Datasets:
row_id string | series_id string | timepoint_h int64 | host_model string | drug string | drug_conc_ng_mL int64 | expected_drug_conc_ng_mL int64 | conc_deviation int64 | qtc_ms int64 | expected_qtc_ms int64 | qtc_rise_vs_expected_ms int64 | cardiac_coherence_index float64 | exposure_index float64 | stress_index float64 | later_serious_arrhythmia_flag int64 | assay_method string | source_type string | qt_risk_signal int64 | earliest_qt_risk int64 | notes string |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
ABXHT004-TR-0001 | S1 | 0 | human_sim | azithromycin | 80 | 80 | 0 | 410 | 410 | 0 | 0.9 | 0.1 | 0.1 | 0 | ecg_pk_panel | simulated | 0 | 0 | baseline |
ABXHT004-TR-0002 | S1 | 6 | human_sim | azithromycin | 120 | 120 | 0 | 415 | 415 | 0 | 0.88 | 0.85 | 0.9 | 0 | ecg_pk_panel | simulated | 0 | 0 | tracks expected |
ABXHT004-TR-0003 | S1 | 12 | human_sim | azithromycin | 125 | 120 | 5 | 450 | 420 | 30 | 0.35 | 0.9 | 0.9 | 0 | ecg_pk_panel | simulated | 0 | 0 | first decoupling |
ABXHT004-TR-0004 | S1 | 18 | human_sim | azithromycin | 130 | 120 | 10 | 460 | 420 | 40 | 0.3 | 0.9 | 0.9 | 0 | ecg_pk_panel | simulated | 1 | 1 | confirmed onset |
ABXHT004-TR-0005 | S1 | 48 | human_sim | azithromycin | 140 | 125 | 15 | 520 | 425 | 95 | 0.2 | 0.9 | 0.9 | 1 | ecg_pk_panel | simulated | 1 | 0 | arrhythmia later |
ABXHT004-TR-0006 | S2 | 0 | human_sim | levofloxacin | 90 | 90 | 0 | 405 | 405 | 0 | 0.9 | 0.1 | 0.1 | 0 | ecg_pk_panel | simulated | 0 | 0 | baseline |
ABXHT004-TR-0007 | S2 | 12 | human_sim | levofloxacin | 110 | 110 | 0 | 410 | 410 | 0 | 0.86 | 0.9 | 0.9 | 0 | ecg_pk_panel | simulated | 0 | 0 | stable |
ABXHT004-TR-0008 | S2 | 24 | human_sim | levofloxacin | 110 | 110 | 0 | 412 | 412 | 0 | 0.84 | 0.9 | 0.9 | 0 | ecg_pk_panel | simulated | 0 | 0 | stable |
ABXHT004-TR-0009 | S3 | 0 | human_sim | azithromycin | 120 | 120 | 0 | 490 | 490 | 0 | 0.9 | 0.9 | 0.9 | 1 | ecg_pk_panel | simulated | 0 | 0 | baseline QTc high |
ABXHT004-TR-0010 | S4 | 0 | human_sim | azithromycin | 130 | 120 | 10 | 460 | 420 | 40 | 0.3 | 0.9 | 0.3 | 1 | ecg_pk_panel | simulated | 0 | 0 | stress low |
ABX-HT-004 QT Prolongation Prediction
Purpose
Detect early QT risk when cardiac repolarization markers stop tracking drug levels before serious arrhythmia events.
Core pattern
- stress_index high
- exposure_index high
- cardiac_coherence_index drops
- qtc_rise_vs_expected_ms stays high
- later_serious_arrhythmia_flag appears
Files
- data/train.csv
- data/test.csv
- scorer.py
Schema
Each row is one timepoint in a within series time course.
Required columns
- row_id
- series_id
- timepoint_h
- host_model
- drug
- drug_conc_ng_mL
- expected_drug_conc_ng_mL
- conc_deviation
- qtc_ms
- expected_qtc_ms
- qtc_rise_vs_expected_ms
- cardiac_coherence_index
- exposure_index
- stress_index
- later_serious_arrhythmia_flag
- assay_method
- source_type
- qt_risk_signal
- earliest_qt_risk
Labels
qt_risk_signal
- 1 for rows at or after first confirmed QT risk onset
earliest_qt_risk
- 1 only for the first onset row in that series
Scorer logic in v1
- exclude series with high baseline QTc
- candidate onset point
- stress_index at least 0.80
- exposure_index at least 0.80
- cardiac_coherence_index at most 0.40
- qtc_rise_vs_expected_ms at least 25 for two consecutive points
- ignore one point QTc spike then recovery artifacts
- confirmation
- later_serious_arrhythmia_flag equals 1 later in series
Evaluation
Run
- python scorer.py --path data/test.csv
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