脂肪肝疾病目前影响全球约三成的成年人，且由于早期通常没有明显症状，许多患者直到病情发展为危及生命的肝衰竭或肝硬化时才被诊断出来。然而，如果在早期发现，这种疾病造成的肝脏损伤是可以透过生活方式的改变或新型药物来逆转并恢复健康的。（关键数字：30）

为了解决早期诊断的困境，医疗专家开始探索人工智慧的应用，希望利用 AI 系统分析大量的电子健康纪录、常规血液检查数据以及胸部 X 光片，从中筛选出隐藏的肝脏脂肪堆积或纤维化高风险患者。这种自动化的背景分析能大幅减轻医生的负担，并及时将合适的患者转介给专科医师。

目前已有如 LiverPRO 与 ALADDIN 等多项 AI 演算法在研究中展现出优于传统指标的准确度，能更精准地预测严重肝脏问题的风险并协助选择适合特定药物治疗的病患。这些技术的普及不仅能减少不必要的侵入性检查与转诊，更能透过早期发现与治疗，为医疗系统省下庞大的开销。

Fatty liver disease currently affects about 30 percent of adults worldwide, and because it usually presents no noticeable symptoms in its early stages, many patients are only diagnosed when the condition progresses to life-threatening liver failure or cirrhosis. However, if detected early, the liver damage caused by this disease is highly reversible through lifestyle changes or novel medications, allowing patients to regain their health.

To address the challenges of early diagnosis, medical experts are exploring the application of artificial intelligence, hoping to use AI systems to analyze vast amounts of electronic health records, routine blood test data, and chest x-rays to identify hidden high-risk patients with liver fat accumulation or fibrosis. This automated background analysis can significantly reduce doctors' workloads and promptly refer appropriate patients to specialists.

Several AI algorithms, such as LiverPRO and ALADDIN, have already demonstrated superior accuracy compared to traditional indexes in predicting the risk of serious liver problems and helping to select patients for specific drug treatments. The widespread adoption of these technologies can not only reduce unnecessary invasive tests and referrals but also save healthcare systems enormous costs through early detection and treatment.