AIMC Topic: Humans

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Automated ICD coding for primary diagnosis via clinically interpretable machine learning.

International journal of medical informatics
BACKGROUND: Computer-assisted clinical coding (CAC) based on automated coding algorithms has been expected to improve the International Classification of Disease, tenth version (ICD-10) coding quality and productivity, whereas studies oriented to pri...

Distinguishing benign and malignant lesions on contrast-enhanced breast cone-beam CT with deep learning neural architecture search.

European journal of radiology
PURPOSE: To utilize a neural architecture search (NAS) approach to develop a convolutional neural network (CNN) method for distinguishing benign and malignant lesions on breast cone-beam CT (BCBCT).

Bone collision detection method for robot assisted fracture reduction based on force curve slope.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: The application of robot technology in fracture reduction ensures the minimal invasiveness and accurate operation process. Most of the existing robot assisted fracture reduction systems don't have the function of bone collis...

Interpretability of time-series deep learning models: A study in cardiovascular patients admitted to Intensive care unit.

Journal of biomedical informatics
Interpretability is fundamental in healthcare problems and the lack of it in deep learning models is currently the major barrier in the usage of such powerful algorithms in the field. The study describes the implementation of an attention layer for L...

A Multitask Deep-Learning System to Classify Diabetic Macular Edema for Different Optical Coherence Tomography Devices: A Multicenter Analysis.

Diabetes care
OBJECTIVE: Diabetic macular edema (DME) is the primary cause of vision loss among individuals with diabetes mellitus (DM). We developed, validated, and tested a deep learning (DL) system for classifying DME using images from three common commercially...

The absorption and multiplication of uncertainty in machine-learning-driven finance.

The British journal of sociology
Uncertainty about market developments and their implications characterize financial markets. Increasingly, machine learning is deployed as a tool to absorb this uncertainty and transform it into manageable risk. This article analyses machine-learning...

Generation of synthetic PET images of synaptic density and amyloid from F-FDG images using deep learning.

Medical physics
PURPOSE: Positron emission tomography (PET) imaging with various tracers is increasingly used in Alzheimer's disease (AD) studies. However, access to PET scans using new or less-available tracers with sophisticated synthesis and short half-life isoto...

EEG-Based Emotion Recognition by Convolutional Neural Network with Multi-Scale Kernels.

Sensors (Basel, Switzerland)
Besides facial or gesture-based emotion recognition, Electroencephalogram (EEG) data have been drawing attention thanks to their capability in countering the effect of deceptive external expressions of humans, like faces or speeches. Emotion recognit...

Virtual Reality-Based Framework to Simulate Control Algorithms for Robotic Assistance and Rehabilitation Tasks through a Standing Wheelchair.

Sensors (Basel, Switzerland)
The implementation of control algorithms oriented to robotic assistance and rehabilitation tasks for people with motor disabilities has been of increasing interest in recent years. However, practical implementation cannot be carried out unless one ha...

A Study of Deep Learning-Based Face Recognition Models for Sibling Identification.

Sensors (Basel, Switzerland)
Accurate identification of siblings through face recognition is a challenging task. This is predominantly because of the high degree of similarities among the faces of siblings. In this study, we investigate the use of state-of-the-art deep learning ...