513 citations · 686 across the 11 of their papers we have counts for
11 papers
Balanced Area Deprivation Index (bADI): Enhancing social determinants of health indices to strengthen their association with healthcare clinical outcomes, utilization and costs
Mohammad Amin Morid, Robert E Tillman, Eran Halperin
Background: As value-based care expands across the U.S. healthcare system, reducing health disparities has become a priority. Social determinants of health (SDoH) indices, like the…
Healthcare cost prediction for heterogeneous patient profiles using deep learning models with administrative claims data
Mohammad Amin Morid, Olivia R. Liu Sheng
Problem: How can we design patient cost prediction models that effectively address the challenges of heterogeneity in administrative claims (AC) data to ensure accurate, fair, and…
Time Series Prediction using Deep Learning Methods in Healthcare
Mohammad Amin Morid, Olivia R. Liu Sheng, Joseph Dunbar
Traditional machine learning methods face two main challenges in dealing with healthcare predictive analytics tasks. First, the high-dimensional nature of healthcare data needs lab…
Learning Hidden Patterns from Patient Multivariate Time Series Data Using Convolutional Neural Networks: A Case Study of Healthcare Cost Prediction
Mohammad Amin Morid, Olivia R. Liu Sheng, Kensaku Kawamoto +1
Objective: To develop an effective and scalable individual-level patient cost prediction method by automatically learning hidden temporal patterns from multivariate time series dat…
Healthcare Cost Prediction: Leveraging Fine-grain Temporal Patterns
Mohammad Amin Morid, Olivia R. Liu Sheng, Kensaku Kawamoto +3
Objective: To design and assess a method to leverage individuals' temporal data for predicting their healthcare cost. To achieve this goal, we first used patients' temporal data in…
A scoping review of transfer learning research on medical image analysis using ImageNet
Mohammad Amin Morid, Alireza Borjali, Guilherme Del Fiol
Objective: Employing transfer learning (TL) with convolutional neural networks (CNNs), well-trained on non-medical ImageNet dataset, has shown promising results for medical image a…