AIMC Topic: Algorithms

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Automatic seizure detection based on imaged-EEG signals through fully convolutional networks.

Scientific reports
Seizure detection is a routine process in epilepsy units requiring manual intervention of well-trained specialists. This process could be extensive, inefficient and time-consuming, especially for long term recordings. We proposed an automatic method ...

A meta-learning approach for genomic survival analysis.

Nature communications
RNA sequencing has emerged as a promising approach in cancer prognosis as sequencing data becomes more easily and affordably accessible. However, it remains challenging to build good predictive models especially when the sample size is limited and th...

Motion-flow-guided recurrent network for respiratory signal estimation of x-ray angiographic image sequences.

Physics in medicine and biology
Motion compensation can eliminate inconsistencies of respiratory movement during image acquisitions for precise vascular reconstruction in the clinical diagnosis of vascular disease from x-ray angiographic image sequences. In x-ray-based vascular int...

Deep Learning CT Image Reconstruction in Clinical Practice.

RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
BACKGROUND:  Computed tomography (CT) is a central modality in modern radiology contributing to diagnostic medicine in almost every medical subspecialty, but particularly in emergency services. To solve the inverse problem of reconstructing anatomica...

Scaffold-Constrained Molecular Generation.

Journal of chemical information and modeling
One of the major applications of generative models for drug discovery targets the lead-optimization phase. During the optimization of a lead series, it is common to have scaffold constraints imposed on the structure of the molecules designed. Without...

Predicting hospitalization following psychiatric crisis care using machine learning.

BMC medical informatics and decision making
BACKGROUND: Accurate prediction models for whether patients on the verge of a psychiatric criseis need hospitalization are lacking and machine learning methods may help improve the accuracy of psychiatric hospitalization prediction models. In this pa...

Hybrid-COVID: a novel hybrid 2D/3D CNN based on cross-domain adaptation approach for COVID-19 screening from chest X-ray images.

Physical and engineering sciences in medicine
The novel Coronavirus disease (COVID-19), which first appeared at the end of December 2019, continues to spread rapidly in most countries of the world. Respiratory infections occur primarily in the majority of patients treated with COVID-19. In light...

Artificial intelligence and machine learning-aided drug discovery in central nervous system diseases: State-of-the-arts and future directions.

Medicinal research reviews
Neurological disorders significantly outnumber diseases in other therapeutic areas. However, developing drugs for central nervous system (CNS) disorders remains the most challenging area in drug discovery, accompanied with the long timelines and high...