| ACEi | Angiotensin-Converting Enzyme inhibitors |
| AD | Alzheimer’s Disease |
| ADHD | Attention-Deficit/Hyperactivity Disorder |
| AI | Artificial Intelligence |
| ALS | Amyotrophic Lateral Sclerosis |
| AOR | Adjusted Odds Ratio |
| ARB | Angiotensin II Receptor Blockers |
| ARG | Alzheimer’s Risk Genes |
| ATE | Average Treatment Effect |
| ATSUD | Amphetamine-Type Stimulant Use Disorder |
| AUC | Area Under the curve |
| aSyn | Alpha-synuclein |
| BSL | Baseline |
| CD | Crohn’s Disease |
| CI | Confidence Interval |
| COX-2 | Cyclooxygenase-2 |
| DHP-CCB | Dihydropyridine Calcium Channel Blocker |
| DMF | Dimethyl Fumarate |
| DPP-4 | Dipeptidyl Peptidase-4 |
| ECT | Emulated Clinical Trials |
| EHR/EMR | Electronic Health Record/Electronic Medical Record |
| FDA | Food and Drug Administration |
| FMA | Frequentist Model Averaging |
| GReX | Gene Expression Profiling |
| GWAS | Genome-Wide Association Study |
| HbA1c | Glycated hemoglobin |
| HR | Hazard Ratio |
| IBD | Inflammatory Bowel Diseases |
| IMID | Immune-Mediated Inflammatory Diseases |
| IPTW | Inverse Probability of Treatment Weighting |
| IPW | Inverse Probability Weighting |
| LASSO | Least Absolute Shrinkage and Selection Operator |
| LTP | Long-Term Potentiation |
| MeSH | Medical Subject Headings |
| ML | Machine Learning |
| MPI | Modeling Path Importance |
| MS | Multiple Sclerosis |
| MSM | Marginal Structural Models |
| NLP | Natural Language Processing |
| OR | Odds Ratio |
| OUD | Opioid Use Disorders |
| PCA | Principal Component Analysis |
| PD | 1. Pharmacodynamic; 2. Parkinson’s Disease |
| PK | Pharmacokinetic |
| PSM | Propensity Score Matching |
| PSW | Propensity Score Weighting |
| RR | Relative Risk |
| RWE/RWD | Real-World Evidence/Real-World Data |
| SSL | Semi-Supervised Learning |
| T2DM | Type 2 Diabetes Mellitus |
| UC | Ulcerative Colitis |
| WHO | World Health Organization |