A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI | Paper Citation Record

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This paper cites The theory and practice of clinical decision-making.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI The theory and practice of clinical decision-making

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This paper cites Online health: untangling the web.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Online health: untangling the web

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This paper cites Changes in rates of autopsy-detected diagnostic errors over time: a system- atic review.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Changes in rates of autopsy-detected diagnostic errors over time: a system- atic review

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Types and origins of diagnostic errors in primary care set- tings

Reference 4

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This paper cites Diagnostic errors in hospital- ized adults who died or were transferred to intensive care.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Diagnostic errors in hospital- ized adults who died or were transferred to intensive care

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This paper cites National Academies Press; December 29, 2015.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI National Academies Press; December 29, 2015

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This paper cites Diagnostic errors in the emergency depart- ment: a systematic review.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Diagnostic errors in the emergency depart- ment: a systematic review

Reference 7

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This paper cites The ef- fect of Dr Google on doctor-patient encounters in primary care: a quantitative, observational, cross-sectional study.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI The ef- fect of Dr Google on doctor-patient encounters in primary care: a quantitative, observational, cross-sectional study

Reference 8

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Health Online 2013

Reference 9

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This paper cites Assessment of Diagnosis and Triage in Validated Case Vignettes Among Nonphysicians Before and After Internet Search.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Assessment of Diagnosis and Triage in Validated Case Vignettes Among Nonphysicians Before and After Internet Search

Reference 10

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This paper cites A random- ized controlled trial of online symptom search- ing to inform diagnosis.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI A random- ized controlled trial of online symptom search- ing to inform diagnosis

Reference 11

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This paper cites Benchmarking triage capability of symptom checkers against that of medical laypersons: survey study.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Benchmarking triage capability of symptom checkers against that of medical laypersons: survey study

Reference 12

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This paper cites Should you search the Internet for information about your acute symptoms? Telemed J E Health.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Should you search the Internet for information about your acute symptoms? Telemed J E Health

Reference 13

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Internet health infor- mation seeking and the patient-physician re- lationship: A systematic review

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This paper cites KFF Health Mis- information Tracking Poll: Artificial In- telligence and Health Information.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI KFF Health Mis- information Tracking Poll: Artificial In- telligence and Health Information

Reference 15

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This paper cites Appropriateness of Arti- ficial Intelligence Chatbots in Diabetic Foot Ulcer Management.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Appropriateness of Arti- ficial Intelligence Chatbots in Diabetic Foot Ulcer Management

Reference 16

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This paper cites GPT-based chatbot tools are still unreliable in the man- agement of prosthetic joint infections.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI GPT-based chatbot tools are still unreliable in the man- agement of prosthetic joint infections

Reference 17

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This paper cites Ethical concerns and re- sponsible use of ChatGPT in healthcare.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Ethical concerns and re- sponsible use of ChatGPT in healthcare

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This paper cites Protocol For Human Evaluation of Artificial Intelligence Chat- bots in Clinical Consultations.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Protocol For Human Evaluation of Artificial Intelligence Chat- bots in Clinical Consultations

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Balancing Innovation and Professionalism: The Emerging Role of AI-Powered Chatbots in Medical Consultation

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Unresolved cited work

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This paper cites Chatbots in Health Care: Connecting Patients to Information: Emerging Health Technologies.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Chatbots in Health Care: Connecting Patients to Information: Emerging Health Technologies

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Un- derstanding Large Language Models

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI The Breakthrough of Large Language Models Re- lease for Medical Applications: 1-Year Timeline and Perspectives

Reference 24

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI The future landscape of large language models in medicine

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Large Lan- guage Models for Therapy Recommendations Across 3 Clinical Specialties: Comparative Study

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Large lan- guage models for science and medicine

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Evaluation of large language models in breast can- cer clinical scenarios: A comparative analy- sis based on ChatGPT-3.5, ChatGPT-4.0, and Claude2

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Towards A Deep Learning Question-Answering Specialized Chat- bot for Objective Structured Clinical Examina- tions

