🚀 StabilarityHub Leads International MedAI Hackathon 2025: Transforming Healthcare with AI

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DOI: 10.5281/zenodo.18752914  25stabilfr·wuedophcgmx
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Celebrating the International MedAI Hackathon 2025 — where 50+ innovators from Ukraine, Germany and beyond collaborated to build transformative AI solutions in radiology, mental health, and healthcare operations. Led by StabilarityHub with ONPU, GROMUS, Innova Clinics, and ScanLab. Discover the winning projects and the future of healthcare technology.

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DOI: 10.5281/zenodo.18752914 25stabilfr·wuedophcgmx
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2025 AI Research Impact: A Year of Transformation

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DOI: 10.5281/zenodo.18752916  50stabilfr·wuedophcgmx
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2025 marked a fundamental shift in artificial intelligence research—transitioning from "powerful tool" to "fundamental infrastructure." This comprehensive review examines the year's transformative achievements across model efficiency, reasoning capabilities, multimodal intelligence, and real-world deployment. We analyze key breakthroughs including the evolution of the Gemini model series, the e...

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DOI: 10.5281/zenodo.18752916 50stabilfr·wuedophcgmx
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Google Antigravity: Redefining AI-Assisted Software Development

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DOI: 10.5281/zenodo.18752918  17stabilfr·wuedophcgmx
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Google Antigravity, launched November 2025, represents the next generation of AI-assisted coding. It's not a tool that suggests code—it's a developer that works alongside you.

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DOI: 10.5281/zenodo.18752918 17stabilfr·wuedophcgmx
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Pixel 10 & AI Integration: The Agentic Phone Era Begins

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DOI: 10.5281/zenodo.18752920  25stabilfr·wuedophcgmx
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Pixel 10 represents a watershed moment: the first phone designed from the ground up to be an agentic device. It's not just running AI—it's an AI that runs a phone.

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DOI: 10.5281/zenodo.18752920 25stabilfr·wuedophcgmx
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AI Transforming Science: Math, Biology, and Discovery 2025

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Journal Commentary
Journal Commentary by Oleh Ivchenko  ·  DOI: 10.5281/zenodo.18748877  47stabilfr·wuedophcgmx
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2025 marked a watershed year for AI-driven scientific discovery, with systems transitioning from computational tools to active research partners. Google DeepMind's AlphaEvolve discovered novel algorithms for fundamental mathematical and computational problems, improving efficiency across Google's infrastructure by 0.7% globally and finding new solutions to open problems that have challenged mat...

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Journal Commentary by Oleh Ivchenko DOI: 10.5281/zenodo.18748877 47stabilfr·wuedophcgmx
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Gemini 3: Google’s Leap in Reasoning and Multimodal AI

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DOI: 10.5281/zenodo.18752922  17stabilfr·wuedophcgmx
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In November 2025, Google unveiled Gemini 3 Pro, marking a watershed moment in AI development. This model represents a quantum leap in reasoning capabilities, multimodal understanding, and raw intelligence.

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DOI: 10.5281/zenodo.18752922 17stabilfr·wuedophcgmx
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Agent Interoperability: Building the AI Economy of Tomorrow

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DOI: 10.5281/zenodo.18752926  17stabilfr·wuedophcgmx
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Today: AI agents are isolated. Cannot collaborate. Cannot discover each other. Tomorrow: an "agent economy" where systems work together seamlessly.

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DOI: 10.5281/zenodo.18752926 17stabilfr·wuedophcgmx
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Hyperscale AI Data Centers: The Infrastructure Revolution

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DOI: 10.5281/zenodo.18752932  17stabilfr·wuedophcgmx
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[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
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Old strategy: build bigger data centers. New strategy: smarter, distributed, efficient systems that do more with less.

