2024-06-29
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Welcome To Gafio

Alliance vision

GAFIO's vision is to revolutionize global cancer care through AI and advanced medical technologies, aiming for a future where cancer is treatable and ultimately curable, with equitable access to innovative healthcare solutions.

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Welcome To Gafio

Mission and Goals

GAFIO's mission is to promote technological advancement and clinical application of AI in oncology, support interdisciplinary and international AI research, and foster excellence in cancer care through education, research, clinical practice, global collaboration, and advocacy.

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Background

Why was GAFIO established

The global incidence of cancer continues to rise, both in high-income countries and, especially, in low- and middle-income countries. In 2020, there were approximately 19.3 million newly diagnosed cancer cases, and 10.0 million cancer-related deaths worldwide. By 2050, the number of cancer cases is predicted to increase 77% to 35 million cases. Meanwhile, the economic cost for cancer treatment and care has been escalating 6%-9% annually, standing at around US$550 billion as of 2020. Moreover, geographic and economic barriers result in significant disparities in cancer survival rates between high-, middle- and low-income countries, for instance 67% in the US, 50% in India, and as low as 30% in sub-Saharan Africa. The escalating cost and complexity of cancer treatment necessitate a radical transformation in cancer care.

19.3 M

diagnosed cancer

10.0 M

related deaths

550 B USD

economic cost

9.0 %

escalating annually

GAFIO offers three types

Membership Types

Professional Background: Individuals applying for membership should have a background or interest in oncology, informatics, artificial intelligence, or related fields.
Qualifications: Applicants may be required to hold a bachelor's degree or higher in a relevant field, such as medicine, informatics, engineering, or related disciplines.
Commitment to GAFIO’s Mission: Prospective members should support GAFIO's mission and goals, which often involve advancing oncology, AI, and patient care through education, research, and collaboration.
Relevant Experience: While not always mandatory, having professional experience or involvement in oncology or AI-related activities can strengthen an individual's application for membership.

Relevant Background:  Open to residents, fellows, and students enrolled in relevant undergraduate, graduate, doctoral, post-doctoral, or resident training programs.
Commitment to GAFIO’s Mission: Prospective members should support GAFIO's mission and goals, which often involve advancing oncology, AI, and patient care through education, research, and collaboration.

Organizational Profile: Corporate members are typically entities such as hospitals, medical institutions, research organizations, and companies involved in healthcare, oncology, AI, or related industries.
Commitment to GAFIO's Mission: Similar to individual members, corporate members should align with GAFIO's mission and goals, especially in areas related to oncology, AI, and healthcare innovation.
Legal Entity Status: Corporate members must have legal entity qualifications or represent social groups with an interest in oncology, AI, or related social welfare activities.
Financial Commitment: Corporate members may be required to pay membership dues or fees based on their organizational size or membership tier.

Latest News

4/15/2025
Interpretable Multimodal Model Enhances Prediction of Chemotherapy Response in Muscle-Invasive Bladder Cancer

A new study published in npj Digital Medicine highlights the potential of an interpretable deep learning framework to improve the prediction of responses to neoadjuvant chemotherapy (NAC) in patients with muscle-invasive bladder cancer (MIBC).

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1/7/2025
AI-based ovarian cancer ultrasound image analysis model performs well in international verification

Stockholm, Sweden – In a groundbreaking study, researchers from the Karolinska Institute, led by Professor Elisabeth Epstein, have developed an AI-driven ultrasound image analysis model that demonstrates exceptional performance in detecting ovarian cancer. Published in Nature Medicine...

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12/30/2024
Enhancing Full-Field Mammogram Classification with the Multi-Scale Region Selection Network (MRSN)

Recently, the journal Medical Image Analysis has accepted an article titled "Multi-scale region selection network in deep features for full-field mammogram classification,"

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Becoming a member

If you have a common vision with us, join us

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Our vision is to democratize cancer care through AI, aiming for a future where cancer is universally curable.

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