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Chatbots for Symptom Screening and Patient Education: A Pilot Study on Patient Acceptability in Autoim- mune Inflammatory Diseases

Reference 30

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Diagnostic reasoning: where we’ve been, where we’re going

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Clinical decision making

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI what is likely to happen

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Medicine information needs of patients: the relationships between informa- tion needs, diagnosis and disease

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Diagnostic rea- soning prompts reveal the potential for large language model interpretability in medicine

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Evaluation of symptom checkers for self diagno- sis and triage: audit study

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Patients don’t present with five choices: an alternative to multiple-choice tests in assessing physicians’ competence

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Am- bient artificial intelligence scribes to alle- viate the burden of clinical documentation

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Clinical reasoning assessment meth- ods: a scoping review and practical guidance

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Accuracy of a gen- erative artificial intelligence model in a complex diagnostic challenge

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI How accurate are digital symptom assessment apps for suggesting conditions and urgency advice? A clinical vignettes comparison to GPs

Reference 41

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Chat- GPT influence on medical decision-making, bias, and equity: a randomized study of clin- icians evaluating clinical vignettes

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Com- paring physician and artificial intelligence chatbot responses to patient questions posted to a public social media forum

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Patient- centered decision making and health care out- comes: an observational study

Reference 44

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Towards Conversational Diagnostic AI

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Large language models in medicine: the poten- tials and pitfalls: a narrative review

Reference 46

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This paper cites Appropriateness of cardiovas- cular disease prevention recommendations ob- tained from a popular online chat-based ar- tificial intelligence model.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Appropriateness of cardiovas- cular disease prevention recommendations ob- tained from a popular online chat-based ar- tificial intelligence model

Reference 47

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This paper cites Young Adults’ Perspectives on the Use of Symptom Checkers for Self-Triage and Self-Diagnosis: Qualitative Study.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Young Adults’ Perspectives on the Use of Symptom Checkers for Self-Triage and Self-Diagnosis: Qualitative Study

Reference 48

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This paper cites Ensuring Fairness in Machine Learning to Advance Health Equity.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Ensuring Fairness in Machine Learning to Advance Health Equity

Reference 49

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Search Engines vs

Reference 51

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This paper cites ‘Next please!’ Psychological and practical consequences of an inconclusive diag- Deep Bhatt, Surya Ayyagari and Anuruddh Mishra December 18, 2024 18 nosis.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI ‘Next please!’ Psychological and practical consequences of an inconclusive diag- Deep Bhatt, Surya Ayyagari and Anuruddh Mishra December 18, 2024 18 nosis

Reference 52

Resolution: verified exact; doi, observed 2026-08-11T14:04:40.606289Z

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This paper cites The use of vignettes for conducting healthcare research.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI The use of vignettes for conducting healthcare research

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:04:41.925678Z

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Observation 8fc3ad12-8057-4c48-9584-d398be62be0f · outbound

This paper cites Do case vignettes accurately reflect antibiotic prescription? Infection Control and Hospital Epidemiology.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Do case vignettes accurately reflect antibiotic prescription? Infection Control and Hospital Epidemiology

Reference 54

Resolution: verified exact; doi, observed 2026-08-11T14:04:40.596104Z

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Observation d1b77bf0-81f2-45be-ad9c-7b57ccee2e02 · outbound

This paper cites Vignettes as research tools in global health communication: a systematic review of the literature from 2000 to 2020.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Vignettes as research tools in global health communication: a systematic review of the literature from 2000 to 2020

Reference 55

Resolution: verified exact; raw_fallback, observed 2026-08-11T14:04:41.191570Z

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This paper cites Com- munication with Diverse Patients: Addressing Culture and Language.Pediatric Clinics of North America.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Com- munication with Diverse Patients: Addressing Culture and Language.Pediatric Clinics of North America

Reference 56

Resolution: verified exact; doi, observed 2026-08-11T14:04:40.585513Z

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Observation f10f704b-4dcb-4bd1-81c8-b80571cdb8be · outbound

