ADHD/ADD

Design and Performance Verification of a Novel RCM Mechanism for a Minimally Invasive Surgical Robot.

Minimally invasive surgical robots have the advantages of high positioning accuracy, good stability, and flexible operation, which can effectively improve the quality of surgery and reduce the difficulty for doctors to operate. However, in order to realize the translation of the existing RCM mechanism, it is often necessary to add a mobile unit, which is often bulky and occupies most space above t...

Leukocyte deep learning classification assessment using Shapley additive explanations algorithm.

INTRODUCTION: A peripheral blood smear is a basic test for hematological disease diagnosis. This test is performed manually in many places worldwide, which requires both time and qualified staff. Large laboratories are equipped with digital morphology analyzers, some of which are based on deep learning methods. However, it is difficult to explain to scientists how they work. In this paper, we prop...

Informing clinical assessment by contextualizing post-hoc explanations of risk prediction models in type-2 diabetes.

Medical experts may use Artificial Intelligence (AI) systems with greater trust if these are supported by 'contextual explanations' that let the pract...

Artificial Intelligence and Data Mining for the Pharmacovigilance of Drug-Drug Interactions.

Despite increasing mechanistic understanding, undetected and underrecognized drug-drug interactions (DDIs) persist. This elusiveness relates to an int...

Current Role of Delta Radiomics in Head and Neck Oncology.

The latest developments in the management of head and neck cancer show an increasing trend in the implementation of novel approaches using artificial ...

Constrained neuro fuzzy inference methodology for explainable personalised modelling with applications on gene expression data.

Interpretable machine learning models for gene expression datasets are important for understanding the decision-making process of a classifier and gai...

Improving Protein-Ligand Interaction Modeling with cryo-EM Data, Templates, and Deep Learning in 2021 Ligand Model Challenge.

Elucidating protein-ligand interaction is crucial for studying the function of proteins and compounds in an organism and critical for drug discovery a...

Classification Approach for Attention Assessment via Singular Spectrum Analysis Based on Single-Channel Electroencephalograms.

Attention refers to the human psychological ability to focus on doing an activity. The attention assessment plays an important role in diagnosing atte...

Gradient Tree Boosting for Hierarchical Data.

Gradient tree boosting is a powerful machine learning technique that has shown good performance in predicting a variety of outcomes. However, when app...

Aligning Small Datasets Using Domain Adversarial Learning: Applications in Automated in Vivo Oral Cancer Diagnosis.

Deep learning approaches for medical image analysis are limited by small data set size due to factors such as patient privacy and difficulties in obta...

STC-NLSTMNet: An Improved Human Activity Recognition Method Using Convolutional Neural Network with NLSTM from WiFi CSI.

Human activity recognition (HAR) has emerged as a significant area of research due to its numerous possible applications, including ambient assisted l...

Deep Learning-Based ADHD and ADHD-RISK Classification Technology through the Recognition of Children's Abnormal Behaviors during the Robot-Led ADHD Screening Game.

Although attention deficit hyperactivity disorder (ADHD) in children is rising worldwide, fewer studies have focused on screening than on the treatmen...

Deep-Learning-Based ADHD Classification Using Children's Skeleton Data Acquired through the ADHD Screening Game.

The identification of attention deficit hyperactivity disorder (ADHD) in children, which is increasing every year worldwide, is very important for ear...

An Embedded Framework for Fully Autonomous Object Manipulation in Robotic-Empowered Assisted Living.

Most of the humanoid social robots currently diffused are designed only for verbal and animated interactions with users, and despite being equipped wi...

Deep learning-based assessment of body composition and liver tumour burden for survival modelling in advanced colorectal cancer.

BACKGROUND: Personalized therapy planning remains a significant challenge in advanced colorectal cancer care, despite extensive research on prognostic...

Polyphony: an Interactive Transfer Learning Framework for Single-Cell Data Analysis.

Reference-based cell-type annotation can significantly reduce time and effort in single-cell analysis by transferring labels from a previously-annotat...

Predicting childhood and adolescent attention-deficit/hyperactivity disorder onset: a nationwide deep learning approach.

Attention-deficit/hyperactivity disorder (ADHD) is a heterogeneous disorder with a high degree of psychiatric and physical comorbidity, which complica...

Equipment Identification and Localization Method Based on Improved YOLOv5s Model for Production Line.

Intelligent video surveillance based on artificial intelligence, image processing, and other advanced technologies is a hot topic of research in the u...

Simple add-on robotic traction device to the conventional endoscope: Will it be an efficient and safe tool for novice training on endoscopic submucosal dissection?

A Proactive Attack Detection for Heating, Ventilation, and Air Conditioning (HVAC) System Using Explainable Extreme Gradient Boosting Model (XGBoost).

The advent of Industry 4.0 has revolutionized the life enormously. There is a growing trend towards the Internet of Things (IoT), which has made life ...