93450ab06b
Update missing evaluation runner
2026-07-01 09:19:42 +08:00
84ae07bf48
Add missing training runs script
2026-06-29 15:40:55 +08:00
ca294193f4
Clarify empty extra-info logging
2026-06-29 11:26:48 +08:00
d4a29063d6
Add no extra-info type list
2026-06-29 11:14:50 +08:00
00ccedf82f
Report death distribution parameters for disease attribution
2026-06-29 10:42:32 +08:00
fe826c4052
Defer attribution output until after GPU pass
2026-06-27 16:11:49 +08:00
980dd7c282
Align disease attribution batching with survival evaluator
2026-06-27 16:01:35 +08:00
517d573d3b
Reduce attribution GPU synchronization
2026-06-27 15:56:12 +08:00
20686c128f
Vectorize per-disease attribution batches
2026-06-27 15:51:12 +08:00
8928688aca
Optimize per-disease attribution scanning
2026-06-27 15:43:27 +08:00
8ef88ff325
Pad attribution batches before concatenation
2026-06-27 15:38:32 +08:00
a7e969ae51
Summarize disease mortality attribution by age and sex
2026-06-27 15:33:50 +08:00
34353d33d5
Scan all diseases for mortality attribution
2026-06-27 15:30:38 +08:00
128a8ce655
Add single-disease mortality attribution script
2026-06-27 15:24:15 +08:00
01629cec56
Fix mortality attribution active rows
2026-06-27 14:29:32 +08:00
2ae92da0ec
Stream mortality attribution batches
2026-06-27 14:08:02 +08:00
12265bd248
Batch mortality attribution queries
2026-06-27 13:57:16 +08:00
0b7c866292
Add mortality attribution evaluation
2026-06-27 13:34:30 +08:00
00de2ff4a9
Fix event-free survival inference tensor use
2026-06-27 12:08:19 +08:00
307704f74d
Simplify event-free survival data loading
2026-06-27 12:02:48 +08:00
3cd1109249
Add event-free survival evaluation
2026-06-27 11:48:47 +08:00
df6b45b95a
Clarify all-future model interpretation
2026-06-27 10:53:55 +08:00
6df0435f65
Refactor DeepHealth indices around disease expression
2026-06-26 16:25:36 +08:00
9ec3921bed
Add burden trajectory plotting script
2026-06-26 12:49:21 +08:00
fb873326ee
Keep burden landmark query times consistent
2026-06-26 12:24:51 +08:00
7ee29329f5
Write burden CSV shards in workers
2026-06-26 12:06:57 +08:00
263267f583
Use DataLoader for burden readouts
2026-06-26 11:50:12 +08:00
2b0b20d231
Use fork for Linux burden workers
2026-06-26 11:36:52 +08:00
c5ecbb79f2
Keep burden reduction on GPU
2026-06-26 11:27:44 +08:00
63df61e1dd
Batch burden index readout computation
2026-06-26 11:15:15 +08:00
ee7d363e3d
Support multi-GPU burden index computation
2026-06-26 10:51:56 +08:00
e400dab887
Add burden mapping files and landmark computation
2026-06-26 10:42:36 +08:00
a3bf3a0cd4
Add burden index computation interfaces
2026-06-25 17:15:56 +08:00
0138cbd95b
Add calendar-dated event index utilities
2026-06-22 17:36:04 +08:00
56421eb3f5
Add dist_mode parameter to evaluate_landmark_auc for improved flexibility in evaluation
2026-06-22 09:40:08 +08:00
615f395058
Refactor evaluation device handling in AUC scripts for improved clarity and flexibility
2026-06-20 12:13:58 +08:00
e5ecb714ba
Refactor loss computation and model input handling for improved clarity and efficiency
2026-06-20 11:26:03 +08:00
c3cac6dcea
Refactor dataset.py to remove caching functionality and related methods for improved simplicity
2026-06-18 16:25:55 +08:00
aa8ec5c3ac
Refactor code structure for improved readability and maintainability
2026-06-18 13:07:35 +08:00
1ea72e9133
Refactor DeepHealth model to expand extra-info token handling and update output structure
2026-06-17 14:27:07 +08:00
1757bcd25b
Refactor DeepHealth model and related components
...
- Removed BaselineEncoder and CrossAttention classes from models.py.
- Introduced OtherInfoTokenizer for handling additional token types.
- Updated DeepHealth class to integrate OtherInfoTokenizer and manage extra pooling logic.
- Added support for extra_pool_reduce parameter to control pooling behavior.
- Modified forward methods to return structured output using DeepHealthOutput dataclass.
- Updated training scripts to accommodate changes in model architecture and output handling.
- Enhanced error handling and validation for input shapes and types.
2026-06-17 11:05:10 +08:00
27aefb2f90
Refactor run directory creation to use a unique naming function in training scripts
2026-06-15 14:54:06 +08:00
36ec36c8a8
Add time attention mask handling and baseline class time computation to DeepHealth model
2026-06-15 14:35:10 +08:00
c3e49db859
Enhance DeepHealth model to incorporate CHECKUP state tokens in next-step training and evaluation, update dataset cache versioning, and improve handling of observed event histories.
2026-06-15 14:10:09 +08:00
593ecd2e71
Revert cross-attention integration into GPTBlock
2026-06-15 10:05:13 +08:00
c87c3b9f7c
Add cross-attention support to GPTBlock and update DeepHealth model integration
2026-06-13 17:02:04 +08:00
58f253d9b6
Implement parallel processing for DOA AUC evaluation and enhance task management
2026-06-13 15:45:07 +08:00
76787d2fb2
Add evaluation split handling and dataset subset size to DOA AUC evaluation
2026-06-13 15:39:31 +08:00
46a3dfe628
Add training scripts for all-future and next-step supervision with DeepHealth
...
- Implement `train_all_future.py` for training with query-conditioned all-future supervision.
- Implement `train_next_step.py` for training with next-token/next-time-point supervision.
- Introduce `train_util.py` for shared utility functions including logging, dataset splitting, and model checkpointing.
- Enhance argument parsing for both training scripts to accommodate new parameters.
- Update loss functions and model configurations to support the new training paradigms.
2026-06-13 11:42:04 +08:00
034d8065a7
Refactor bias handling in AUC evaluation scripts to improve robustness and prevent errors when bias is not defined
2026-06-12 17:28:22 +08:00
