AIMC Topic: Databases, Factual

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Interpretable machine learning-based predictive modeling of patient outcomes following cardiac surgery.

The Journal of thoracic and cardiovascular surgery
BACKGROUND: The clinical applicability of machine learning predictions of patient outcomes following cardiac surgery remains unclear. We applied machine learning to predict patient outcomes associated with high morbidity and mortality after cardiac s...

Enzyme Databases in the Era of Omics and Artificial Intelligence.

International journal of molecular sciences
Enzyme research is important for the development of various scientific fields such as medicine and biotechnology. Enzyme databases facilitate this research by providing a wide range of information relevant to research planning and data analysis. Over...

Using published pathway figures in enrichment analysis and machine learning.

BMC genomics
Pathway Figure OCR (PFOCR) is a novel kind of pathway database approaching the breadth and depth of Gene Ontology while providing rich, mechanistic diagrams and direct literature support. Here, we highlight the utility of PFOCR in disease research in...

Delving into New Frontiers: assessing ChatGPT's proficiency in revealing uncharted dimensions of general surgery and pinpointing innovations for future advancements.

Langenbeck's archives of surgery
PURPOSE: The advent of artificial intelligence (AI) has significantly influenced various medical domains, including general surgery. This research aims to assess ChatGPT, an AI language model, in its ability to shed light on the historical facets of ...

Research Hotspots and Trends of Social Robot Interaction Design: A Bibliometric Analysis.

Sensors (Basel, Switzerland)
(1) Background: Social robot interaction design is crucial for determining user acceptance and experience. However, few studies have systematically discussed the current focus and future research directions of social robot interaction design from a b...

Guidelines, Consensus Statements, and Standards for the Use of Artificial Intelligence in Medicine: Systematic Review.

Journal of medical Internet research
BACKGROUND: The application of artificial intelligence (AI) in the delivery of health care is a promising area, and guidelines, consensus statements, and standards on AI regarding various topics have been developed.

IDPpub: Illuminating the Dark Phosphoproteome Through PubMed Mining.

Molecular & cellular proteomics : MCP
Global phosphoproteomics experiments quantify tens of thousands of phosphorylation sites. However, data interpretation is hampered by our limited knowledge on functions, biological contexts, or precipitating enzymes of the phosphosites. This study es...

Assessing the applicability and appropriateness of ChatGPT in answering clinical pharmacy questions.

Annales pharmaceutiques francaises
OBJECTIVES: Clinical pharmacists rely on different scientific references to ensure appropriate, safe, and cost-effective drug use. Tools based on artificial intelligence (AI) such as ChatGPT (Generative Pre-trained Transformer) could offer valuable s...

CLOOME: contrastive learning unlocks bioimaging databases for queries with chemical structures.

Nature communications
The field of bioimage analysis is currently impacted by a profound transformation, driven by the advancements in imaging technologies and artificial intelligence. The emergence of multi-modal AI systems could allow extracting and utilizing knowledge ...

Outcome prediction of methadone poisoning in the United States: implications of machine learning in the National Poison Data System (NPDS).

Drug and chemical toxicology
Methadone is an opioid receptor agonist with a high potential for abuse. The current study aimed to compare different machine learning models to predict the outcomes following methadone poisoning. This six-year retrospective longitudinal study utiliz...