AIMC Topic: Humans

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Pattern Recognition of Spiking Neural Networks Based on Visual Mechanism and Supervised Synaptic Learning.

Neural plasticity
Electrophysiological studies have shown that mammalian primary visual cortex are selective for the orientations of visual stimuli. Inspired by this mechanism, we propose a hierarchical spiking neural network (SNN) for image classification. Grayscale ...

Discrimination of alcohol dependence based on the convolutional neural network.

PloS one
In this paper, a total of 20 sites of single nucleotide polymorphisms (SNPs) on the serotonin 3 receptor A gene (HTR3A) and B gene (HTR3B) are used for feature fusion with age, education and marital status information, and the grid search-support vec...

Traditional and New Methods of Bone Age Assessment-An Overview.

Journal of clinical research in pediatric endocrinology
Bone age is one of biological indicators of maturity used in clinical practice and it is a very important parameter of a child’s assessment, especially in paediatric endocrinology. The most widely used method of bone age assessment is by performing a...

Conversion rate of laparoscopic or robotic to open sacrocolpopexy: are there associated factors and complications?

International urogynecology journal
OBJECTIVES: To evaluate the conversion rate of laparoscopic or robotic to open sacrocolpopexy and to identify associated factors in a large population-based database.

Machine learning to predict the cancer-specific mortality of patients with primary non-metastatic invasive breast cancer.

Surgery today
PURPOSE: We used five machine-learning algorithms to predict cancer-specific mortality after surgical resection of primary non-metastatic invasive breast cancer.

Deep learning reconstruction for cardiac magnetic resonance fingerprinting T and T mapping.

Magnetic resonance in medicine
PURPOSE: To develop a deep learning method for rapidly reconstructing T and T maps from undersampled electrocardiogram (ECG) triggered cardiac magnetic resonance fingerprinting (cMRF) images.

Identifying gross post-mortem organ images using a pre-trained convolutional neural network.

Journal of forensic sciences
Identifying organs/tissue and pathology on radiological and microscopic images can be performed using convolutional neural networks (CNN). However, there are scant studies on applying CNN to post-mortem gross images of visceral organs. This proof-of-...

A novel approach for personalized response model: deep learning with individual dropout feature ranking.

Journal of pharmacokinetics and pharmacodynamics
Deep learning is the fastest growing field in artificial intelligence and has led to many transformative innovations in various domains. However, lack of interpretability sometimes hinders its application in hypothesis-driven domains such as biology ...