5 citations · 6 across the 10 of their papers we have counts for
6 papers · 1 filter
CAMOS: Coupled Oscillatory State-Space Model for Multimodal Clinical Time-Series
Maxx Richard Rahman, Mostafa Hammouda, Wolfgang Maass
Longitudinal clinical cohorts are multimodal, irregularly sampled and pervasively incomplete: in ADNI, positron emission tomography and cerebrospinal fluid assays are absent from r…
MedLLM: An Open Medical Language Model at the Sub-Billion Scale
Maxx Richard Rahman, Asim Ahmed, Mihan Mohagheghzadeh +1
Open medical language models have converged on a single scale: every widely used system runs at 7B parameters or more, leaving the sub-billion regime uncharacterized. We present Me…
INCLAIR: Inception-Based Longitudinal Clinical Anomaly Detection with Informed Reasoning
Maxx Richard Rahman, Wolfgang Maass
Detecting anomalies in longitudinal clinical profiles is clinically important but difficult: abnormal evidence is often sparse, patient histories have unequal length, and expert ex…
AgentPLM: Agentic Protein Language Models with Reasoning-Augmented Decoding for Protein Sequence Design
Sahil Rahman, Maxx Richard Rahman
Protein language models (PLMs) are passive oracles: they generate sequences in a single forward pass with no mechanism to consult external biophysical feedback or redirect generati…
LongMoE: Longitudinal Multimodal Learning via Trajectory-Aware Mixture-of-Experts
Maxx Richard Rahman, Prakhar Kumar, Wolfgang Maass
Multimodal clinical learning is increasingly important for integrating diverse patient data, including imaging, text, and personalised health records. However, it faces two fundame…
DiGAN: Diffusion-Guided Attention Network for Early Alzheimer's Disease Detection
Maxx Richard Rahman, Mostafa Hammouda, Wolfgang Maass
Early diagnosis of Alzheimer's disease (AD) remains a major challenge due to the subtle and temporally irregular progression of structural brain changes in the prodromal stages. Ex…