New AI femtech competition in Portugal aims to fast-track women’s health innovation

2026-04-10 · Source: Tech.eu - Tech.eu · Field: Health & Wellbeing — Medical Devices & Health Technology, Medical Specialties & Subspecialties · Depth: Advanced, quick

Summary

Portugal is hosting a new AI femtech competition, launched by EmbryoNet-AI in partnership with FemTech Real Money Talks Media, to accelerate innovation in women's health. The initiative targets areas like endometriosis, fertility, and gynaecological cancers, aiming to transform early-stage ideas into working AI solutions by leveraging clinical and imaging data. An open call for submissions is active until April 28, 2026, inviting Portuguese and international teams with strong hypotheses and access to relevant data. The competition seeks projects in drug discovery, diagnostic support, and clinical research, including those using time-series phenotyping or accelerating medical image pre-labelling for mammography, pelvic MRI, ultrasound, or pathology slides. Up to 10 companies will be selected for a Mentor Sprint in early May 2026, culminating in a Live Pitch Day later that month.

Key takeaway

For research scientists and early-stage startups in women's health, this competition offers a significant opportunity to develop AI solutions with expert support and substantial cost savings. If you have a strong hypothesis and access to clinical or imaging data related to gynaecological cancers, endometriosis, or fertility, you should consider applying by April 28, 2026, to gain access to resources, mentorship, and investor connections.

Key insights

A new competition aims to fast-track AI-driven innovation in women's health through targeted challenges and expert mentorship.

Principles

• AI can address underfunded health areas.
• Early-stage ideas benefit from structured development.
• Data access is key for AI solution development.

Method

The competition involves an open call, selection of up to 10 teams, a Mentor Sprint for refinement, and a Live Pitch Day, followed by an 8-10 week build period for the winner.

In practice

• Apply with strong hypotheses and relevant data.
• Focus on gynaecological cancers, endometriosis, fertility.
• Consider medical image pre-labelling solutions.

Topics

• Femtech
• Women's Health
• Artificial Intelligence
• EmbryoNet-AI
• Medical Imaging

Best for: Research Scientist, AI Scientist, Entrepreneur, Director of AI/ML

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Editorial summary, takeaway, and curation by AIssential. Original article published by Tech.eu - Tech.eu.