AIMC Topic: Humans

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Modelling prognostic trajectories of cognitive decline due to Alzheimer's disease.

NeuroImage. Clinical
Alzheimer's disease (AD) is characterised by a dynamic process of neurocognitive changes from normal cognition to mild cognitive impairment (MCI) and progression to dementia. However, not all individuals with MCI develop dementia. Predicting whether ...

Computer-aided diagnosis of breast ultrasound images using ensemble learning from convolutional neural networks.

Computer methods and programs in biomedicine
Breast ultrasound and computer aided diagnosis (CAD) has been used to classify tumors into benignancy or malignancy. However, conventional CAD software has some problems (such as handcrafted features are hard to design; conventional CAD systems are d...

Computer-aided tumor detection in automated breast ultrasound using a 3-D convolutional neural network.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Automated breast ultrasound (ABUS) is a widely used screening modality for breast cancer detection and diagnosis. In this study, an effective and fast computer-aided detection (CADe) system based on a 3-D convolutional neur...

Segmentation of breast ultrasound image with semantic classification of superpixels.

Medical image analysis
Breast cancer is a great threat to females. Ultrasound imaging has been applied extensively in diagnosis of breast cancer. Due to the poor image quality, segmentation of breast ultrasound (BUS) image remains a very challenging task. Besides, BUS imag...

Directed EEG neural network analysis by LAPPS (p≤1) Penalized sparse Granger approach.

Neural networks : the official journal of the International Neural Network Society
The conventional multivariate Granger Analysis (GA) of directed interactions has been widely applied in brain network construction based on EEG recordings as well as fMRI. Nevertheless, EEG is usually inevitably contaminated by strong noise, which ma...

EEG based multi-class seizure type classification using convolutional neural network and transfer learning.

Neural networks : the official journal of the International Neural Network Society
Recognition of epileptic seizure type is essential for the neurosurgeon to understand the cortical connectivity of the brain. Though automated early recognition of seizures from normal electroencephalogram (EEG) was existing, no attempts have been ma...

Classification of glomerular hypercellularity using convolutional features and support vector machine.

Artificial intelligence in medicine
Glomeruli are histological structures of the kidney cortex formed by interwoven blood capillaries, and are responsible for blood filtration. Glomerular lesions impair kidney filtration capability, leading to protein loss and metabolic waste retention...

Batch Mode Active Learning on the Riemannian Manifold for Automated Scoring of Nuclear Pleomorphism in Breast Cancer.

Artificial intelligence in medicine
Breast cancer is the most prevalent invasive type of cancer among women. The mortality rate of the disease can be reduced considerably through timely prognosis and felicitous treatment planning, by utilizing the computer aided detection and diagnosis...

[Do artificial intelligence systems reason in the same way as clinicians when making diagnoses?].

La Revue de medecine interne
Clinical reasoning is at the heart of physicians' competence, as it allows them to make diagnoses. However, diagnostic errors are common, due to the existence of reasoning biases. Artificial intelligence is undergoing unprecedented development in thi...