ADHD/ADD

Machine Learning for Analysis of Microscopy Images: A Practical Guide and Latest Trends.

The explosive growth of Machine Learning provided scientists with insights into the data in the ways unattainable using established research techniques. It allowed the detection of biological features that were previously unrecognized and overlooked. Yet, since Machine Learning methodology originates from informatics, many cell biology laboratories experience difficulties with implementing it. In ...

Real-Time Epileptic Seizure Detection Based on Deep Learning.

Epilepsy is one of the most common neurological diseases, and video EEG is the most commonly used examination method for epilepsy diagnosis. However, since the video EEG examination lasts for hours, the escort has a heavy burden, and the large amount of video EEG data needs to be visually checked by the doctor. The real-time detection of epileptic seizures can reduce the stress of the escort and p...

Impact of synthetic noise signature and physiologic ECG signal on designing ML-based ECG noise detection framework.

Automatic signal analysis using artificial intelligence is getting popular in digital healthcare, such as ECG rhythm analysis, where ECG signals are c...

GIRUS-net: A Multimodal Deep Learning Model Identifying Imaging and Genetic Biomarkers Linked to Alzheimer's Disease Severity.

We introduce an explainable deep neural architecture that combines brain structure with genetic influence to improve disease severity prediction in Al...

Model-Independent Learning of Quantum Phases of Matter with Quantum Convolutional Neural Networks.

Quantum convolutional neural networks (QCNNs) have been introduced as classifiers for gapped quantum phases of matter. Here, we propose a model-indepe...

[Artificial intelligence and psychiatry: questions from psychiatrists to ChatGPT].

Psychiatrists and psychotherapists specialising in the fields of addiction, personality disorders, ADHD and suicidal crisis, we questioned the ChatGPT...

Review of Artificial Intelligence-Based Signal Processing in Dialysis: Challenges for Machine-Embedded and Complementary Applications.

Artificial intelligence technology is trending in nearly every medical area. It offers the possibility for improving analytics, therapy outcome, and u...

Upper Limb Movement Decoding Scheme Based on Surface Electromyography Using Attention-Based Kalman Filter Scheme.

Convolutional neural network (CNN)-based models are widely used in human movement decoding based on surface electromyography. However, they capture on...

Challenges and opportunities for mining adverse drug reactions: perspectives from pharma, regulatory agencies, healthcare providers and consumers.

Monitoring drug safety is a central concern throughout the drug life cycle. Information about toxicity and adverse events is generated at every stage ...

Critical appraisal of artificial intelligence-based prediction models for cardiovascular disease.

The medical field has seen a rapid increase in the development of artificial intelligence (AI)-based prediction models. With the introduction of such ...

Designing Deep Neural Networks Robust to Sensor Failure in Mobile Health Environments.

Missing data is a very common challenge in health monitoring systems and one reason for that is that they are largely dependent on different types of ...

Redistributing Ground Reaction Forces During Squatting Using a Cable-Driven Robotic Device.

Squatting is a dynamic task that is often done for strengthening and improving balance. Most squat training systems partially support body weight. How...

Morphological Development at the Evolutionary Timescale: Robotic Developmental Evolution.

Evolution and development operate at different timescales; generations for the one, a lifetime for the other. These two processes, the basis of much o...

S2Snet: deep learning for low molecular weight RNA identification with nanopore.

Ribonucleic acid (RNA) is a pivotal nucleic acid that plays a crucial role in regulating many biological activities. Recently, one study utilized a ma...

Addressing ergonomic, skill acquisition and mentoring constraints that may be contributory to gender disparity in surgery: a 'value add' for robotics?

TF-Unet:An automatic cardiac MRI image segmentation method.

Personalized heart models are widely used to study the mechanisms of cardiac arrhythmias and have been used to guide clinical ablation of different ty...

Deep structural clustering for single-cell RNA-seq data jointly through autoencoder and graph neural network.

Single-cell RNA sequencing (scRNA-seq) permits researchers to study the complex mechanisms of cell heterogeneity and diversity. Unsupervised clusterin...

Food Metabolomics.

Foods contain not only nutrients but also a wide variety of components related to flavor and functionality. Many studies have been conducted on the co...

[Protein modeling and design based on deep learning].

The accumulation of protein sequence and structure data allows researchers to obtain large amount of descriptive information, simultaneously it poses ...

The difficult role of Artificial Intelligence in Medical Liability: to err is not only human.

The entrance of Artificial Intelligence (AI) as a new actor in the doctor-patient relationship has encouraged important legal and ethi-cal considerati...