Latest AI and machine learning research in practice management for healthcare professionals.
Generative artificial intelligence (AI) tools such as ChatGPT, Bard, and Claude have recently become...
Natural language processing techniques are having an increasing impact on clinical care from patient...
Recognition of patient symptoms is core to medicine, research, and public health. We tested four lar...
Annotated language resources are essential for supervised machine learning methods. In the clinical ...
The high-performance computing (HPC) platform for large-scale drug discovery simulation demands sign...
There is growing interest in predictive coding as a model of how the brain learns through prediction...
Falls are a common problem associated with significant morbidity, mortality, and economic costs. Cur...
UNLABELLED: Since the publication of its 2020 position statement on artificial intelligence (AI) in ...
Non-coding RNAs (ncRNAs) play a critical role in the occurrence and development of numerous human di...
Automatic document classification is a common problem that has successfully been addressed with mach...
Clinical information systems have become large repositories for semi-structured and partly annotated...
A semi-structured clinical problem list containing ∼1.9 million de-identified entries linked to ICD-...
From basic research to the bedside, precise terminology is key to advancing medicine and ensuring op...
MOTIVATION: Recent experimental evidence has shown that some long non-coding RNAs (lncRNAs) contain ...
MOTIVATION: Analysis of whole-genome sequencing (WGS) for genetics is still a challenge due to the l...
PURPOSE: Understanding treatment patterns and effectiveness for patients with metastatic prostate ca...
Hebbian theory proposes that ensembles of neurons form a basis for neural processing. It is possible...
The objective of this research was to develop a reproducible method of integrating human patterns of...
Automated coding of diseases can support hospitals in the billing of inpatient cases with the health...
The increasing amount of transcriptomic data has brought to light vast numbers of potential novel RN...
Backpropagation of error (backprop) is a powerful algorithm for training machine learning architectu...