Work Force

Fractional whale driving training-based optimization enabled transfer learning for detecting autism spectrum disorder.

Autism Spectrum Disorder (ASD) is a neurological illness that degrades communication and interaction...

The path to the G protein-coupled receptor structural landscape: Major milestones and future directions.

G protein-coupled receptors (GPCRs) play a crucial role in cell function by transducing signals from...

Developing Machine Vision in Tree-Fruit Applications-Fruit Count, Fruit Size and Branch Avoidance in Automated Harvesting.

Recent developments in affordable depth imaging hardware and the use of 2D Convolutional Neural Netw...

Mental issues, internet addiction and quality of life predict burnout among Hungarian teachers: a machine learning analysis.

BACKGROUND: Burnout is usually defined as a state of emotional, physical, and mental exhaustion that...

Adoption of Artificial Intelligence-Enabled Robots in Long-Term Care Homes by Health Care Providers: Scoping Review.

BACKGROUND: Long-term care (LTC) homes face the challenges of increasing care needs of residents and...

Robot-assisted gait training in patients with various neurological diseases: A mixed methods feasibility study.

BACKGROUND: Walking impairment represents a relevant symptom in patients with neurological diseases ...

Balancing act: the complex role of artificial intelligence in addressing burnout and healthcare workforce dynamics.

Burnout and workforce attrition present pressing global challenges in healthcare, severely impacting...

Inter-participant transfer learning with attention based domain adversarial training for P300 detection.

A Brain-computer interface (BCI) system establishes a novel communication channel between the human ...

Navigating cultural diversity: harnessing AI for mental health diagnosis despite value-laden judgements.

Deep learning applications for quantitative and qualitative PET in PET/MR: technical and clinical unmet needs.

We aim to provide an overview of technical and clinical unmet needs in deep learning (DL) applicatio...

SNN-BERT: Training-efficient Spiking Neural Networks for energy-efficient BERT.

Spiking Neural Networks (SNNs) are naturally suited to process sequence tasks such as NLP with low p...

A preliminary study on the effects of long-term robot suit exercise training on gait function and quality of life in patients with spinal and bulbar muscular atrophy.

Spinal and bulbar muscular atrophy (SBMA) progressively impairs gait function, resulting in the need...

Automated Bio-AFM Generation of Large Mechanome Data Set and Their Analysis by Machine Learning to Classify Cancerous Cell Lines.

Mechanobiological measurements have the potential to discriminate healthy cells from pathological ce...

Deep Learning-Based Model for Non-invasive Hemoglobin Estimation via Body Parts Images: A Retrospective Analysis and a Prospective Emergency Department Study.

Anemia is a significant global health issue, affecting over a billion people worldwide, according to...

Artificial intelligence facilitates the potential of simulator training: An innovative laparoscopic surgical skill validation system using artificial intelligence technology.

PURPOSE: The development of innovative solutions, such as simulator training and artificial intellig...

Gait pattern modification based on ground contact adaptation using the robot-assisted training platform (RATP).

Robot-assisted rehabilitation and training systems are utilized to improve the functional recovery o...

Focal liver lesion diagnosis with deep learning and multistage CT imaging.

Diagnosing liver lesions is crucial for treatment choices and patient outcomes. This study develops ...

Multimodal representations of biomedical knowledge from limited training whole slide images and reports using deep learning.

The increasing availability of biomedical data creates valuable resources for developing new deep le...

Intraoperative detection of parathyroid glands using artificial intelligence: optimizing medical image training with data augmentation methods.

BACKGROUND: Postoperative hypoparathyroidism is a major complication of thyroidectomy, occurring whe...

Simulation training in mammography with AI-generated images: a multireader study.

OBJECTIVES: The interpretation of mammograms requires many years of training and experience. Current...

Foundation models in gastrointestinal endoscopic AI: Impact of architecture, pre-training approach and data efficiency.

Pre-training deep learning models with large data sets of natural images, such as ImageNet, has beco...