most citedMedformer: A Multi-Granularity Patching Transformer for Medical Time-Series Classification

16 citations · 20 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CV2025

Audio Frequency-Time Dual Domain Evaluation on Depression Diagnosis

Yu Luo, Nan Huang, Sophie Yu +5

Depression, as a typical mental disorder, has become a prevalent issue significantly impacting public health. However, the prevention and treatment of depression still face multipl…

cs.LG2025★ 2 cited

LEAD: An EEG Foundation Model for Alzheimer's Disease Detection

Yihe Wang, Nan Huang, Nadia Mammone +2

Electroencephalography (EEG) provides a non-invasive, highly accessible, and cost-effective approach for detecting Alzheimer's disease (AD). However, existing methods, whether base…

cs.LG2024★ 1 cited

Repurposing Foundation Model for Generalizable Medical Time Series Classification

Nan Huang, Haishuai Wang, Zihuai He +2

Medical time series (MedTS) classification suffers from poor generalizability in real-world deployment due to inter- and intra-dataset heterogeneity, such as varying numbers of cha…

cs.LG2024★ 1 cited

UnitNorm: Rethinking Normalization for Transformers in Time Series

Nan Huang, Christian Kümmerle, Xiang Zhang

Normalization techniques are crucial for enhancing Transformer models' performance and stability in time series analysis tasks, yet traditional methods like batch and layer normali…

eess.SP2024★ 16 cited

Medformer: A Multi-Granularity Patching Transformer for Medical Time-Series Classification

Yihe Wang, Nan Huang, Taida Li +2

Medical time series (MedTS) data, such as Electroencephalography (EEG) and Electrocardiography (ECG), play a crucial role in healthcare, such as diagnosing brain and heart diseases…