Table 2.
The overall organization of the article
| Topic | Work Refs. |
|---|---|
| 1: Introduction | |
| 1.1: Motivation and Contributions | |
| 1.2: Organization of the Article | |
| 2: Generic Chronic Disease Prediction Method | |
| 2.1: Diagnosis Report based Method | |
| 2.2: Pathological Image based Method | |
| 3: Evaluation Metrics | |
| 4: Cancer Prediction Methods | |
| 4.1: Breast Cancer Prediction Methods | |
| 4.1.1: Diagnosis Report based Methods | [6, 36, 43, 49, 66, 67, 72, 73, 98, 109, 121, 122, 129, 149, 165, 166, 202–204] |
| 4.1.2: Pathological Image based Methods | [28, 30, 37, 38, 40, 44, 52, 77, 79, 105, 172, 178, 185, 189, 195, 199, 212, 228, 230] |
| 4.2: Lung Cancer Prediction Methods | |
| 4.2.1: Diagnosis Report based Methods | [47, 49, 53, 87, 132, 151, 153, 161, 169, 180, 183] |
| 4.2.2: Pathological Image based Methods | [9, 13, 16, 104, 117, 152, 198, 209, 216, 218, 222, 231] |
| 4.3: Leukemia Prediction Methods | |
| 4.3.1: Gene Expression based Methods | [27, 55, 63, 70, 94, 114, 187, 188] |
| 4.3.2: Pathological Image based Methods | [2, 125, 142–145, 170, 176, 181, 196, 197] |
| 5: Heart Disease Prediction Methods | |
| 5.1: Single Classifier based Methods | [8, 43, 56, 60, 64, 69, 81, 97, 100, 101, 106, 110, 113, 136, 158, 186, 194, 200, 208] |
| 5.2: Ensemble based Methods | [14, 48, 130, 138, 146] |
| 6: Diabetes Prediction Methods | [19, 39, 43, 46, 54, 81, 82, 84, 99, 102, 111, 154, 160, 168, 173, 182, 202–204, 206, 221, 227] |
| 7: CKD Prediction Methods | [11, 12, 15, 18, 21, 35, 41, 74, 81, 108, 164, 167, 186, 190, 207, 219, 223, 225] |
| 8: Liver Disease Prediction Methods | [1, 4, 22, 43, 45, 80, 83, 112, 118–120, 174, 210, 220] |
| 9: Future Research Directions | |
| 9.1: Exploring more DL Models | |
| 9.2: Designing Sophisticated Data Processing Strategies | |
| 9.2.1: Handling Missing Values | |
| 9.2.2: Exploring more Dimensionality Reduction Strategies | |
| 9.2.3: Designing new FS Strategies | |
| 9.3: Fusing Handcrafted Features with Deep Features | |
| 9.4: Handling Class Imbalance Problem | |
| 9.5: Generating Large-scale Datasets | |
| 9.5.1: New Data Collection | |
| 9.5.2: Generating Synthetic Data | |
| 9.5.3: Preparing Multi-modal Data | |
| 9.6: Medical Image Segmentation | |
| 9.7: Maintaining Ethical and Legal Aspects | |
| 10: Conclusion |