A Machine Learning Framework for Detecting and Mitigating Cultural Bias in Autism Spectrum Disorder Screening (2025)
Author: Mohammad Motaghianfar Abstract Background: Autism screening tools like the AQ-10 were largely developed in Western settings. When used[…]
Explainable AI Reveals Healthcare Cost Determinants When Accurate Forecasting Fails (2025)
Author: Mohammad Motaghianfar Abstract Background: Healthcare costs are rising quickly, and understanding what drives them has become essential. Traditional[…]
Cross-Attention Fusion for Early Crop Stress Prediction and the Challenge of Limited Temporal Patterns in Agricultural Data (2025)
Author: Mohammad Motaghianfar Abstract Farming faces growing challenges from climate change and pests, making early crop stress detection vital[…]
Estimating the Health Impact of Multi-Pollutant Reduction Strategies Using Double Machine Learning (2024)
Author: Mohammad Motaghianfar Abstract Heart disease is a global killer, and lifestyle changes like quitting smoking are key to[…]
Personalized Cardiovascular Disease Prevention: Estimating Heterogeneous Treatment Effects of Lifestyle Interventions Using Causal Machine Learning (2024)
Author: Mohammad Motaghianfar Abstract Heart disease is a major global health issue, and lifestyle changes like quitting smoking are[…]
A Hybrid Deep Ensemble and Evidential Regression Framework for Dual Uncertainty Quantification in Agricultural Yield Prediction (2024)
Author: Mohammad Motaghianfar Abstract Predicting crop yields accurately is vital for ensuring food security worldwide, but most machine learning[…]
Contrastive Pre-training for Data-Efficient Parkinson’s Disease Detection from Speech Signals (2023)
Author: Mohammad Motaghianfar Abstract Parkinson’s Disease (PD) affects millions globally, with speech changes often appearing early. Most AI models[…]
Interpretable Machine Learning Identifies Data-Driven Critical Thresholds for Water Potability Assessment (2023)
Author: Mohammad Motaghianfar Abstract Access to clean drinking water is a major global health issue. Traditional methods rely on[…]
Causal AI Reveals Potential Harm of Standard Hemodynamic Management: A Double Machine Learning Study of Critical Care Patients (2023)
Author: Mohammad Motaghianfar Abstract Keeping blood pressure (mean arterial pressure, MAP) above 65 mmHg is standard in critical care,[…]
Temporal-Transformer Framework for Credit Card Fraud Detection: Leveraging Sequential Patterns in Highly Imbalanced Data (2022)
Author: Mohammad Motaghianfar Abstract Credit card fraud costs billions yearly and is tough to catch due to rare cases[…]
Deep Phenotyping of Coronary Artery Disease Using Unsupervised Deep Learning Reveals Three Distinct Clinical Subtypes (2022)
Author: Mohammad Motaghianfar Abstract Coronary Artery Disease (CAD) varies widely in how it affects people, making personalized treatment tricky.[…]
Optimizing Crop Selection and Resource Allocation in Multi-Seasonal Indian Agriculture Using Deep Reinforcement Learning (2022)
Author: Mohammad Motaghianfar Abstract Indian farming, with its diverse seasonal cycles, struggles to pick the best crops and use[…]
Multi-View Evidential Deep Learning with Uncertainty Quantification for Robust Breast Cancer Diagnosis (2021)
Author: Mohammad Motaghianfar Abstract Breast cancer diagnosis with AI faces hurdles like uneven datasets, overly confident wrong predictions, and[…]
Unsupervised Learning of Cardiovascular Aging Trajectories from Cross-Sectional Population Data Reveals Critical Early-Adulthood Divergence (2021)
Author: Mohammad Motaghianfar Abstract Heart disease varies widely as people age, but tracking it over time is costly and[…]
Precision Crop Recommendation Using Multi-Feature Soil and Climatic Analysis for Sustainable Agriculture (2021)
Author: Mohammad Motaghianfar Abstract Sustainable farming is key to feeding a growing world amid climate shifts and soil decline.[…]
Stacked Ensemble Modeling with Domain-Specific Clustering for Robust Loan Approval Classification (2021)
Author: Mohammad Motaghianfar Abstract Background: Accurate loan approval classification is critical for financial risk management. Traditional machine learning models often[…]