AIMC Topic: Neural Networks, Computer

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Multimodal temporal-clinical note network for mortality prediction.

Journal of biomedical semantics
BACKGROUND: Mortality prediction is an important task to achieve smart healthcare, especially for the management of intensive care unit. It can provide a reference for doctors to quickly predict the course of disease and customize early intervention ...

Sensitivity analysis for interpretation of machine learning based segmentation models in cardiac MRI.

BMC medical imaging
BACKGROUND: Image segmentation is a common task in medical imaging e.g., for volumetry analysis in cardiac MRI. Artificial neural networks are used to automate this task with performance similar to manual operators. However, this performance is only ...

Biomimetic FPGA-based spatial navigation model with grid cells and place cells.

Neural networks : the official journal of the International Neural Network Society
The mammalian spatial navigation system is characterized by an initial divergence of internal representations, with disparate classes of neurons responding to distinct features including location, speed, borders and head direction; an ensuing converg...

Seeing through disguise: Getting to know you with a deep convolutional neural network.

Cognition
People use disguise to look unlike themselves (evasion) or to look like someone else (impersonation). Evasion disguise challenges human ability to see an identity across variable images; Impersonation challenges human ability to tell people apart. Pe...

Deep learning detection of subtle fractures using staged algorithms to mimic radiologist search pattern.

Skeletal radiology
OBJECTIVE: To develop and evaluate a two-stage deep convolutional neural network system that mimics a radiologist's search pattern for detecting two small fractures: triquetral avulsion fractures and Segond fractures.

DeepHCS: Bright-field to fluorescence microscopy image conversion using multi-task learning with adversarial losses for label-free high-content screening.

Medical image analysis
In this paper, we propose a novel microscopy image translation method for transforming a bright-field microscopy image into three different fluorescence images to observe the apoptosis, nuclei, and cytoplasm of cells, which visualize dead cells, nucl...

A deep learning model (ALNet) for the diagnosis of acute leukaemia lineage using peripheral blood cell images.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Morphological differentiation among blasts circulating in blood in acute leukaemia is challenging. Artificial intelligence decision support systems hold substantial promise as part of clinical practise in detecting haematol...

Predictive Analytics for Care and Management of Patients With Acute Diseases: Deep Learning-Based Method to Predict Crucial Complication Phenotypes.

Journal of medical Internet research
BACKGROUND: Acute diseases present severe complications that develop rapidly, exhibit distinct phenotypes, and have profound effects on patient outcomes. Predictive analytics can enhance physicians' care and management of patients with acute diseases...

TranSynergy: Mechanism-driven interpretable deep neural network for the synergistic prediction and pathway deconvolution of drug combinations.

PLoS computational biology
Drug combinations have demonstrated great potential in cancer treatments. They alleviate drug resistance and improve therapeutic efficacy. The fast-growing number of anti-cancer drugs has caused the experimental investigation of all drug combinations...

A reservoir computing approach for forecasting and regenerating both dynamical and time-delay controlled financial system behavior.

PloS one
Significant research in reservoir computing over the past two decades has revived interest in recurrent neural networks. Owing to its ingrained capability of performing high-speed and low-cost computations this has become a panacea for multi-variate ...