schema · 13 fields

A database of artificial intelligence applications in healthcare

Automate extraction for "A database of artificial intelligence applications in healthcare". Extract structured, evidence-grounded data points directly from hundreds of papers with source page coordinates.

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Schema Field Definitions (13)

Field Name	Data Type	Description
medical_specialty	string	The medical specialty or clinical domain addressed by the AI application, such as Radiology, Pathology, Cardiology, or Oncology.
target_disease_or_condition	string	The specific disease, pathology, or clinical condition targeted by the AI system. Return null if the application is not disease-specific.
clinical_task	string	The specific clinical or operational task performed by the AI system, such as lesion segmentation, mortality risk prediction, automated diagnosis, or triage.
data_modality	string	The primary input data type used to train or evaluate the model, such as Chest X-ray, MRI, EHR tabular records, Whole Slide Images (WSI), or ECG signals.
model_architecture	string	The specific machine learning or deep learning architecture, algorithm, or framework used, such as U-Net, ResNet-50, XGBoost, or Vision Transformer.
total_dataset_size	number	The total numerical count of data instances (e.g., patients, scans, records) included in the study's training, validation, and test datasets combined.
total_dataset_size_unit	string	The unit of measurement corresponding to the total dataset size, such as patients, images, slides, visits, or records, exactly as reported in the study.
validation_method	string	The validation strategy used to evaluate the AI model. Must be one of: Internal split, K-fold cross-validation, External independent cohort, Prospective clinical evaluation. Return null when the paper does not provide enough information to select one.
primary_performance_metric_name	string	The name of the primary metric reported for evaluating model performance on the test/validation cohort, such as AUROC, Sensitivity, Specificity, F1-score, or Dice Similarity Coefficient.
primary_performance_metric_value	number	The numerical score of the primary performance metric reported for the best-performing model on the test or validation set.
primary_performance_metric_unit	string	The unit associated with the extracted primary performance metric value (e.g., %, fraction 0-1), exactly as reported in the paper.
prospective_validation_performed	boolean	True if the AI application was evaluated in a real-time prospective clinical setting or clinical trial within the study; false if validation was solely retrospective.
code_publicly_available	boolean	True if the study authors state that the model code, architecture weights, or implementation scripts are publicly accessible in a repository.

Data Verification Status Taxonomy

To maintain rigorous scientific standards, Sci-database differentiates between automated signals and human audit:

Extracted

Value located and extracted from the full-text PDF by the Kateeb engine.

Model-Agreed

An independent second model produced a compatible value during automated second-pass review.

Human-Reviewed

A named researcher audited the value against the visual page coordinates.

Benchmark-Validated

Performance evaluated against a standardized, published evaluation protocol.

Replicated

An independent external research group reproduced the extraction and experimental result.

A database of artificial intelligence applications in healthcare

Schema Field Definitions (13)

Data Verification Status Taxonomy

Dataset provenance & access