: a hybrid neural network approach.

Scientific reports
Mortality risk prediction can greatly improve the utilization of resources in intensive care units (ICUs). Existing schemes in ICUs today require laborious manual input of many complex parameters. In this work, we present a scheme that uses variation...

Feature replacement methods enable reliable home video analysis for machine learning detection of autism.

Scientific reports
Autism Spectrum Disorder is a neuropsychiatric condition affecting 53 million children worldwide and for which early diagnosis is critical to the outcome of behavior therapies. Machine learning applied to features manually extracted from readily acce...

Evaluation of Four Artificial Intelligence-Assisted Self-Diagnosis Apps on Three Diagnoses: Two-Year Follow-Up Study.

Journal of medical Internet research
BACKGROUND: Consumer-oriented mobile self-diagnosis apps have been developed using undisclosed algorithms, presumably based on machine learning and other artificial intelligence (AI) technologies. The US Food and Drug Administration now discerns apps...

StackNet-DenVIS: a multi-layer perceptron stacked ensembling approach for COVID-19 detection using X-ray images.

Physical and engineering sciences in medicine
The highly contagious nature of Coronavirus disease 2019 (Covid-19) resulted in a global pandemic. Due to the relatively slow and taxing nature of conventional testing for Covid-19, a faster method needs to be in place. The current researches have su...

Severity and Consolidation Quantification of COVID-19 From CT Images Using Deep Learning Based on Hybrid Weak Labels.

IEEE journal of biomedical and health informatics
Early and accurate diagnosis of Coronavirus disease (COVID-19) is essential for patient isolation and contact tracing so that the spread of infection can be limited. Computed tomography (CT) can provide important information in COVID-19, especially f...