activity
20162024
most citedDeepAD: A Robust Deep Learning Model of Alzheimer's Disease Progression for Real-World Clinical Applications

4 citations · 13 across the 7 of their papers we have counts for

collaborators

7 papers

cs.CL2024★ 1 cited

Speaking the Same Language: Leveraging LLMs in Standardizing Clinical Data for AI

Arindam Sett, Somaye Hashemifar, Mrunal Yadav +2

The implementation of Artificial Intelligence (AI) in the healthcare industry has garnered considerable attention, attributable to its prospective enhancement of clinical outcomes,…

eess.IV2023★ 4 cited

Multiclass Semantic Segmentation to Identify Anatomical Sub-Regions of Brain and Measure Neuronal Health in Parkinson's Disease

Hosein Barzekar, Hai Ngu, Han Hui Lin +6

Automated segmentation of anatomical sub-regions with high precision has become a necessity to enable the quantification and characterization of cells/ tissues in histology images.…

cs.CV2023★ 3 cited

Self-supervised Learning for Segmentation and Quantification of Dopamine Neurons in Parkinson's Disease

Fatemeh Haghighi, Soumitra Ghosh, Hai Ngu +5

Parkinson's Disease (PD) is the second most common neurodegenerative disease in humans. PD is characterized by the gradual loss of dopaminergic neurons in the Substantia Nigra (SN)…

cs.CV2022★ 1 cited

Robust Alzheimer's Progression Modeling using Cross-Domain Self-Supervised Deep Learning

Saba Dadsetan, Mohsen Hejrati, Shandong Wu +1

Developing successful artificial intelligence systems in practice depends on both robust deep learning models and large, high-quality data. However, acquiring and labeling data can…

cs.LG2022★ 4 cited

DeepAD: A Robust Deep Learning Model of Alzheimer's Disease Progression for Real-World Clinical Applications

Somaye Hashemifar, Claudia Iriondo, Evan Casey +2

The ability to predict the future trajectory of a patient is a key step toward the development of therapeutics for complex diseases such as Alzheimer's disease (AD). However, most…

q-bio.MN2017

Computational prediction and analysis of protein-protein interaction networks

Somaye Hashemifar

Biological networks provide insight into the complex organization of biological processes in a cell at the system level. They are an effective tool for understanding the comprehens…

cs.DS2016

Joint alignment of multiple protein-protein interaction networks via convex optimization

Somaye Hashemifar, Qixing Huang, Jinbo XU

Motivation: High-throughput experimental techniques have been producing more and more protein-protein interaction (PPI) data. PPI network alignment greatly benefits the understandi…