datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
clinical-fluid-balance-renal-response-coherence-risk-v0.1What this repo is for
Detect when
fluid balance signals
and
renal management
fall out of alignment
before
acute kidney injury
or fluid overload harm.
ABX-HT-002_renal_clearance_decoupling-v0.1ABX-HT-002 Renal Clearance Decoupling
Purpose
Detect early kidney function marker drift that no longer tracks drug levels.
Core pattern
stress_index high
exposure_index high
renal_coherence_index drops
egfr_drop_vs_expected or creatinine_rise_vs_expected stays high
later_severe_aki_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_mg_L… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/ABX-HT-002_renal_clearance_decoupling-v0.1.clinical-fluid-balance-renal-function-coherence-risk-v0.1What this repo is for
Detect when fluid strategy
and renal function signals
fall out of alignment
before
fluid overload
or avoidable AKI.
clinical-quad-ddi-renal-drift-conmed-change-attribution-bias-v0.1
Clinical Quad: DDI Risk × Renal Drift × Concomitant Meds Change × AE Attribution Bias
This dataset targets a trial failure pattern where safety signals get misread.
High drug–drug interaction risk exists.Renal function drifts.Concomitant meds shift during the trial.AE attribution gets biased toward “not drug related”.
That four-way coupling can hide a real safety problem until it becomes a serious event.
Variables
ddi_risk (low | medium | high)
renal_drift (yes | no)… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-ddi-renal-drift-conmed-change-attribution-bias-v0.1.clinical-renal-function-nephrotoxic-dosing-coherence-risk-v0.1What this repo is for
Detect when renal function trends
and nephrotoxic drug dosing
fall out of alignment
before
avoidable acute kidney injury
dose toxicity
or under-treatment.
clinical-quad-renal-stress-buffer-lag-coupling-aki-transition-v0.7What this repo does
This repository contains a Clarus v0.7 dataset modeling trauma deterioration using a quad-coupling system representation.
The dataset extends the v0.6 intervention layer by introducing uncertainty geometry.
The question addressed by earlier versions was:
Can the system be stabilized?
v0.7 adds a second critical question:
How confident are we in that conclusion?
This allows Clarus to distinguish three operational states:
• confident deterioration
• confident stabilization
•… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-renal-stress-buffer-lag-coupling-aki-transition-v0.7.clinical-quad-dose-renal-conmed-time-safety-drift-v0.1Clinical Quad Dose–Renal–ConMed–Time Safety Drift v0.1
What this dataset is
You test whether a model can detect when a patient is about to experience a safety event in a drug trial.
Each row represents a patient state during treatment.
Core quad coupling
Dose levelRenal functionConcomitant medication loadTime on treatment
The label asks
Will an adverse event occur in the next 7 days
Why this matters
Most safety models track single variables.
This dataset tests interaction drift between dose… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-quad-dose-renal-conmed-time-safety-drift-v0.1.clinical-renal-buffer-exhaustion-v0.1
clinical-renal-buffer-exhaustion-v0.1
What this dataset does
This dataset evaluates whether models can detect instability caused by renal buffering failure.
Each row represents a simplified renal regulation scenario observed across three time points.
The task is to determine whether renal buffering remains stable or is moving toward renal instability.
Core stability idea
The kidney stabilizes metabolic and electrolyte balance through filtration, excretion, and… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-renal-buffer-exhaustion-v0.1.clinical-renal-filtration-instability-v0.1
clinical-renal-filtration-instability-v0.1
What this dataset does
This dataset evaluates whether models can detect instability in renal filtration and waste clearance.
Each row represents a simplified kidney function monitoring scenario observed across three time points.
The task is to determine whether renal filtration remains stable or is moving toward renal instability.
Core stability idea
Kidney stability depends on interaction between filtration capacity… See the full description on the dataset page: https://huggingface.co/datasets/ClarusC64/clinical-renal-filtration-instability-v0.1.testrenal-food-db