This paper cites Ex- ploring the role of communication barriers in healthcare.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Ex- ploring the role of communication barriers in healthcare

Reference 57

Resolution: verified exact; raw_fallback, observed 2026-08-11T14:04:41.117432Z

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Observation 13fc7ccf-d03d-46ff-8dfe-d5bdce8742a1 · outbound

This paper cites Recognition of patients with medically un- explained physical symptoms by family physi- cians: results of a focus group study.BMC Family Practice.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Recognition of patients with medically un- explained physical symptoms by family physi- cians: results of a focus group study.BMC Family Practice

Reference 58

Resolution: verified exact; doi, observed 2026-08-11T14:04:40.574462Z

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This paper cites Do Patients Under- stand? The Permanente Journal.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Do Patients Under- stand? The Permanente Journal

Reference 59

Resolution: verified exact; doi, observed 2026-08-11T14:04:40.563979Z

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI The importance of the history and physical in diagnosis

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T14:04:41.915087Z

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Observation cc12c55f-c654-457b-804b-74ee80c7d0d1 · outbound

This paper cites In- ternational variations in primary care physi- cian consultation time: a systematic review of 67 countries.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI In- ternational variations in primary care physi- cian consultation time: a systematic review of 67 countries

Reference 61

Resolution: verified exact; doi, observed 2026-08-11T14:04:40.553263Z

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This paper cites Preva- lence of Occupational Burnout among Resident Doctors Working in Public Sector Hospitals in Mumbai.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Preva- lence of Occupational Burnout among Resident Doctors Working in Public Sector Hospitals in Mumbai

Reference 62

Resolution: verified exact; doi, observed 2026-08-11T14:04:40.542624Z

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Observation 6bc82e7e-c92e-472d-9ea2-31cb2cd2aded · outbound

This paper cites Eval- uating the Diagnostic Performance of Symp- tom Checkers: Clinical Vignette Study.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Eval- uating the Diagnostic Performance of Symp- tom Checkers: Clinical Vignette Study

Reference 63

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Observation 7e00d90b-862a-43e3-afe7-98cdfc837dd7 · outbound

This paper cites A systematic review of trustworthy and explainable artificial intelligence in healthcare: Assessment of quality, bias risk, and data fusion.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI A systematic review of trustworthy and explainable artificial intelligence in healthcare: Assessment of quality, bias risk, and data fusion

Reference 64

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Evalu- ation framework to guide implementation of AI systems into healthcare settings

Reference 65

Resolution: malformed identifier; doi_truncated, observed 2026-08-11T14:04:40.525790Z

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This paper cites What Disease Does This Patient Have? A Large-Scale Open Domain Question Answering Dataset from Med- ical Exams.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI What Disease Does This Patient Have? A Large-Scale Open Domain Question Answering Dataset from Med- ical Exams

Reference 66

Resolution: unresolved; no resolver link, observed 2026-08-11T14:04:40.475563Z

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This paper cites WHO and ITU establish benchmarking process for artificial intelligence in health.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI WHO and ITU establish benchmarking process for artificial intelligence in health

Reference 67

Resolution: malformed identifier; no resolver link, observed 2026-08-11T14:04:40.479370Z

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A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Unresolved cited work

Reference 173

Resolution: verified exact; raw_fallback, observed 2026-08-11T14:04:41.828559Z

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Observation 7a725f8e-d38d-46c4-ab46-fdd111b6205d · outbound

This paper cites an unresolved cited work.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Unresolved cited work

Reference 2014

Resolution: verified exact; raw_fallback, observed 2026-08-11T14:04:41.043691Z

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Observation e9b99c61-7c13-4c20-bc36-be9bf952e1a6 · outbound

This paper cites an unresolved cited work.

A Scalable Approach to Benchmarking the In-Conversation Differential Diagnostic Accuracy of a Health AI Unresolved cited work

Reference 2024

Resolution: verified exact; doi, observed 2026-08-11T14:04:40.810100Z

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No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

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