Platforms
Expert Network
Build & Train AI
Vertical AI
Explore our full suite of AI platforms, data marketplaces, and expert services designed to build, train, fine-tune, and deploy reliable, production-grade AI systems at scale.
Platforms
Expert Network
Build & Train AI
Vertical AI
Explore our full suite of AI platforms, data marketplaces, and expert services designed to build, train, fine-tune, and deploy reliable, production-grade AI systems at scale.
Platforms
Expert Network
Build & Train AI
Vertical AI
Explore our full suite of AI platforms, data marketplaces, and expert services designed to build, train, fine-tune, and deploy reliable, production-grade AI systems at scale.
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PRISM Evaluation Suite · v2.0 · June 2026
Benchmarking AI
across seven domains
The PRISM suite provides rigorous assessments of frontier models across Internationalization, Audio, Vision, Agentic & RL, Physical AI, Healthcare, and AI Safety.
7
Domains
14
Benchmarks
25K+
Eval Tasks
50+
Models Evaluated
PRISM Evaluation Suite · v2.0 · June 2026
Benchmarking AI
across seven domains
The PRISM suite provides rigorous assessments of frontier models across Internationalization, Audio, Vision, Agentic & RL, Physical AI, Healthcare, and AI Safety.
7
Domains
14
Benchmarks
25K+
Eval Tasks
50+
Models Evaluated
PRISM Evaluation Suite · v2.0 · June 2026
Benchmarking AI
across seven domains
The PRISM suite provides rigorous assessments of frontier models across Internationalization, Audio, Vision, Agentic & RL, Physical AI, Healthcare, and AI Safety.
7
Domains
14
Benchmarks
25K+
Eval Tasks
50+
Models Evaluated
PRISM Evaluation Suite · v2.0 · June 2026
Benchmarking AI
across seven domains
The PRISM suite provides rigorous assessments of frontier models across Internationalization, Audio, Vision, Agentic & RL, Physical AI, Healthcare, and AI Safety.
7
Domains
14
Benchmarks
25K+
Eval Tasks
50+
Models Evaluated
PRISM-Health
3 Benchmarks
Clinical & Healthcare AI Evaluation
Rigorous evaluation of AI as a clinical agent — execution-grounded EHR workflows and medical audio reasoning, validated against board-certified clinician judgement.
CareTransition-Audit: A Benchmark to Audit Discharge Summaries for Efficient Care Transitions
A structured audit of 100 de-identified hospital discharge summaries from MIMIC-IV against a 46-item clinical documentation rubric. Each item is a yes/no/unclear/N-A question covering whether a specific piece of information is present in the summary (allergies, medication reconciliation, follow-up plans, etc.). Items are grouped into 10 components: Demographic Information (D), Important alerts (I), Social setup (S), Comprehensive Past Medical History (C), Goals of care (G), Record of Medication Changes (R), Expected Follow-up Instructions (E), History of Presenting Complaint & Physical Examination (H), Assessment & Clinical Course (A), and Additional Documentation items (Add.). 8 of the 46 items are conditional and allow N/A. Models return structured output with answer, evidence, and justification per question; agreement with the clinician gold standard is summarized by accuracy, macro/weighted F1, and Cohen’s κ. Clinician Labels — the clinician gold standard marks 0.78 of items "yes" per summary on average. Model completeness ranges from 0.55 (Qwen 2.5-7B) to 0.75 (Gemini 3 Flash Preview), with Gemini closest to the clinician baseline.
CareTransition-Audit: A Benchmark to Audit Discharge Summaries for Efficient Care Transitions
A structured audit of 100 de-identified hospital discharge summaries from MIMIC-IV against a 46-item clinical documentation rubric. Each item is a yes/no/unclear/N-A question covering whether a specific piece of information is present in the summary (allergies, medication reconciliation, follow-up plans, etc.). Items are grouped into 10 components: Demographic Information (D), Important alerts (I), Social setup (S), Comprehensive Past Medical History (C), Goals of care (G), Record of Medication Changes (R), Expected Follow-up Instructions (E), History of Presenting Complaint & Physical Examination (H), Assessment & Clinical Course (A), and Additional Documentation items (Add.). 8 of the 46 items are conditional and allow N/A. Models return structured output with answer, evidence, and justification per question; agreement with the clinician gold standard is summarized by accuracy, macro/weighted F1, and Cohen’s κ. Clinician Labels — the clinician gold standard marks 0.78 of items "yes" per summary on average. Model completeness ranges from 0.55 (Qwen 2.5-7B) to 0.75 (Gemini 3 Flash Preview), with Gemini closest to the clinician baseline.
Rankings
0-shot Careful WER
WER vs N-Shots (Random Context)
Lower = better · gpt-4o-audio best improver
MM · Sample Tasks
Sample task 1 of 1
CareTransition-Audit · Discharge Summary Completeness
Task Prompt
You are a clinical documentation auditor who works on demographic information and patient alerts. You will be given a discharge summary. Your task is to answer the following audit questions based ONLY on the information present in the discharge summary. Note: - You are working with a de-identified dataset, information maybe explicitly stated but the details of it maybe blank (e.g. contact information) - Give justification clearly when dealing with information which has blanks or dashes Rules: - Do NOT infer or assume information. - Answers must be strictly one of: "Yes", "No", "Unclear", or "N/A". - Use "Unclear" ONLY if partial or ambiguous information is present. - If the information is completely absent, answer "No". - Use "N/A" ONLY when the question's precondition does not apply (e.g., a conditional question whose triggering condition is not met). - Evidence must be a direct quote or exact phrase(s) from the discharge summary. - Justification must briefly explain why the evidence supports the selected answer. - Do NOT add any content outside the specified JSON structure. Audit Questions for Demographic Information: 1) Are basic patient demographics (age or date of birth, and sex) documented in the discharge summary? 2) Is a patient identifier (e.g. name, medical record number, or patient identification number) documented, even if de-identified? 3) Is patient contact information (e.g. address or phone number) documented, even if de-identified or blank? Audit Questions for Important Alerts: 1) Is the patient's allergy status documented (either specific allergies listed, or an explicit statement such as NKDA/NDA/no known allergies)? 2) If specific allergies are listed, are the allergens and their reaction types (e.g. rash, anaphylaxis) documented? Answer "N/A" if the patient is documented as having no allergies. 3) Are any other clinical alerts documented, such as adverse drug reactions, special risks, or precautions? -------------------- Output Format (STRICT - valid JSON only): { "D": { "1": { "answer": "Yes/No/Unclear", "evidence": "Exact quoted text or Not documented", "justification": "Brief explanation linking the evidence to the answer" }, "2": { "answer": "Yes/No/Unclear", "evidence": "Exact quoted text or Not documented", "justification": "Brief explanation linking the evidence to the answer" }, "3": { "answer": "Yes/No/Unclear", "evidence": "Exact quoted text or Not documented", "justification": "Brief explanation linking the evidence to the answer" } }, "I": { "1": { "answer": "Yes/No/Unclear", "evidence": "Exact quoted text or Not documented", "justification": "Brief explanation linking the evidence to the answer" }, "2": { "answer": "Yes/No/Unclear/N/A", "evidence": "Exact quoted text or Not documented", "justification": "Brief explanation linking the evidence to the answer" }, "3": { "answer": "Yes/No/Unclear", "evidence": "Exact quoted text or Not documented", "justification": "Brief explanation linking the evidence to the answer" } } } ------------------------- Discharge Summary: [Patient Summary]
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