Pathology faces a global shortage of specialists, uneven access to expertise, rising diagnostic complexity and growing demand for second opinions. Digital and telepathology platforms address part of this, but existing tools tend to trade accessibility against structured, workflow-aware clinical integration. Multimodal medical AI promises diagnostic support, yet raises real concerns about transparency, automation bias and clinical accountability.
What PaiX Net does
PaiX Net is a structured, AI-augmented second-opinion platform built to support collaborative consultation while preserving human ownership of the diagnosis. It brings standardised case templates, moderated expert discussion and human-centred AI assistance into one scalable, browser-based system that meets data-protection requirements.
AI support is placed at defined points in the workflow (case structuring, summarisation and exploratory interpretation), while the diagnostic conclusion stays under expert control.
Designing against automation bias
This was an explicit design constraint rather than an afterthought. AI-generated content is visually separated, collapsed by default, and shown only after the expert has given independent input, so the model cannot anchor the reader’s first impression.
The platform uses a multimodal medical AI model (MedGemma-4B), chosen for its open availability and computational efficiency, fine-tuned on curated, anonymised consultation cases. An illustrative retrospective evaluation shows substantial reductions in case preparation time alongside modest but consistent gains elsewhere.