Latest AI and machine learning research in surveys for healthcare professionals.
In this paper, the CD-TWINSAFE is introduced, a V2I-based digital twin for Autonomous Vehicles. The proposed architecture is composed of two stacks running simultaneously, an on-board driving stack that includes a stereo camera for scene understanding, and a digital twin stack that runs an Unreal Engine 5 replica of the scene viewed by the camera as well as returning safety alerts to the cockpit. ...
Background The assessment of physical examination skills in medical education is resource-intensive and prone to inter-rater variability. While artificial intelligence (AI) has successfully automated the grading of clinical notes and transcripts, evaluating the physical techniques themselves-what students do rather than what they say-remains an unsolved challenge. We evaluated whether a multimodal...
Most pseudo-label selection strategies in semi-supervised learning rely on fixed confidence thresholds, implicitly assuming that prediction confidence...
Vision-Language Models (VLMs) offer the ability to generate high-level, interpretable descriptions of complex activities from images and videos, makin...
A model that avoids stereotypes in a lab benchmark may not avoid them in deployment. We show that measured bias shifts dramatically when prompts menti...
BackgroundThe accuracy and safety of generating medication orders by large language models (LLMs) must be demonstrated. Without standardization, perfo...
Learning under unobservable feedback reliability poses a distinct challenge beyond optimization robustness: a system must decide whether to learn from...
When training machine learning (ML) models for potential deployment in a healthcare setting, it is essential to ensure that they do not replicate or e...
Recent works have implemented machine learning based solutions for many complex classification tasks including pulse shape discrimination in radiation...
A range of generative machine learning models for the design of novel molecules and materials have been proposed in recent years. Models that can gene...
Traditional drug discovery and development are time-consuming and expensive. Deep learning-based molecule generation techniques can reduce costs and i...
The way a person moves is a direct reflection of their neurological and musculoskeletal health, yet it remains one of the most underutilized vital s...
Recent work has revisited the infamous task Name that dataset and established that in non-medical datasets, there is an underlying bias and achieved...
Clothes-Changing Re-Identification (CC-ReID) aims to recognize individuals across different locations and times, irrespective of clothing. Existing ...
Explainable artificial intelligence (XAI) has become increasingly important in biomedical image analysis to promote transparency, trust, and clinica...
Open vocabulary Human-Object Interaction (HOI) detection is a challenging
task that detects all
Medical physics and clinical engineering (MPCE) professionals have a critical role in the safe and effective deployment of artificial intelligence (AI...
Despite the remarkable progress of large language models (LLMs) across various domains, their capacity to predict retinopathy of prematurity (ROP) r...
Large language models (LLMs) are rapidly being integrated into psychological research as research tools, evaluation targets, human simulators, and c...
Machine Learning is a diverse field applied across various domains such as computer science, social sciences, medicine, chemistry, and finance. This...