Funding

Financing Innovation in Healthcare AI
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Introduction

Securing funding is crucial for advancing research and innovation in healthcare AI. This section provides an overview of various funding opportunities, including research grants, competitions, and entrepreneurship programs, specifically focused on machine learning in healthcare. These resources can help researchers, startups, and innovators to obtain the necessary support and drive significant advancements in the field.

Research Grants

Research grants are essential for supporting groundbreaking projects in healthcare AI. Here are some notable grants dedicated to machine learning applications in healthcare:

NIH Machine Learning for Biomedical and Health Research
Horizon Europe: AI for Health
NIH Artificial Intelligence and Machine Learning in Health
Wellcome Trust Data Science Initiative
NSF Smart and Connected Health (SCH) Program
UKRI AI and Data Science Fellowships
EU EIT Health AI Innovation Grants
Canada CIFAR AI Chairs Program
Gates Foundation AI for Global Health
HHS AI Health Outcomes Challenge
NIH Big Data to Knowledge (BD2K) Initiative
Description
Funds research using machine learning to solve biomedical and health challenges.
Supports AI research in health under the Horizon Europe framework.
Funds AI and machine learning research projects focused on health applications.
Supports data science and AI innovations in healthcare.
Funds interdisciplinary research on smart health systems and AI technologies.
Provides funding for AI and data science researchers to advance healthcare projects.
Supports AI-driven health innovation projects across Europe.
Provides long-term funding for AI research chairs in Canada focusing on health.
Funds AI projects addressing global health challenges.
Supports AI-driven solutions to improve health outcomes and patient care.
Funds big data and AI research to enhance biomedical research and healthcare.
Eligibility
Open to US-based researchers and institutions.
Open to EU-based researchers and institutions.
Open to US-based researchers and institutions.
Open to researchers globally with data science and AI projects.
Open to US-based researchers, interdisciplinary teams.
Open to UK-based AI and data science researchers.
Open to EU-based health innovators and startups.
Open to Canadian researchers in AI.
Open to researchers globally working on AI for global health.
Open to US-based researchers and healthcare organizations.
Open to US-based researchers working on big data and AI in health.

Competitions

Participating in competitions can provide funding, recognition, and opportunities to advance machine learning projects in healthcare. Here are some prominent competitions focused on machine learning in healthcare:

Kaggle Data Science Bowl
IBM Watson AI XPRIZE
GE Healthcare AI Challenge
HHS AI Health Outcomes Challenge
RSNA AI Challenge
MedNIST AI Challenge
MICCAI Grand Challenge
NIH Data Science Challenge
Topcoder Health AI Challenge
AIMed Clinical AI Challenge
AI for Good Global Summit Challenges
Description
Annual competition focusing on data science problems, including healthcare applications.
Global competition encouraging teams to develop AI solutions for various challenges, including healthcare.
Challenges participants to develop AI solutions for healthcare imaging and diagnostics.
Supports AI-driven solutions to improve health outcomes and patient care.
Annual competition hosted by the Radiological Society of North America focusing on AI in radiology.
Challenge to develop AI models for medical imaging classification using the MedNIST dataset.
International competition focused on medical image computing and computer-assisted interventions.
Encourages innovative data science solutions to biomedical and health problems.
Hosts competitions to develop AI solutions for health-related problems.
Challenges participants to develop AI solutions for clinical healthcare problems.
Global competition to develop AI solutions addressing global challenges, including health.
Prize
$100,000+
$5,000,000
$50,000+
$1,000,000
$30,000+
Varies
Varies
$100,000+
Varies
$50,000+
Varies

Entrepreneurship

Pursuing entrepreneurial ventures in healthcare AI requires access to the right resources, mentorship, and funding. Here are some prominent entrepreneurship programs specifically focused on healthcare AI:

Y Combinator
Techstars Healthcare Accelerator
Matter Health
Startup Health
Johnson & Johnson JLABS
MassChallenge HealthTech
EIT Health Catapult
MedTech Innovator
Plug and Play Health
Dreamit HealthTech
Cambridge Judge Entrepreneurship Centre
Description
Accelerator program providing seed funding, mentorship, and networking for startups.
Healthcare-focused accelerator providing funding, mentorship, and access to healthcare networks.
Incubator for health startups, offering workspace, mentorship, and access to a health network.
Global startup incubator providing coaching, funding, and networking for health innovators.
Incubator providing resources, mentorship, and funding to health and life sciences startups.
Startup accelerator providing funding, mentorship, and networking for health tech innovators.
Startup competition and accelerator offering training, mentorship, and funding for health startups.
Accelerator focused on medical technology startups, offering funding, mentorship, and networking.
Innovation platform offering funding, mentorship, and networking opportunities for health startups.
Accelerator providing funding, mentorship, and networking for health tech startups.
Entrepreneurship programs and resources for startups, including healthcare AI innovators.
Eligibility
Open to startups globally in various sectors, including healthcare.
Open to startups focusing on healthcare and AI.
Open to health startups at various stages.
Open to health startups globally.
Open to health and life sciences startups.
Open to health tech startups globally.
Open to European health startups.
Open to medical technology startups globally.
Open to health startups globally.
Open to health tech startups globally.
Open to startups, including healthcare AI, affiliated with the University of Cambridge.