Deep Mind's AI for Smart Healthcare
GPTKB entity
Statements (74)
| Predicate | Object |
|---|---|
| gptkbp:instance_of |
gptkb:Artificial_Intelligence
|
| gptkbp:addressed |
healthcare disparities
|
| gptkbp:aims_to_improve |
patient outcomes
hospital readmissions healthcare efficiency |
| gptkbp:analyzes |
medical data
|
| gptkbp:collaborated_with |
non-profit organizations
academic institutions healthcare providers health technology companies |
| gptkbp:collaborates_with |
gptkb:NHS
|
| gptkbp:contributes_to |
research in AI ethics
|
| gptkbp:created |
AI models for pathology
AI for health risk assessment AI-driven health apps |
| gptkbp:developed_by |
gptkb:Deep_Mind_Technologies
|
| gptkbp:development |
AI for mental health applications
AI for chronic illness management AI for surgical assistance AI solutions for telemedicine AI tools for radiology |
| gptkbp:develops |
AI algorithms
|
| gptkbp:engages_in |
community health programs
patient education initiatives |
| gptkbp:enhances |
diagnostic accuracy
|
| gptkbp:explores |
AI in genomics
AI for rare diseases |
| gptkbp:focuses_on |
healthcare solutions
|
| https://www.w3.org/2000/01/rdf-schema#label |
Deep Mind's AI for Smart Healthcare
|
| gptkbp:is_analyzed_in |
patient feedback
|
| gptkbp:is_designed_to |
assist healthcare professionals
|
| gptkbp:is_engaged_in |
public health research
|
| gptkbp:is_enhanced_by |
patient engagement
personalized medicine |
| gptkbp:is_evaluated_by |
clinical trials
treatment effectiveness AI impact on healthcare costs |
| gptkbp:is_focused_on |
chronic disease management
data privacy and security healthcare accessibility healthcare workforce training |
| gptkbp:is_incorporated_in |
user-centered design principles
|
| gptkbp:is_integrated_with |
electronic health records
|
| gptkbp:is_involved_in |
healthcare policy discussions
healthcare technology assessments |
| gptkbp:is_part_of |
digital health initiatives
AI in healthcare movement |
| gptkbp:is_recognized_for |
innovation in healthcare technology
|
| gptkbp:is_supported_by |
government funding
|
| gptkbp:is_tested_for |
various healthcare settings
|
| gptkbp:is_used_in |
gptkb:medical_imaging
|
| gptkbp:is_utilized_for |
predicting patient deterioration
|
| gptkbp:notable_contributor |
global health initiatives
|
| gptkbp:originated_in |
remote patient monitoring
healthcare research methodologies AI for public health surveillance |
| gptkbp:participated_in |
healthcare hackathons
healthcare innovation challenges |
| gptkbp:promotes |
evidence-based practices
collaborative healthcare solutions data-driven healthcare |
| gptkbp:provides |
predictive analytics
|
| gptkbp:provides_information_on |
patient care
|
| gptkbp:research |
AI for elderly care
AI for health economics. |
| gptkbp:supports |
clinical decision making
|
| gptkbp:utilizes |
gptkb:machine_learning
natural language processing real-time data analysis big data analytics cloud computing technologies interoperable health systems |
| gptkbp:bfsParent |
gptkb:Deep_Mind
|
| gptkbp:bfsLayer |
5
|