Latest AI and machine learning research in surveys for healthcare professionals.
The reliability of autonomous driving sensing systems impacts the overall safety of the driving system. However, perception system fault diagnosis is currently a weak area of research, with limited attention and solutions. In this paper, we present an information-fusion-based fault-diagnosis method for autonomous driving perception systems. To begin, we built an autonomous driving simulation scena...
Machine learning tools have proven useful across biological disciplines, allowing researchers to draw conclusions from large datasets, and opening up new opportunities for interpreting complex and heterogeneous biological data. Alongside the rapid growth of machine learning, there have also been growing pains: some models that appear to perform well have later been revealed to rely on features of ...
While laparoscopic simulation-based training is a well-established component of general surgery training, no such requirement or standardized curricul...
Every research participant has their own personality characteristics. For example, older adults assisted by socially assistive robots (SAR) may have t...
Markerless motion capture methods are continuously in development to target limitations encountered in marker-, sensor-, or depth-based systems. Previ...
Nonintrusive estimation of oxygen uptake (V̇o) is possible with wearable sensor technology and artificial intelligence. V̇o kinetics have been accurat...
The United Nations has set a Sustainable Development Goal in education to be met hopefully by 2030. One of the target areas is to substantially increa...
Rice () is India's major crop. India has the most land dedicated to rice agriculture, which includes both brown and white rice. Rice cultivation creat...
Micro-computed tomography (µCT)-based imaging plays a key role in monitoring disease progression and response to candidate drugs in various animal mod...
Estimation of fractional flow reserve from coronary CTA (FFR-CT) is an established method of assessing the hemodynamic significance of coronary lesio...
Background Automation bias (the propensity for humans to favor suggestions from automated decision-making systems) is a known source of error in human...
Immediate access to the patient in crisis situations, such as cardiac arrest during robotic surgery, can be challenging. We aimed to present a full im...
Background Machine learning (ML) is pervasive in all fields of research, from automating tasks to complex decision-making. However, applications in di...
: The role of the pharmacist in healthcare society is unique, since they are providers of health information and medication counseling to patients. He...
The use of artificial intelligence in neurosurgical education has been growing in recent times. ChatGPT, a free and easily accessible language model, ...
Artificial Intelligence (AI) and machine learning are the current forefront of computer science and technology. AI and related sub-disciplines, includ...
Cerebrovascular imaging is a common examination. Its accurate cerebrovascular segmentation become an important auxiliary method for the diagnosis and ...
While artificial intelligence (AI) and recent developments in deep learning (DL) have sparked interest in medical imaging, there has been little comme...
High resolution poverty mapping supports evidence-based policy and research, yet about half of all countries lack the survey data needed to generate u...
Machine learning (ML) has emerged as a method to determine patient-specific risk for prolonged postoperative opioid use after orthopedic procedures. ...