Latest AI and machine learning research in risk management for healthcare professionals.
In vitro fertilization-embryo transfer (IVF-ET) stands as one of the most prevalent treatments for infertility. During an IVF-ET cycle, the time interval between trigger shot and oocyte pickup (OPU) is a pivotal period for follicular maturation, which determines mature oocytes yields and impacts the success of subsequent procedures. However, accurately predicting this interval is severely hinder...
The quality of the part fabricated from the Additive Manufacturing (AM) process depends upon the process parameters used, and therefore, optimization is required for apt quality. A methodology is proposed to set these parameters non-iteratively without human intervention. It utilizes Artificial Intelligence (AI) to fully automate the process, with the capability to self-train any apt AI model by...
Despite progresses in data engineering, there are areas with limited consistencies across data validation and documentation procedures causing confu...
With the wide application of new technologies such as large language models and generative artificial intelligence (AI) in the health care sector, art...
The computation of collision probability ($\mathcal{P}_c$) is crucial for space environmentalism and sustainability by providing decision-making kno...
Autonomous agents represent an inevitable evolution of the internet. Current agent frameworks do not embed a standard protocol for agent-to-agent in...
This article argues that the integration of artificial intelligence (AI) into healthcare, particularly under the European Union's Artificial Intellige...
Stress is a natural response of the body to perceived threats, and it can have both positive and negative effects on brain hemodynamics. Stress-induce...
Progress at the intersection of artificial intelligence and pediatric neuroimaging necessitates large, heterogeneous datasets to generate robust and g...
Sleep and circadian rhythms both contribute to cognitive performance, but the underlying neuronal network-level changes remain unclear. We quantified ...
To construct and validate a deep-learning (DL) model for the automatic quantification of temporalis muscle thickness (TMT) in CT head scans. We develo...
Songbirds are essential animal models for studying neuronal and behavioral mechanisms of learned vocalizations. Bengalese finch (Lonchura striata dome...
Propofol is a widely used sedative-hypnotic agent for critically-ill patients requiring invasive mechanical ventilation (IMV). Despite its clinical be...
The Social Determinants of Health (SDoH) have long been recognised as significant drivers of health inequalities. Within healthcare settings, large EH...
Several clinical prediction models have been developed using electronic health records data to help inform decisions about HIV pre-exposure prophylaxi...
Randomized controlled trials (RCTs) can produce valid estimates of the benefits and harms of therapeutic interventions. However, incomplete reporting ...
Data, information and knowledge in health care has expanded exponentially over the last 50 years, leading to significant challenges with information o...
Despite improvements in HIV prevention, treatment, and surveillance, vast disparities remain in access, uptake, and adherence of evidence-based interv...
Accelerated knee MRI protocols using deep learning (DL)-based reconstruction, 3D acquisitions, and parallel imaging can significantly reduce scan time...
Automated detection of papilloedema using artificial intelligence (AI) and retinal images acquired through an ophthalmoscope for triage of patients wi...