ADHD/ADD

Human-Machine Differentiation in Speed and Separation Monitoring for Improved Efficiency in Human-Robot Collaboration.

Human-robot collaborative applications have been receiving increasing attention in industrial applications. The efficiency of the applications is often quite low compared to traditional robotic applications without human interaction. Especially for applications that use speed and separation monitoring, there is potential to increase the efficiency with a cost-effective and easy to implement method...

Artificial intelligence strategy integrating morphologic and architectural biomarkers provides robust diagnostic accuracy for disease progression in chronic lymphocytic leukemia.

Artificial intelligence-based tools designed to assist in the diagnosis of lymphoid neoplasms remain limited. The development of such tools can add value as a diagnostic aid in the evaluation of tissue samples involved by lymphoma. A common diagnostic question is the determination of chronic lymphocytic leukemia (CLL) progression to accelerated CLL (aCLL) or transformation to diffuse large B-cell ...

Automatic Film Label Acquisition Method Based on Improved Neural Networks Optimized by Mutation Ant Colony Algorithm.

Nowadays, with the constant change of public aesthetic standards, a large number of new types and themes of film programs have emerged. For this reaso...

Attention-Based Joint Training of Noise Suppression and Sound Event Detection for Noise-Robust Classification.

Sound event detection (SED) recognizes the corresponding sound event of an incoming signal and estimates its temporal boundary. Although SED has been ...

A novel deep learning model DDU-net using edge features to enhance brain tumor segmentation on MR images.

Glioma is a relatively common brain tumor disease with high mortality rate. Humans have been seeking a more effective therapy. In the course of treatm...

Research on Information Visualization Graphic Design Teaching Based on DBN Algorithm.

With the advent of the era of big data, how to quickly obtain effective information and efficiently disseminate information technology has become the ...

A Novel Handwritten Digit Classification System Based on Convolutional Neural Network Approach.

An enormous number of CNN classification algorithms have been proposed in the literature. Nevertheless, in these algorithms, appropriate filter size s...

Comparing Class-Aware and Pairwise Loss Functions for Deep Metric Learning in Wildlife Re-Identification.

Similarity learning using deep convolutional neural networks has been applied extensively in solving computer vision problems. This attraction is supp...

Deep neural network-estimated electrocardiographic age as a mortality predictor.

The electrocardiogram (ECG) is the most commonly used exam for the evaluation of cardiovascular diseases. Here we propose that the age predicted by ar...

Interpretable and explainable AI (XAI) model for spatial drought prediction.

Accurate prediction of any type of natural hazard is a challenging task. Of all the various hazards, drought prediction is challenging as it lacks a u...

Design of Deep Learning Model for Task-Evoked fMRI Data Classification.

Machine learning methods have been successfully applied to neuroimaging signals, one of which is to decode specific task states from functional magnet...

A novel method for peanut variety identification and classification by Improved VGG16.

Crop variety identification is an essential link in seed detection, phenotype collection and scientific breeding. This paper takes peanut as an exampl...

Amphetamine-type stimulants (ATS) drug classification using shallow one-dimensional convolutional neural network.

Amphetamine-type stimulants (ATS) drug analysis and identification are challenging and critical nowadays with the emergence production of new syntheti...

Machine learning for cardiology.

This paper reviews recent cardiology literature and reports how artificial intelligence tools (specifically, machine learning techniques) are being us...

PHOTONAI-A Python API for rapid machine learning model development.

PHOTONAI is a high-level Python API designed to simplify and accelerate machine learning model development. It functions as a unifying framework allow...

Deep learning prediction of attention-deficit hyperactivity disorder in African Americans by copy number variation.

Current understanding of the underlying molecular network and mechanism for attention-deficit hyperactivity disorder (ADHD) is lacking and incomplete....

Automated Measurements of Body Composition in Abdominal CT Scans Using Artificial Intelligence Can Predict Mortality in Patients With Cirrhosis.

Body composition measures derived from already available electronic medical records (computed tomography [CT] scans) can have significant value, but a...

An automated method for detecting atrial fat using convolutional neural network.

Atrial Fibrillation (A-fib) is a common cardiac rhythm problem in the population these days in which irregular heartbeat leads to blood clots, heart f...

Clinical Application Study of Polymeric Nanospheres Network in Methylphenidate Extraction from Urine Samples by Dispersive Solid Phase Extraction Adsorbent.

This research introduces a polymeric nanosphere as a new dispersive solid phase extraction (DSPE) adsorbent for the extraction of methylphenidate (MP...

Using Artificial Intelligence for High-Volume Identification of Silicosis and Tuberculosis: A Bio-Ethics Approach.

Although Artificial Intelligence (AI) is being increasingly applied, considerable distrust about introducing "disruptive" technologies persists. Intri...