AIMC Topic: Humans

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Proteome analysis using machine learning approaches and its applications to diseases.

Advances in protein chemistry and structural biology
With the tremendous developments in the fields of biological and medical technologies, huge amounts of data are generated in the form of genomic data, images in medical databases or as data on protein sequences, and so on. Analyzing this data through...

Small Bowel Capsule Endoscopy and artificial intelligence: First or second reader?

Best practice & research. Clinical gastroenterology
Several machine learning algorithms have been developed in the past years with the aim to improve SBCE (Small Bowel Capsule Endoscopy) feasibility ensuring at the same time a high diagnostic accuracy. If past algorithms were affected by low performan...

Improved detection of air trapping on expiratory computed tomography using deep learning.

PloS one
BACKGROUND: Radiologic evidence of air trapping (AT) on expiratory computed tomography (CT) scans is associated with early pulmonary dysfunction in patients with cystic fibrosis (CF). However, standard techniques for quantitative assessment of AT are...

Inherent Haptic Feedback From Supernumerary Robotic Limbs.

IEEE transactions on haptics
Supernumerary Robotics Limbs, or SuperLimbs for short, are wearable extra limbs for augmenting the wearer. SuperLimbs are attached directly to a human and, thereby, transmit a force from the environment to the human body. This inherent haptic feedbac...

Generation of Tactile Data From 3D Vision and Target Robotic Grasps.

IEEE transactions on haptics
Tactile perception is a rich source of information for robotic grasping: it allows a robot to identify a grasped object and assess the stability of a grasp, among other things. However, the tactile sensor must come into contact with the target object...

Haptic and Visual Feedback Assistance for Dual-Arm Robot Teleoperation in Surface Conditioning Tasks.

IEEE transactions on haptics
Contact driven tasks, such as surface conditioning operations (wiping, polishing, sanding, etc.), are difficult to program in advance to be performed autonomously by a robotic system, specially when the objects involved are moving. In many applicatio...

Combining a parallel 2D CNN with a self-attention Dilated Residual Network for CTC-based discrete speech emotion recognition.

Neural networks : the official journal of the International Neural Network Society
A challenging issue in the field of the automatic recognition of emotion from speech is the efficient modelling of long temporal contexts. Moreover, when incorporating long-term temporal dependencies between features, recurrent neural network (RNN) a...

Automated renal segmentation in healthy and chronic kidney disease subjects using a convolutional neural network.

Magnetic resonance in medicine
PURPOSE: Total kidney volume (TKV) is an important measure in renal disease detection and monitoring. We developed a fully automated method to segment the kidneys from T -weighted MRI to calculate TKV of healthy control (HC) and chronic kidney diseas...

MRzero - Automated discovery of MRI sequences using supervised learning.

Magnetic resonance in medicine
PURPOSE: A supervised learning framework is proposed to automatically generate MR sequences and corresponding reconstruction based on the target contrast of interest. Combined with a flexible, task-driven cost function this allows for an efficient ex...

Evaluation of supervised machine-learning methods for predicting appearance traits from DNA.

Forensic science international. Genetics
The prediction of human externally visible characteristics (EVCs) based solely on DNA information has become an established approach in forensic and anthropological genetics in recent years. While for a large set of EVCs, predictive models have alrea...