AIMC Topic: Humans

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Mixed methods usability evaluation of an assistive wearable robotic hand orthosis for people with spinal cord injury.

Journal of neuroengineering and rehabilitation
BACKGROUND: Robotic hand orthoses (RHO) aim to provide grasp assistance for people with sensorimotor hand impairment during daily tasks. Many of such devices have been shown to bring a functional benefit to the user. However, assessing functional ben...

Minimally invasive percutaneous screw internal fixation under robot navigation for the treatment of a hamate bone fracture.

BMC musculoskeletal disorders
PURPOSE: Hamate fractures are rare fractures of the wrist and there is still no consensus on the optimal treatment for these fractures, especially hook of hamate fractures. Herein, the authors present a case study of a series of patients who were tre...

Prediction of the number of asthma patients using environmental factors based on deep learning algorithms.

Respiratory research
BACKGROUND: Air pollution, weather, pollen, and influenza are typical aggravating factors for asthma. Previous studies have identified risk factors using regression-based and ensemble models. However, studies that consider complex relationships and i...

HostNet: improved sequence representation in deep neural networks for virus-host prediction.

BMC bioinformatics
BACKGROUND: The escalation of viruses over the past decade has highlighted the need to determine their respective hosts, particularly for emerging ones that pose a potential menace to the welfare of both human and animal life. Yet, the traditional me...

AI and semantic ontology for personalized activity eCoaching in healthy lifestyle recommendations: a meta-heuristic approach.

BMC medical informatics and decision making
BACKGROUND: Automated coaches (eCoach) can help people lead a healthy lifestyle (e.g., reduction of sedentary bouts) with continuous health status monitoring and personalized recommendation generation with artificial intelligence (AI). Semantic ontol...

Learning massive interpretable gene regulatory networks of the human brain by merging Bayesian networks.

PLoS computational biology
We present the Fast Greedy Equivalence Search (FGES)-Merge, a new method for learning the structure of gene regulatory networks via merging locally learned Bayesian networks, based on the fast greedy equivalent search algorithm. The method is competi...

Perceptions of Data Set Experts on Important Characteristics of Health Data Sets Ready for Machine Learning: A Qualitative Study.

JAMA network open
IMPORTANCE: The lack of data quality frameworks to guide the development of artificial intelligence (AI)-ready data sets limits their usefulness for machine learning (ML) research in health care and hinders the diagnostic excellence of developed clin...

Deep learning models for automatic tumor segmentation and total tumor volume assessment in patients with colorectal liver metastases.

European radiology experimental
BACKGROUND: We developed models for tumor segmentation to automate the assessment of total tumor volume (TTV) in patients with colorectal liver metastases (CRLM).

Clinical status and future prospects of single-incision robotic-assisted surgery: a review.

International journal of surgery (London, England)
Since the advent of conventional multiport laparoscopic surgery, the prosperity of minimally invasive surgery has been thriving on the advancement of endoscopic techniques. Cosmetic superiority, recovery benefits, and noninferior surgical outcomes we...

Ethical Considerations for Artificial Intelligence in Medical Imaging: Data Collection, Development, and Evaluation.

Journal of nuclear medicine : official publication, Society of Nuclear Medicine
The development of artificial intelligence (AI) within nuclear imaging involves several ethically fraught components at different stages of the machine learning pipeline, including during data collection, model training and validation, and clinical u...