Psychiatry

Bipolar Disorder

Latest AI and machine learning research in bipolar disorder for healthcare professionals.

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Deep learning-based activity recognition and fine motor identification using 2D skeletons of cynomolgus monkeys.

Video-based action recognition is becoming a vital tool in clinical research and neuroscientific stu...

A convolutional neural network-based decision support system for neonatal quiet sleep detection.

Sleep plays an important role in neonatal brain and physical development, making its detection and c...

[Identifying Depressive Disorder With Sleep Electroencephalogram Data: A Study Based on Deep Learning].

OBJECTIVE: To explore the effectiveness of using deep learning network combined Vision Transformer (...

Basic performance of domestic surgical robot and the safety and effectiveness of integrated energy equipment.

OBJECTIVES: Surgical robot system has broken the limitation of traditional surgery and shown excelle...

[Surgical Technique for Mesorectal Division in the Robotic Anterior Resection for Rectal Cancer].

Since April 2018, robot-assisted rectal resection has been approved as an insurance medical treatmen...

A social theory-enhanced graph representation learning framework for multitask prediction of drug-drug interactions.

Current machine learning-based methods have achieved inspiring predictions in the scenarios of mono-...

Comparison of Surgical Outcome of Bipolar Scissors with Conventional Cold Dissection Tonsillectomy.

Background The tonsillectomy is the most common Ear, Nose, and Throat (ENT) surgical procedure. Diff...

Robo-Lap Approach Optimizes Intraoperative Outcomes in Robotic Left and Right Hepatectomy.

BACKGROUND: The aim of the present study is to evaluate the possible advantages of the Robo-Lap (par...

Artificial Intelligence-based Detection of Epileptic Discharges from Pediatric Scalp Electroencephalograms: A Pilot Study.

We developed an artificial intelligence (AI) technique to identify epileptic discharges (spikes) in ...

Pilot Mental Health, Methodologies, and Findings: A Systematic Review.

Pilots' mental health has received increased attention following Germanwings Flight 9525 in 2015, w...

Joint Embedding of Structural and Functional Brain Networks with Graph Neural Networks for Mental Illness Diagnosis.

Multimodal brain networks characterize complex connectivities among different brain regions from bot...

A new MAGDM method with 2-tuple linguistic bipolar fuzzy Heronian mean operators.

In this article, we introduce the 2-tuple linguistic bipolar fuzzy set (2TLBFS), a new strategy for ...

Decision support system for the differentiation of schizophrenia and mood disorders using multiple deep learning models on wearable devices data.

In the modern world, with so much inherent stress, mental health disorders (MHDs) are becoming more ...

Major depression disorder diagnosis and analysis based on structural magnetic resonance imaging and deep learning.

Major depression disorder is one of the diseases with the highest rate of disability and morbidity a...

De novo generation of dual-target ligands using adversarial training and reinforcement learning.

Artificial intelligence, such as deep generative methods, represents a promising solution to de novo...

Optimizing Input for Gesture Recognition using Convolutional Networks on HD-sEMG Instantaneous Images.

Hand gesture recognition using high-density surface electromyography (HD-sEMG) has gained increasing...

Discriminating Heterogeneous Trajectories of Resilience and Depression After Major Life Stressors Using Polygenic Scores.

IMPORTANCE: Major life stressors, such as loss and trauma, increase the risk of depression. It is kn...

Probabilistic Contextual and Structural Dependencies Learning in Grammar-Based Genetic Programming.

Genetic Programming is a method to automatically create computer programs based on the principles of...

Multimodal Machine Learning Workflows for Prediction of Psychosis in Patients With Clinical High-Risk Syndromes and Recent-Onset Depression.

IMPORTANCE: Diverse models have been developed to predict psychosis in patients with clinical high-r...

Machine Learning Analysis of Blood microRNA Data in Major Depression: A Case-Control Study for Biomarker Discovery.

BACKGROUND: There is a lack of reliable biomarkers for major depressive disorder (MDD) in clinical p...

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