At IDWeek 2025, a premier global infectious disease conference, a research team led by Professor Chien-Chang Lee of National Taiwan University Hospital achieved top honors, winning the IDSA Abstract Award and ranking first among over 3,000 submissions for their breakthrough in AI-predicted bacterial resistance. To address the critical 72-to-96-hour delay in traditional sepsis diagnosis—a window where empirical antibiotic treatment fails in approximately 30% of cases—the team utilized Neural Networks and Large Language Models (LLMs) to analyze over 400,000 mass spectrometry data entries. This innovative approach moves beyond standard bacterial identification to predict drug resistance with over 80% accuracy, offering physicians real-time, precise recommendations for antibiotic selection and dosage. This achievement, realized through the dedication of young researchers and cross-departmental collaboration, not only significantly improves patient prognosis but also highlights Taiwan’s growing leadership in clinical AI and smart healthcare innovation.