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DOI: 10.5281/zenodo.18752932 17stabilfr·wuedophcgmx
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[a]DOI0%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic0%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References2 refs○Minimum 10 references required
[w]Words [REQ]171✗Minimum 1,000 words of article body. Current: 171
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]0✗Cites at least 1 external source(s): links, DOIs or a reference list. Current: 0
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752932
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[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
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[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams0○Mermaid architecture/flow diagrams. Current: 0
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (1 × 60%) + Required (2/4 × 30%) + Optional (1/7 × 10%)
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English as the New Programming Language: AI Coding Revolution

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DOI: 10.5281/zenodo.18752934  17stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted0%○≥80% from verified, high-quality sources
[a]DOI0%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic0%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References2 refs○Minimum 10 references required
[w]Words [REQ]181✗Minimum 1,000 words of article body. Current: 181
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]0✗Cites at least 1 external source(s): links, DOIs or a reference list. Current: 0
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752934
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness0%○≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams0○Mermaid architecture/flow diagrams. Current: 0
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (1 × 60%) + Required (2/4 × 30%) + Optional (1/7 × 10%)

For decades: learning to code was hard. Now: describing what you want is the bottleneck. AI handles syntax, patterns, implementation. Humans handle design and creativity.

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DOI: 10.5281/zenodo.18752934 17stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted0%○≥80% from verified, high-quality sources
[a]DOI0%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic0%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References2 refs○Minimum 10 references required
[w]Words [REQ]181✗Minimum 1,000 words of article body. Current: 181
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]0✗Cites at least 1 external source(s): links, DOIs or a reference list. Current: 0
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752934
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness0%○≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams0○Mermaid architecture/flow diagrams. Current: 0
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (1 × 60%) + Required (2/4 × 30%) + Optional (1/7 × 10%)
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AI in Healthcare 2026: From Research Settings to Real-World Impact

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DOI: 10.5281/zenodo.18752936  49stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted50%○≥80% from verified, high-quality sources
[a]DOI25%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
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[l]Academic25%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References4 refs○Minimum 10 references required
[w]Words [REQ]4,570✓Minimum 1,000 words of article body. Current: 4,570
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]15✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 15
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752936
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness0%○≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (27 × 60%) + Required (4/4 × 30%) + Optional (2/7 × 10%)

Artificial intelligence has transitioned from experimental research to operational deployment across healthcare systems globally. This comprehensive analysis examines the 2026 landscape of medical AI adoption, documenting the gap between regulatory approval—1,200+ FDA-cleared devices—and clinical implementation, where 81% of U.S. hospitals maintain zero AI adoption. We analyze deployment patter...

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DOI: 10.5281/zenodo.18752936 49stabilfr·wuedophcgmx
BadgeMetricValueStatusDescription
[s]Reviewed Sources0%○≥80% from editorially reviewed sources
[t]Trusted50%○≥80% from verified, high-quality sources
[a]DOI25%○≥80% have a Digital Object Identifier
[b]CrossRef0%○≥80% indexed in CrossRef
[i]Indexed0%○≥80% have metadata indexed
[l]Academic25%○≥80% from journals/conferences/preprints
[f]Free Access100%✓≥80% are freely accessible
[r]References4 refs○Minimum 10 references required
[w]Words [REQ]4,570✓Minimum 1,000 words of article body. Current: 4,570
[u]Original [REQ]100%✓≥85% unique sentences (no padding or repeated blocks) and no leaked drafting notes. Current: 100% unique
[e]Evidence [REQ]15✓Cites at least 1 external source(s): links, DOIs or a reference list. Current: 15
[d]DOI [REQ]✓✓Zenodo DOI registered for persistent citation. DOI: 10.5281/zenodo.18752936
[o]ORCID✓✓Author ORCID verified for academic identity
[p]Peer Reviewed—○Peer reviewed by an assigned reviewer
[h]Freshness0%○≥60% of references from 2025–2026. Current: 0%
[c]Data Charts0○Original data charts from reproducible analysis (min 2). Current: 0
[g]Code—○Source code available on GitHub
[m]Diagrams3✓Mermaid architecture/flow diagrams. Current: 3
[x]Cited by0○Referenced by 0 other hub article(s)
Score = Ref Trust (27 × 60%) + Required (4/4 × 30%) + Optional (2/7 × 10%)
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