A research paper by scientists from Sun Yat-sen University Cancer Center represented the largest prospective validation to date of AI-based treatment planning for NPC, demonstrating real-time feasibility, robust generalizability, and consistent clinical quality.

The new research paper, published on May. 18 in the journal Cyborg and Bionic Systems, developed and clinically validated a deep‑learning‑based automated planning system that generates high‑quality treatment plans in real time – within an integrated CT‑linear accelerator (CT‑linac) “all‑in‑one” (AIO) workflow.

A review paper by scientists from Imperial College introduce embodied cross-domain intelligence, a framework for synergistic coupling across physical, biological, computational, and human intelligence, enabling multifunctional, collaborative, and adaptive micro-robotic behavior in dynamic, safety-critical biological settings.

The new research paper, published on May. 14 in the journal Cyborg and Bionic Systems, introduced a unifying concept called embodied cross‑domain intelligence, which weaves together physical, biological, computational, and human intelligence into a synergistic whole.

A new correspondence highlights a critical gap in modern medical education, arguing that digital simulations and virtual reality fail to transmit the hands-on "tacit learning" essential for clinical practice. By attempting to recreate a dissection using the detailed ancient texts of the Roman physician Galen, the study demonstrated that written instructions and digital tools alike cannot replace the physical intuition and judgment gained through real-life, mentored practice. To address this, the correspondence suggests identifying and integrating these unspoken, tacit elements into the design of future digital pedagogical tools to better align with the actual needs of clinical skill acquisition.