Evaluate whether domain models can verify medication order constraints and locate violations in pediatric rheumatology cases.

A high-quality dataset to enhance the accuracy of drug image recognition in intelligent pharmacy systems.

Evaluate how well models recognize self-harm and suicide risk and respond safely in high-risk psychotherapy dialogues.

The Clinic Electronic Medical Record Q&A Dataset focuses on image data mining in the healthcare field.

Evaluate whether conversational models respect clinical boundaries, avoid unauthorized diagnoses, and recommend professional support when appropriate.

Evaluate how well models verify evidence against pediatric ADHD criteria, one diagnostic constraint at a time.

A time series dataset covering the overall situation of influenza cases in the United States from 2002 to 2021.

Evaluate withdrawal level-of-care recommendations against case-specific constraints and test reasoning in addiction psychiatry.

The CT Imaging Lung Nodule Detection Dataset focuses on improving the accuracy of lung nodule detection in the healthcare sector.

The Dental Clinic X-ray Image Caries Segmentation Dataset is fundamental data for improving caries detection accuracy.

Evaluate a model's ability to validate specialty intake rules using structured referrals that include both compliant and problematic cases.

Evaluate whether models can detect clinical constraint conflicts in medication initiation plans for opioid use disorder and explain their judgments.

The Medical Teaching Image Dataset is a high-quality image resource to assist medical teaching.

This dataset is an effective tool for enhancing the analysis of physical activity behaviors and rehabilitation outcomes in the medical and health field.

Evaluate whether models can identify consistent, conflicting, and inconclusive diagnostic and severity judgments in pediatric diabetic ketoacidosis cases.

Evaluate primary care prescription review against key constraints involving allergies, concomitant medications, dosage, and renal function.

The Accompanied Communication Voice Dialogue Dataset is specifically designed for TTS training to enhance the model's ability to generate speech for everyday communication.

The hospital corridor personnel density estimation dataset is used to improve the accuracy of density estimation models.

Evaluate whether models can detect conflicts, duplicates, and incompatible arrangements across orders in pediatric inpatient care plans.

The Nurse Station Call Voice Command Recognition Dataset is dedicated to improving the accuracy of voice command recognition in medical environments.