The Problem We're Solving
AIHealthTech is an independent medical AI intelligence platform dedicated to making complex healthcare technology accessible, accurate, and actionable. We synthesize peer-reviewed research, FDA guidance, and clinical trial data into clear insights for researchers, clinicians, and health-tech innovators.
A world where every healthcare professional has instant access to the most current AI evidence.
We believe that when a radiologist in rural Kenya understands how an AI model detects breast cancer as accurately as a board-certified specialist, lives change. When a health minister reads our policy analysis on AI bias, better decisions get made. That's the impact we build toward — every article, every week.
Medical AI is not coming — it is here. Our job is to make sure every clinician, researcher, and patient can navigate it with confidence.
From Launch to Global Platform
Founded
AIHT Tech launches with 3 founding editors and a simple belief: medical AI deserves better science journalism.
First 10K Readers
Our deep-dive on FDA-cleared AI diagnostics goes viral in medical Twitter, crossing 10,000 monthly readers within 90 days.
Newsletter Launch
AIHT Weekly debuts, reaching 5,000 subscribers in its first month — clinicians, researchers, and health tech founders.
9 Categories Established
We formalize our editorial structure with 9 specialized verticals, each with a dedicated expert editor and advisory board.
Research Partnerships
Strategic partnerships with 3 medical schools and 2 AI research institutes to co-produce peer-informed content.
50K Monthly Readers
Platform reaches 50,000 monthly readers across 120+ countries. Named Best Health Tech Publication by Digital Health Awards.
AI Content Studio
Launching our AI-assisted research pipeline and expanding services to hospitals and health-tech companies globally.
Our Core Values
Every article we publish is held to these non-negotiable editorial principles.
Scientific Accuracy
We cite only peer-reviewed research, FDA guidance, and clinical trial data. All statistics include source links. Errors are corrected with full transparency and dated annotations.
Editorial Independence
We accept no paid editorial content. Sponsors are clearly labeled. Our editorial team's opinions are never influenced by advertisers, investors, or affiliated institutions.
Clinical Relevance
Every insight is evaluated for real-world applicability. We prioritize findings that directly impact clinical practice, patient outcomes, and healthcare decision-making.
Global Accessibility
Medical AI impacts every country. We write for both domain experts and first-time readers, ensuring our content is understandable without sacrificing technical depth or nuance.
Experts Behind Every Insight
Our team combines clinical medicine, AI research, and science communication to deliver content that is both accurate and compelling.
Dr. Rachel Kim, MD, PhD
Former Stanford radiologist and AI researcher with 14 years in clinical medicine. Rachel leads editorial strategy and writes our flagship diagnostic AI analyses.
Dr. James Lee, MD
Practicing neuroradiologist at Johns Hopkins with a research focus on deep learning for MRI interpretation. Published in NEJM, Radiology, and Nature Medicine.
Dr. Sarah Park, PhD
Computational biologist and former DeepMind Health researcher. Leads our genomics and drug discovery vertical with a focus on AlphaFold applications and precision oncology.
Dr. Marcus Adeyemi
Bioethicist at the University of Lagos with expertise in AI fairness, algorithmic accountability, and the deployment of AI systems in low- and middle-income healthcare settings.
Dr. Yuki Tanaka, MD
Minimally invasive surgeon and robotics researcher at the University of Tokyo. Covers the latest advances in AI-guided robotic systems and autonomous surgical planning.
Elena Petrov, MSc
Health technology journalist with a background in clinical psychology and digital therapeutics. Covers the human side of AI deployment — patient experience, mental wellness tools, and remote care platforms.
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