Latest AI and machine learning research in medicare for healthcare professionals.
An on-water remote monitoring robotic system was developed for indirectly estimating the relative density of marine cyanobacteria blooms at the subtidal sandy-rocky beach in Balandra Cove, Baja California Sur, Mexico. The system is based on an unmanned surface vehicle to gather underwater videos of the seafloor for avoiding physical damage on Anabaena sp. cyanobacteria colonies, which grow in tuft...
BACKGROUND: Manual eligibility screening (ES) for a clinical trial typically requires a labor-intensive review of patient records that utilizes many resources. Leveraging state-of-the-art natural language processing (NLP) and information extraction (IE) technologies, we sought to improve the efficiency of physician decision-making in clinical trial enrollment. In order to markedly reduce the pool ...
A sweeping fingerprint sensor converts fingerprints on a row by row basis through image reconstruction techniques. However, a built fingerprint image ...
Expert opinion plays an important role when choosing clusters of chemical compounds for further investigation. Often, the process by which the cluster...
During the past several decades, Escherichia coli has been a treasure chest for molecular biology. The molecular mechanisms of many fundamental cellul...
OBJECTIVE: To estimate the rate of inpatient stay and the factors predicting inpatient status after robotic surgery for endometrial cancer following t...
Background: In Japan, acute inpatient care is divided into approximately 335 secondary medical care areas, which serve as the basic units for planning...
People with Down syndrome have higher age-specific mortality rates compared to the general population as well as peers with other intellectual and dev...
Background. Predicting conversion from mild cognitive impairment (MCI) to Alzheimer's disease (AD) is central to trial enrichment and care planning, y...
Graphical User Interface (GUI) agents powered by vision-language models hold promise for automating real-world mobile tasks. However, progress is limi...
Standard evaluation of many recognition systems contains distribution shift by construction, since benchmarks place disjoint conditions in the trainin...
This study focuses on the relationship between access to Advanced Neonatal Care (ANC) and fertility across the regions in Ghana between 1988 and 2022....
We present Audio-Visual Flamingo (AV-Flamingo), a fully open state-of-the-art audio-visual large language model (AV-LLM) for joint understanding and r...
Foundation models for biology achieve impressive pattern recognition on molecular sequences and single-cell transcriptomics, yet they fail to outperfo...
The cost of healthcare remains a concern in the United States and may have been influenced by disruptions associated with the COVID-19 pandemic. This ...
Long-tailed label distributions reduce the reliability of deep learning for electrocardiogram (ECG) arrhythmia diagnosis, particularly for clinically ...
Text-to-image (T2I) models can synthesize realistic, prompt-aligned images, yet samples generated for the same prompt often cover only a small subset ...
Large language models achieve strong scores on medical benchmarks, yet these benchmarks evaluate each question in isolation, providing no measure of w...
Radiative Gaussian splatting has made sparse-view CT reconstruction fast, but existing methods output point estimates with no notion of where the reco...
Heavy-tailed data arise in many domains where rare events carry disproportionate importance, such as imbalanced image datasets, financial returns, and...