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ML-MS
Machine-Learning and the Future of HPC for MS-Based Omics
asd
Characterization and diagnosis of Autism Spectrum
fmri
Characterization and diagnosis of Autism Spectrum
ml-ms
ML Ecosystem for Mass Spectrometry Data
eeg
MLSPred-Bench: Reference EEG Benchmark for Prediction of Epileptic Seizures
Predicting Epileptic Seizures
HPC-MS
HPC Engine for Mass Spectrometry based Omics Data
software
UtilLLM_EPS
MAESTRO
phyNGSC
HiCOPS & GiCOPS
Temporal Pattern Mining (TPM) algorithm
ProteoRift
Mass-Simulator
MS-Reduce
J-EROS
ASD-DiagNet
preprint
Predicting peptide properties from mass spectrometry data using deep attention-based multitask network and uncertainty quantification
MLSPred-Bench: ML-Ready Benchmark Leveraging Seizure Detection EEG data for Predictive Models
ML-seizure
Paras Parani Advances to University-Wide 3MT Competition
Dr. Umair Mohammad Selected as an AES Fellow
2024 IEEE International Conference on Big Data workshop HPC-BOD Paper Acceptance
CDMA Paper Acceptance
conference
Utilizing Pretrained Vision Transfomers and Large Language Models for Epileptic Seizure Prediction
workshop
Robustness of ML-Based Seizure Prediction Using Noisy EEG Data From Limited Channels
Lightweight Transformer exhibits comparable performance to LLMs for Seizure Prediction: A case for light-weight models for EEG data
Grants
NIH Funding Mechanisms (Research and Development) - part 1
Academia
NIH Funding Mechanisms (Research and Development) - part 1
ML
Alzheimer’s disease-associated gene ranking using PhenoGeneRanker
Predicting Individual’s Cognitive Performance Through Multi-Omics Blood Data Using Hierarchical Input Neural Network - HINN
gene
Alzheimer’s disease-associated gene ranking using PhenoGeneRanker
Predicting Individual’s Cognitive Performance Through Multi-Omics Blood Data Using Hierarchical Input Neural Network - HINN
ADRD
Predicting and Characterizing Alzheimer's Disease & Related Dementias
Alzheimer’s disease-associated gene ranking using PhenoGeneRanker
Predicting Individual’s Cognitive Performance Through Multi-Omics Blood Data Using Hierarchical Input Neural Network - HINN
journal
Machine-learning models for Alzheimer’s disease diagnosis using neuroimaging data: survey, reproducibility, and generalizability evaluation
TA‐RNN: an Attention‐based Time‐aware Recurrent Neural Network Architecture to Predict Progression of Alzheimer’s Disease
Alzheimer’s disease diagnosis using gray matter of T1-weighted sMRI data and vision transformer
mri
Predicting and Characterizing Alzheimer's Disease & Related Dementias
Knight Foundation School of Computing and Information Sciences (KFSCIS)
Florida International University (FIU)
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