AI Medical Compendium Topic

Explore the latest research on artificial intelligence and machine learning in medicine.

Databases, Factual

Showing 601 to 610 of 2902 articles

Clear Filters

A Multidatabase ExTRaction PipEline (METRE) for facile cross validation in critical care research.

Journal of biomedical informatics
Transforming raw EHR data into machine learning model-ready inputs requires considerable effort. One widely used EHR database is Medical Information Mart for Intensive Care (MIMIC). Prior work on MIMIC-III cannot query the updated and improved MIMIC-...

Recent Advancements and Challenges of AIoT Application in Smart Agriculture: A Review.

Sensors (Basel, Switzerland)
As the most popular technologies of the 21st century, artificial intelligence (AI) and the internet of things (IoT) are the most effective paradigms that have played a vital role in transforming the agricultural industry during the pandemic. The conv...

Performance analysis of pretrained convolutional neural network models for ophthalmological disease classification.

Arquivos brasileiros de oftalmologia
PURPOSE: This study aimed to evaluate the classification performance of pretrained convolutional neural network models or architectures using fundus image dataset containing eight disease labels.

Deep neural network for food image classification and nutrient identification: A systematic review.

Reviews in endocrine & metabolic disorders
Technology impacts human life in both the aspects such as positive and negative, which helps in better communication and eliminating geographical boundaries. However, social media and mobile devices may lead to severe health conditions such as sleep ...

Automated assembly of molecular mechanisms at scale from text mining and curated databases.

Molecular systems biology
The analysis of omic data depends on machine-readable information about protein interactions, modifications, and activities as found in protein interaction networks, databases of post-translational modifications, and curated models of gene and protei...

Application of a developed triple-classification machine learning model for carcinogenic prediction of hazardous organic chemicals to the US, EU, and WHO based on Chinese database.

Ecotoxicology and environmental safety
Cancer, the second largest human disease, has become a major public health problem. The prediction of chemicals' carcinogenicity before their synthesis is crucial. In this paper, seven machine learning algorithms (i.e., Random Forest (RF), Logistic R...

ChatGPT: Is this version good for healthcare and research?

Diabetes & metabolic syndrome
BACKGROUND AND AIMS: There have been advancements in artificial intelligence (AI) and deep learning in the past decade. Recently, OpenAI Inc. has launched a new chatbot, called ChatGPT that interacts in a conversational way and its dialogue format ma...

Content and quality of physical activity ontologies: a systematic review.

The international journal of behavioral nutrition and physical activity
INTRODUCTION: Ontologies are a formal way to represent knowledge in a particular field and have the potential to transform the field of health promotion and digital interventions. However, few researchers in physical activity (PA) are familiar with o...

The curse and blessing of abundance-the evolution of drug interaction databases and their impact on drug network analysis.

GigaScience
BACKGROUND: Widespread bioinformatics applications such as drug repositioning or drug-drug interaction prediction rely on the recent advances in machine learning, complex network science, and comprehensive drug datasets comprising the latest research...