Latest AI and machine learning research in work force for healthcare professionals.
Many stroke patients are expected to rehabilitate at home, which limits their access to proper rehabilitation equipment, treatment, or assessment by therapists. We have developed a novel telerehabilitation system that incorporates a human-upper-limb-like device and an exoskeleton device. The system is designed to provide the feeling of real therapist-patient contact via telerehabilitation. We appl...
High Throughput Screening (HTS) is a common approach in life sciences to discover chemical matter that modulates a biological target or phenotype. However, low assay throughput, reagents cost, or a flowchart that can deal with only a limited number of hits may impair screening large numbers of compounds. In this case, a subset of compounds is assayed, and in silico models are utilized to aid in it...
The dual challenge of increasing numbers of older adults and overall increases in those with some form of insurance is driving the need to develop and...
Artificial neural networks (NNs) represent a relatively recent approach for the prediction of molecular potential energies, suitable for simulations o...
The vast amount and diversity of the content shared on social media can pose a challenge for any business wanting to use it to identify potential cust...
This paper presents a novel electromyography (EMG)-driven hand exoskeleton for bilateral rehabilitation of grasping in stroke. The developed hand exos...
It is unclear how the variability of kinematic errors experienced during motor training affects skill retention and motivation. We used force fields p...
Robots are a promising tool for rehabilitation, and research suggests combining assistance with subject participation to maintain motivation and engag...
Physical therapy is an important component of gait recovery for individuals with locomotor dysfunction. There is a growing body of evidence that sugge...
The aim of this study was to present a new training algorithm using artificial neural networks called multi-objective least absolute shrinkage and sel...
Computer vision models that estimate body mass index (BMI) from facial features offer a non-invasive, low-cost alternative to physical measurement, wi...
Background. Routine service databases are attractive sources of training labels for clinical prediction models, but the processes that write those lab...
Proteins are dynamic molecules existing in diverse conformational states underlying their biological functions. Although recent approaches have enable...
Code-level autonomous research loops (ARLs) have recently emerged as a concrete object of study in automated machine learning research. In such loops,...
Stroke remains a leading cause of mortality and long-term disability worldwide, yet rapid diagnosis is often limited by the shortage of trained radiol...
BACKGROUND Generative AI (genAI) chart summarization tools embedded in electronic health records (EHRs) are being rapidly deployed across U.S. health ...
Large vision-language models (LVLMs) incur substantial inference costs due to their long and highly redundant visual-token sequences. Diversity-based ...
Real-time musculoskeletal (MSK) surrogates could support personalized rehabilitation for children with cerebral palsy (CP), but their credibility depe...
Volatile organic compounds (VOCs) define the distinctive aroma of cannabis and critically influence consumer preference, cultivar authentication, and ...
Oral potentially malignant disorders (OPMDs) precede a subset of oral squamous cell carcinomas (OSCCs), but microbiome studies are difficult to compar...