AIMC Topic: Deep Learning

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Cardio-respiratory signal extraction from video camera data for continuous non-contact vital sign monitoring using deep learning.

Physiological measurement
UNLABELLED: Non-contact vital sign monitoring enables the estimation of vital signs, such as heart rate, respiratory rate and oxygen saturation (SpO), by measuring subtle color changes on the skin surface using a video camera. For patients in a hospi...

Evaluation of colorectal cancer subtypes and cell lines using deep learning.

Life science alliance
Colorectal cancer (CRC) is a common cancer with a high mortality rate and a rising incidence rate in the developed world. Molecular profiling techniques have been used to better understand the variability between tumors and disease models such as cel...

Neonatal seizure detection from raw multi-channel EEG using a fully convolutional architecture.

Neural networks : the official journal of the International Neural Network Society
A deep learning classifier for detecting seizures in neonates is proposed. This architecture is designed to detect seizure events from raw electroencephalogram (EEG) signals as opposed to the state-of-the-art hand engineered feature-based representat...

Deep learning improves automated rodent behavior recognition within a specific experimental setup.

Journal of neuroscience methods
Automated observation and analysis of rodent behavior is important to facilitate research progress in neuroscience and pharmacology. Available automated systems lack adaptivity and can benefit from advances in AI. In this work we compare a state-of-t...

Characterizing autism spectrum disorder by deep learning spontaneous brain activity from functional near-infrared spectroscopy.

Journal of neuroscience methods
BACKGROUND: Functional near-infrared spectroscopy (fNIRS) was used to investigate spontaneous hemodynamic fluctuations in the bilateral temporal cortices for typically developing (TD) children and children with autism spectrum disorder (ASD).

Evolving the pulmonary nodules diagnosis from classical approaches to deep learning-aided decision support: three decades' development course and future prospect.

Journal of cancer research and clinical oncology
PURPOSE: Lung cancer is the commonest cause of cancer deaths worldwide, and its mortality can be reduced significantly by performing early diagnosis and screening. Since the 1960s, driven by the pressing needs to accurately and effectively interpret ...

An overview of deep learning algorithms and water exchange in colonoscopy in improving adenoma detection.

Expert review of gastroenterology & hepatology
: Among the Gastrointestinal (GI) Endoscopy Editorial Board top 10 topics in advances in endoscopy in 2018, water exchange colonoscopy and artificial intelligence were both considered important advances. Artificial intelligence holds the potential to...

Deep Green Diagnostics: Urban Green Space Analysis Using Deep Learning and Drone Images.

Sensors (Basel, Switzerland)
Nowadays, more than half of the world's population lives in urban areas, and this number continues increasing. Consequently, there are more and more scientific publications that analyze health problems of people associated with living in these highly...

A Deep Learning-Based End-to-End Composite System for Hand Detection and Gesture Recognition.

Sensors (Basel, Switzerland)
Recent research on hand detection and gesture recognition has attracted increasing interest due to its broad range of potential applications, such as human-computer interaction, sign language recognition, hand action analysis, driver hand behavior mo...

Deep learning tools for the measurement of animal behavior in neuroscience.

Current opinion in neurobiology
Recent advances in computer vision have made accurate, fast and robust measurement of animal behavior a reality. In the past years powerful tools specifically designed to aid the measurement of behavior have come to fruition. Here we discuss how capt...