HKUMed launches Centre for Health AI Research and Translation to advance human-centered healthcare through AI
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This month, we’re focusing on artificial intelligence (AI), a topic that continues to capture attention everywhere. Here, you’ll find the latest research news, insights, and discoveries shaping how AI is being developed and used across the world.
Updates every hour. Last Updated: 3-Nov-2026 01:15 ET (3-Nov-2026 06:15 GMT/UTC)
- Professor Uichin Lee’s team in the Department of AI Computing develops a technology that identifies daily stress from repeated behaviors within smartphone apps
- Analysis of data from 26 people in their 20s and 30s shows that personalized models achieve an average accuracy of about 75%
- Analyzing only a few behaviors, such as chatting and payment, still outperforms the conventional approach, showing potential for long-term monitoring
Brain connectivity findings support individualized targeting of this groundbreaking therapy
What does it take for an autonomous robot to be faster around a course than human drone-pilots? At these dizzying speeds, humans need lightning-fast reflexes. Researchers at Delft University of Technology (The Netherlands) have developed an AI system that enables a racing drone to navigate demanding courses at extreme speed using only a single camera. It outperformed even former world champion human drone-pilots in a race. Now published in Science Robotics, the scientific work behind this accomplishment shows how compact, efficient neural-network-based control can achieve high-performance autonomous flight under real-world conditions. The underlying principles could help advance a much broader class of autonomous robots, from vehicles to mobile and humanoid systems.
In this issue of Science Translational Medicine, two Editorials and two Viewpoint articles dive into the latest challenges and opportunities in humanity’s fight against antimicrobial resistance. Highlighted topics include the grave danger posed by drug-resistant tuberculosis and the rollout of AI technologies to streamline the discovery of antibiotics.
In the first Editorial, Mark Woolhouse considers the paramount importance of a simple but fundamental concept in antibiotic therapy: “Prevention is better than cure.” He discusses the dire lack of access to frontline antibiotics in low- and middle-income countries, and stresses that new antibiotics will not solve the problem of drug resistance in the long term. Woolhouse argues that investing resources into preventative frameworks such as infection prevention and control (IPC) and water, sanitation, and hygiene (WASH) would improve the health of millions with only minimal risk, while also reducing demand for antibiotics and extending their lifespans.
In the second Editorial, Cesar Roque-Borda, João Perdigão, and Fernando Pavan sound the alarm against the emergence of strains of tuberculosis that can resist rifampicin, the backbone of tuberculosis care. They write about how these strains mark an inflection point in antimicrobial resistance, and highlight the urgent need for an effective tuberculosis vaccine. They also call for holistic control measures that integrate genomics and social interventions to combat poverty, malnutrition, and unequal access to care.
Despite these dangers, a Viewpoint from Gianmarco Gasperini and colleagues presents a plethora of new strategies to tackle the threat. These innovations include adoption of modernized commercial models, genomic surveillance, and more streamlined clinical trial designs, which could be integrated with rapidly advancing artificial intelligence platforms and international collaborations to safeguard global health.
Aarti Krishnan and colleagues focus further on how the rise of artificial intelligence is transforming the discovery and design of antibiotics. In their Viewpoint, they survey the latest advances in models built to discover small-molecule and peptide antimicrobials. However, these models also require data standards, validation pipelines, economic incentives, and regulatory frameworks to reach the clinic. “Without them, even the most sophisticated models will remain disconnected from the patients who urgently need new treatments,” the authors write.