Latest AI and machine learning research in surveys for healthcare professionals.
Ensuring that large language models (LLMs) reflect diverse user values and preferences is crucial as their user bases expand globally. It is therefore encouraging to see the growing interest in LLM personalization within the research community. However, current works often rely on the LLM-as-a-Judge approach for evaluation without thoroughly examining its validity. In this paper, we investigate ...
Federated Learning (FL) is a distributed and privacy-preserving machine learning paradigm that coordinates multiple clients to train a model while keeping the raw data localized. However, this traditional FL poses some challenges, including privacy risks, data heterogeneity, communication bottlenecks, and system heterogeneity issues. To tackle these challenges, knowledge distillation (KD) has be...
Foundation models (FMs) are large-scale deep learning models trained on massive datasets, often using self-supervised learning techniques. These mod...
Data are essential in developing healthcare artificial intelligence (AI) systems. However, patient data collection, access, and use raise ethical co...
In the evolving landscape of computer vision (CV) technologies, the automatic detection and interpretation of gender and emotion in images is a crit...
This study developed an improved dog heart rate and blood oxygen sensor system using Arduino. Traditional methods face accuracy and reliability issu...
The convergence of digital pathology and artificial intelligence could assist histopathology image analysis by providing tools for rapid, automated mo...
PURPOSE: The RECIST guidelines provide a standardized approach for evaluating the response of cancer to treatment, allowing for consistent comparison ...
Machine learning models hold great promise with medical applications, but also give rise to a series of ethical challenges. In this survey we focus on...
This study aimed to evaluate the readability, reliability, and quality of responses by 4 selected artificial intelligence (AI)-based large language mo...
Clinical adoption of deep learning models has been hindered, in part, because the black-box nature of neural networks leads to concerns regarding th...
Predictive biomarkers of treatment response are lacking for metastatic clear cell renal cell carcinoma (ccRCC), a tumor type that is treated with an...
In order to clarify the transmission mechanism of the impact of mechanization on the occupational health of miners and to provide empirical evidence f...
Subdural hematoma is defined as blood collection in the subdural space between the dura mater and arachnoid. Subdural hematoma is a condition that neu...
Artificial intelligence (AI) algorithms are prone to bias at multiple stages of model development, with potential for exacerbating health disparities....
PURPOSE: Evaluation of PD-L1 tumor proportion score (TPS) by pathologists has been very impactful but is limited by factors such as intraobserver/inte...
Background ChatGPT (OpenAI) can pass a text-based radiology board-style examination, but its stochasticity and confident language when it is incorrect...
This study scrutinizes free AI tools tailored for supporting literature review and analysis in academic research, emphasizing their response to direct...
OBJECTIVES: Leveraging artificial intelligence (AI) in conjunction with electronic health records (EHRs) holds transformative potential to improve hea...
Nutcracker phenomenon is the compression of the left renal vein between the superior mesenteric artery (SMA) and the abdominal aorta. Nutcracker synd...